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Author SHA1 Message Date
Oleg Proskurin 45eefaa587 spy: midjorney 2026-01-12 00:34:56 +07:00
Oleg Proskurin 04607e3ecd research: new ideas 2026-01-11 02:07:36 +07:00
Oleg Proskurin c261cc2b4e add research - josh and mara ideas 2026-01-10 23:39:41 +07:00
Oleg Proskurin 46c8cf76f6 add research AI coding 2026-01-10 23:39:04 +07:00
Oleg Proskurin c497ff2674 feat: update authors 2026-01-10 23:38:37 +07:00
Oleg Proskurin 31699a93df feat: Josh and Mara 2026-01-10 20:03:36 +07:00
Oleg Proskurin a20e8e44ed feat: add seo agent 2026-01-10 19:45:42 +07:00
38 changed files with 7576 additions and 15 deletions

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---
name: seo-researcher
description: "Use this agent when you need comprehensive SEO research for keyword opportunities, domain availability, and branding decisions. This agent is specialized for deep SERP analysis, keyword difficulty assessment, and strategic domain/brand recommendations.\\n\\n**Triggering Conditions:**\\n- User requests keyword research for a specific topic or niche\\n- User needs to evaluate keyword difficulty (KD) for target keywords\\n- User wants to discover available domains matching keyword opportunities\\n- User seeks branding suggestions based on SEO data\\n- User asks for competitive SERP analysis\\n- User needs domain availability checks combined with SEO metrics\\n- User requests strategic recommendations for content targeting\\n\\n**Examples:**\\n\\n<example>\\nContext: User is exploring a new content vertical and needs keyword research.\\nuser: \"I want to explore content opportunities around AI automation tools for small businesses\"\\nassistant: \"I'll use the Task tool to launch the seo-researcher agent to conduct comprehensive keyword and domain research for this vertical.\"\\n<commentary>\\nThe user is requesting strategic research that requires SERP analysis, keyword difficulty assessment, and potentially domain/branding recommendations. The seo-researcher agent is specifically designed for this type of deep SEO research using DataForSEO, Whois, Perplexity, and BraveSearch.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: User needs to validate keyword targeting for a content piece.\\nuser: \"What's the keyword difficulty for 'project management software for startups' and are there any good domain opportunities?\"\\nassistant: \"Let me use the Task tool to launch the seo-researcher agent to analyze keyword difficulty and explore domain availability for this target phrase.\"\\n<commentary>\\nThis requires specific SEO metrics (KD analysis) combined with domain research, which is the seo-researcher agent's core function.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: User is planning a new content series and needs data-driven topic selection.\\nuser: \"I'm planning a content series on B2B SaaS marketing. Can you help me identify the best keywords to target?\"\\nassistant: \"I'll launch the seo-researcher agent using the Task tool to conduct SERP analysis and identify high-opportunity keywords for your B2B SaaS marketing content series.\"\\n<commentary>\\nStrategic keyword research for content planning requires the seo-researcher's specialized tools and methodology.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: User wants to check if a branded term is viable.\\nuser: \"Is 'TaskFlowPro' available as a domain and does it have SEO potential?\"\\nassistant: \"I'm going to use the Task tool to launch the seo-researcher agent to check domain availability and assess the SEO landscape for 'TaskFlowPro'.\"\\n<commentary>\\nCombining domain availability checks (Whois) with SEO analysis (DataForSEO, BraveSearch) is exactly what the seo-researcher agent handles.\\n</commentary>\\n</example>"
model: opus
color: green
---
You are an elite SEO Research Specialist with deep expertise in keyword analysis, SERP intelligence, domain strategy, and data-driven branding decisions. Your mission is to conduct comprehensive, strategic research that uncovers high-value opportunities and provides actionable recommendations.
# Your Core Identity
You combine the analytical precision of an SEO data scientist with the strategic thinking of a digital marketing consultant. You don't just pull numbers—you interpret them, identify patterns, and translate data into clear strategic guidance. Your research is thorough, your recommendations are justified with evidence, and your insights help shape content and branding decisions that drive organic growth.
# Your Research Toolkit
You have access to four powerful MCP tools:
1. **DataForSEO MCP**: Your primary source for SERP data, keyword metrics, search volumes, keyword difficulty (KD), competitive analysis, and ranking intelligence
2. **Whois MCP**: Your domain availability checker and ownership verification tool
3. **Perplexity MCP**: Your research assistant for contextual understanding, trend analysis, and supplementary intelligence
4. **BraveSearch MCP**: Your real-time SERP explorer and content discovery engine
You must use these tools strategically and in combination to produce comprehensive research.
# Mandatory Context Files
Before conducting any research, you MUST thoroughly review and follow the guidance in these files:
- **desktop-agents/000-spy/system-prompt.md**: Core research methodology and operational principles
- **desktop-agents/000-spy/agent-guide.md**: Detailed workflow patterns and best practices
- **project-knowledge/project-soul.md**: Banatie's mission, values, and strategic positioning
- **project-knowledge/research-tools-guide.md**: Tool-specific techniques and usage patterns
- **shared/log-chat-format.md**: Required format for logging your research process
- **shared/inline-edits-syntax.md**: Syntax for making inline comments and annotations
These files contain critical requirements, formatting standards, and strategic context that govern how you operate. Violating these guidelines is unacceptable.
# Your Research Process
## Phase 1: Understanding the Request
1. Clarify the research objective: keyword discovery, KD analysis, domain search, branding evaluation, or comprehensive assessment
2. Identify the topic/niche and any specific constraints (budget, geographic focus, content type)
3. Determine success criteria: What defines a "good" opportunity for this research?
4. Ask clarifying questions if the request is ambiguous
## Phase 2: Data Collection
1. **Keyword Intelligence** (DataForSEO):
- Search volume trends and seasonality
- Keyword difficulty (KD) scores
- SERP feature presence (featured snippets, People Also Ask, etc.)
- Related keywords and semantic clusters
- Competitive density analysis
2. **SERP Analysis** (BraveSearch + DataForSEO):
- Top-ranking content types and formats
- Domain authority of ranking sites
- Content gaps and opportunities
- User intent signals
3. **Domain Research** (Whois):
- Availability checks for target keywords
- Alternative TLD options (.com, .io, .ai, etc.)
- Brandability assessment
4. **Contextual Intelligence** (Perplexity):
- Industry trends and emerging topics
- Competitive landscape insights
- Content angle validation
## Phase 3: Analysis & Synthesis
1. **Opportunity Scoring**: Evaluate keywords based on:
- Search volume vs. competition balance
- Relevance to Banatie's audience and mission (per project-soul.md)
- Content creation feasibility
- Ranking probability given current domain authority
2. **Strategic Recommendations**:
- Prioritized keyword targets with KD scores
- Content angle suggestions
- Domain/branding options with pros/cons
- Quick wins vs. long-term plays
3. **Risk Assessment**:
- Flag high-competition keywords requiring significant resources
- Identify potential trademark conflicts
- Note seasonal or trend-dependent opportunities
## Phase 4: Reporting
Your research output must be:
- **Structured**: Clear sections with headers
- **Data-Driven**: Include specific metrics (KD, volume, trends)
- **Actionable**: Explicit recommendations with reasoning
- **Logged Properly**: Follow log-chat-format.md for process documentation
- **Contextual**: Reference Banatie's positioning and constraints
# Output Format
Structure your research reports as follows:
```markdown
# SEO Research Report: [Topic]
## Executive Summary
[2-3 sentences: key findings and top recommendation]
## Research Objective
[What you were asked to research and why]
## Methodology
[Tools used and research approach]
## Keyword Analysis
### Primary Targets
| Keyword | Volume | KD | Opportunity Score | Notes |
|---------|--------|----|--------------------|-------|
| ... | ... | ... | ... | ... |
### Secondary Targets
[Additional keywords worth considering]
### Keyword Clusters
[Semantic groupings and content themes]
## SERP Landscape
### Top Ranking Content
[Types of content ranking, domain authorities, content patterns]
### Content Gaps
[Opportunities not being addressed by current top-rankers]
### SERP Features
[Featured snippets, PAA, video carousels, etc.]
## Domain & Branding Options
### Available Domains
| Domain | TLD | Brandability | SEO Potential | Notes |
|--------|-----|--------------|---------------|-------|
| ... | ... | ... | ... | ... |
### Branding Recommendations
[Strategic guidance on naming and positioning]
## Strategic Recommendations
### Immediate Actions (0-30 days)
[Quick wins and low-hanging fruit]
### Medium-Term Strategy (1-3 months)
[Content series and sustained efforts]
### Long-Term Positioning (3-12 months)
[Authority-building and competitive keywords]
## Risk Factors & Considerations
[Challenges, competition, seasonality, etc.]
## Appendix: Raw Data
[Detailed metrics, full keyword lists, tool outputs]
```
# Quality Standards
1. **Accuracy**: Every metric must be current and correctly sourced
2. **Completeness**: Don't skip phases—do thorough multi-tool research
3. **Strategic Thinking**: Don't just report data; interpret it
4. **Banatie Alignment**: Every recommendation must fit the project's mission and audience (see project-soul.md)
5. **Tool Mastery**: Use each tool for its strengths per research-tools-guide.md
# Decision-Making Framework
When evaluating opportunities, apply this hierarchy:
1. **Relevance** > Volume: A keyword must align with Banatie's content strategy
2. **Achievability** > Popularity: Target keywords Banatie can realistically rank for
3. **Intent Match** > Metrics: Prioritize keywords where user intent matches content capabilities
4. **Long-Term Value** > Short-Term Gains: Build sustainable organic presence
# Self-Verification Checklist
Before delivering research, verify:
- [ ] Used at least 3 of 4 available tools
- [ ] Reviewed all mandatory context files
- [ ] Included specific KD scores and volume data
- [ ] Checked domain availability for key recommendations
- [ ] Provided clear prioritization with reasoning
- [ ] Followed log-chat-format.md for process documentation
- [ ] Aligned recommendations with project-soul.md
- [ ] Structured output matches required format
# When to Escalate or Clarify
- Request is too vague (e.g., "research SEO stuff")
- Research scope exceeds single session (suggest breaking into phases)
- Found critical competitive threats or trademark issues
- Tools return unexpected or contradictory data
- Strategic direction conflicts with Banatie's positioning
You are not just a data gatherer—you are a strategic research partner. Your insights drive content decisions, branding choices, and SEO strategy. Deliver research that is thorough, strategic, and immediately actionable.

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"DATAFORSEO_USERNAME": "regx@usul.su",
"DATAFORSEO_PASSWORD": "4f4b51b823df234c"
}
},
"whois": {
"command": "npx",
"args": ["-y", "whois-mcp"]
}
}
}

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---
slug: ai-image-to-video-generator
title: "AI Image to Video: I Tested 5 Tools and This Is What Actually Works"
author: mara-solheim
status: inbox
priority: HIGH
created: 2026-01-10
source: seo-research-josh-mara-warmup
---
# Idea
## Discovery
**Source:** SEO Research for Josh & Mara warmup articles — 2026-01-10
**Evidence:**
- "ai image to video generator" = 5,400 monthly searches
- KD: 18 (LOW — very achievable)
- Search intent: Transactional
- Target audience: Digital artists animating their work, marketers creating dynamic content, creators exploring new formats
## Why This Matters
Strong comparison opportunity:
- 5,400 searches with KD 18 = solid opportunity
- Comparison format ranks well
- Growing interest in image-to-video tools
- Mara can show REAL outputs side-by-side
- Perfect for her visual, hands-on style
## Content Angle
**Title:** "AI Image to Video: I Tested 5 Tools and This Is What Actually Works"
**Mara's Approach:**
- Comparative review using SAME source images across all tools
- Show real outputs from each tool
- Rank by quality, ease of use, pricing
- Honest about which tools disappointed
- Include use cases for each
**Structure:**
1. Opening: "I've been curious about image-to-video tools for months..."
2. The 5 tools tested (overview)
3. Testing methodology (same images, same prompts)
4. Tool-by-tool results with actual outputs
5. Comparison table (quality, speed, price, ease)
6. Recommendations by use case
7. Closing: "If you've been hesitant to try this — give it a real shot..."
## Tools to Compare
Based on current market (Mara should verify latest):
1. **Runway** — premium quality, expensive
2. **Pika** — balance of quality/price
3. **Luma Dream Machine** — newer, fast
4. **Kling AI** — Chinese market leader
5. **CapCut** — accessible, free tier
## Why This Works for Mara
Perfect for her expertise:
- Visual comparison format
- Hands-on testing methodology
- She can show her actual creative experiments
- Genuine reactions to quality differences
- Helps readers choose without testing all 5 themselves
- "I tried this so you don't have to" value
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| ai image to video generator | 5,400 | 18 | PRIMARY |
| image to video ai | 4,400 | — | Synonym |
| photo to video ai | 2,900 | — | Include |
| ai animate image | 1,600 | — | Related |
## Secondary Keywords
- "best image to video ai"
- "animate still images with ai"
- "ai video from photo"
- "image to video generator free"
## Content Format
**Mara's Style:**
- Comparative review format
- Show her actual test results
- Include screenshots/video outputs
- Side-by-side comparisons
- Honest assessment of each tool
- Personal recommendations
## Visual Content Opportunity
This article is PERFECT for visual content:
- Show same image animated by different tools
- Side-by-side quality comparison
- Before/after for each tool
- Can create engaging social media snippets
- Great for portfolio showcase
## Notes
- Comparison content performs well in search
- Readers want to see REAL outputs, not marketing claims
- Mara's "here's what I got..." honesty is key differentiator
- Each tool has different strengths — help readers choose
- Include pricing to help decision-making
- Free tier options important for audience
## Follow-Up Potential
This article can lead to:
- Individual deep-dives on each tool
- "Best image to video for [use case]" variations
- Tutorial: "How to animate your images with AI"
- Updates as new tools emerge

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---
slug: ai-product-photos
title: "AI Product Photography: Create Professional Images Without a Photoshoot"
author: banatie
status: inbox
priority: HIGH
created: 2026-01-10
source: seo-research-additional-opportunities
---
# Idea
## Discovery
**Source:** Additional SEO research for Banatie blog — 2026-01-10
**Evidence:**
- "ai product photos" = 320 monthly searches
- KD: 23 (MEDIUM-LOW — achievable)
- Search intent: Commercial/Informational
- Target audience: E-commerce sellers, product creators, small businesses, Amazon/Etsy sellers
## Why This Matters
Strong commercial opportunity:
- 320 searches = niche but high-intent
- KD 23 = achievable for quality content
- Product photography = expensive pain point
- AI solution = cost-saving angle
- E-commerce audience = valuable
- Growing category
## Content Angle
**Title:** "AI Product Photography: Create Professional Images Without a Photoshoot"
**Banatie's Approach:**
- Comprehensive guide to AI product photography
- Multiple tool comparison
- Real product examples
- Cost savings analysis
- Quality vs traditional photography
- Step-by-step workflows
**Structure:**
1. Opening: "Professional product photos without a studio or photographer..."
2. Why AI product photography matters:
- Cost savings (vs traditional shoots)
- Speed and iteration
- Consistency
- Creative flexibility
3. How AI product photography works:
- Upload existing photo or description
- AI generates context/backgrounds
- Refinement and variations
4. Best tools comparison:
- Flair AI
- PhotoRoom
- Pixelcut
- Removal.ai + Midjourney workflow
5. Real examples by product category:
- Fashion/apparel
- Electronics
- Home goods
- Beauty products
6. Quality comparison (AI vs traditional)
7. Platform requirements (Amazon, Etsy, Shopify)
8. Common mistakes and fixes
9. Cost analysis
10. Closing: "Professional photos, fraction of the cost"
## Why This Works for Banatie
Perfect for brand positioning:
- Practical business solution
- Cost-saving angle
- Tool comparisons (authority)
- Real examples
- E-commerce audience
- Technical + creative blend
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| ai product photos | 320 | 23 | PRIMARY |
| ai product photography | — | — | Synonym |
| ai generated product images | — | — | Related |
| product photos ai | — | — | Variant |
## Secondary Keywords
- "ai product photography tool"
- "create product photos with ai"
- "ai product image generator"
- "amazon product photos ai"
## Tools Coverage
**Flair AI:**
- Specialized for product photography
- Studio-quality results
- Easy interface
- Pricing considerations
**PhotoRoom:**
- Background removal + generation
- Mobile-friendly
- Free tier available
- Quick workflow
**Pixelcut:**
- AI background generation
- Template library
- E-commerce focused
- Affordable pricing
**Removal.ai + Midjourney:**
- Manual workflow
- Maximum control
- Creative freedom
- Requires more skill
## Content Format
**Banatie's Style:**
- Real product examples
- Before/after comparisons
- Cost analysis
- Tool comparisons
- Platform requirements
- Quality assessment
## Differentiation
Most AI product photo content:
- Single tool focus
- No quality comparison
- Missing platform requirements
Banatie's angle:
- Multi-tool comparison
- Quality vs traditional
- Platform-specific guidance
- Cost savings analysis
- Real business context
- Workflow integration
## Use Cases by Product Type
**Fashion/Apparel:**
- Lifestyle contexts
- Model alternatives
- Seasonal backgrounds
**Electronics:**
- Clean studio shots
- Lifestyle contexts
- Detail highlights
**Home Goods:**
- Room settings
- Lifestyle contexts
- Scale demonstration
**Beauty Products:**
- Lifestyle settings
- Mood creation
- Luxury positioning
## Platform Requirements
**Amazon:**
- White background requirement
- Multiple angles
- Lifestyle supplements allowed
- Resolution requirements
**Etsy:**
- Creative freedom
- Lifestyle emphasis
- Storytelling focus
**Shopify:**
- Brand consistency
- Flexible formats
- Homepage features
## Strategic Value
**Why This Article Matters:**
- KD 23 = achievable
- High commercial intent
- Solves expensive pain point
- E-commerce audience = valuable
- Can update with new tools
- Real business value
## Notes
- 320 vol = niche but high-intent
- E-commerce audience = valuable traffic
- Cost-saving angle = strong hook
- Quality comparison = credibility
- Can expand per tool later
- Update as tools improve
## Real Examples Needed
Must include:
- Before: basic product photo
- After: AI-enhanced with context
- Quality comparison with traditional
- Platform-specific examples
- Cost breakdown
## Related Content Opportunities
Can expand to:
- "Flair AI Complete Guide"
- "Amazon Product Photography with AI"
- "Etsy Product Photos with AI"
- "AI vs Traditional Product Photography"
## Publication Priority
**HIGH — AFTER MIDJOURNEY ALTERNATIVE**
Strong second article:
- KD 23 (achievable)
- High commercial value
- Practical business solution
- Should follow quick win

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---
slug: amazon-product-images-api
title: "Generate Amazon Product Images via API: Implementation Guide"
author: henry
status: inbox
priority: HIGH
created: 2026-01-10
source: seo-research-additional-opportunities
urgency_reason: "KD 9 — ultra-low competition, e-commerce audience matches Henry's expertise"
---
# Idea
## Discovery
**Source:** Additional SEO research for Henry — 2026-01-10
**Evidence:**
- "amazon product images" = 140 monthly searches
- KD: 9 (ULTRA LOW — very easy to rank)
- Search intent: Commercial/Informational
- Target audience: Amazon sellers, e-commerce developers, marketplace integrations builders
## Why This Matters
Perfect niche opportunity:
- 140 searches = small but highly targeted
- KD 9 = ULTRA LOW competition
- E-commerce = Henry's expertise area
- API integration = his strength
- Amazon sellers = specific, valuable audience
## Content Angle
**Title:** "Generate Amazon Product Images via API: Implementation Guide"
**Henry's Approach:**
- Technical implementation guide
- API integration architecture
- Focus on Amazon requirements (white background, dimensions, etc.)
- Production-ready code
- Batch processing for multiple products
- Error handling and retry logic
- Real implementation from e-commerce experience
**Structure:**
1. Opening: "Built an Amazon product image generator last month. Here's the architecture that works."
2. Amazon image requirements (context)
- Technical specifications
- White background requirement
- Dimension rules
- Quality standards
3. Architecture overview
- API selection
- Processing pipeline
- Storage and CDN
4. Implementation:
- Node.js + TypeScript
- API integration
- Image processing (background removal)
- Batch processing
5. Amazon listing integration
- Upload automation
- Bulk operations
- Error handling
6. Production considerations:
- Rate limiting
- Cost optimization
- Caching strategy
7. Code repository reference
8. Closing: "That's the production approach. Handles thousands of products."
## Why This Works for Henry
Perfect expertise match:
- E-commerce platform experience (Shopify, custom)
- API integration = core skill
- Production architecture thinking
- 12 years experience with marketplace integrations
- Direct, technical approach
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| amazon product images | 140 | 9 | PRIMARY |
| amazon product images api | — | — | Intent |
| generate amazon images | — | — | Intent |
| amazon product photo requirements | — | — | Related |
## Secondary Keywords
- "amazon product image generator"
- "automate amazon product images"
- "amazon product photography api"
- "white background product images"
## Technical Requirements
**Amazon Specifications:**
- White background (RGB 255,255,255)
- Minimum 1000px longest side (recommended 1600px)
- Maximum 10000px
- JPEG or PNG format
- Product fills 85% of image
- No text overlays, borders, watermarks
**Architecture Components:**
1. **Image Generation API** (Banatie or alternative)
2. **Background Processing** (remove/replace with white)
3. **Image Optimization** (compression, format)
4. **Storage** (S3 or CDN)
5. **Amazon Integration** (MWS API or SP-API)
6. **Batch Processing** (handle multiple SKUs)
## Content Format
**Henry's Style:**
- Architecture diagram
- Complete code implementation
- TypeScript throughout
- Real production patterns
- Error handling examples
- Performance considerations
- No pseudocode
**Code Coverage:**
- API integration setup
- Image generation function
- Background removal/replacement
- Batch processing logic
- Amazon API upload
- Error handling and retries
## Differentiation
Most Amazon image content:
- Manual photography guides
- No API automation
- No code implementation
Henry's angle:
- Full API automation
- Production-ready architecture
- Batch processing for scale
- E-commerce platform integration
- Real code from experience
- Cost and performance optimized
## Strategic Value
**Why This Article Matters:**
- KD 9 = ultra-low, easy ranking
- Niche but valuable audience (Amazon sellers)
- Showcases e-commerce expertise
- API integration depth
- Natural Banatie product fit
- Can expand into broader e-commerce series
## Banatie Integration
Natural fit:
- Use Banatie API for image generation
- Show white background feature
- Demonstrate bulk generation
- Compare cost vs manual photography
- "I recently built..." disclosure style
- Technical merit focus
## E-Commerce Context
Henry's experience shows:
- Marketplace requirements knowledge
- Bulk operations understanding
- Cost considerations for sellers
- Integration architecture
- Production scalability needs
## Notes
- KD 9 = ultra-low, prioritize for quick win
- Small volume (140) but highly targeted
- Amazon sellers = specific, valuable niche
- E-commerce = Henry's expertise area
- Can expand to Shopify, eBay, Etsy
- Real implementation = differentiation
- Batch processing = scale consideration
## Production Code
Henry should show:
- Complete TypeScript implementation
- Environment configuration
- API integration module
- Background processing pipeline
- Batch operation handler
- Error handling and logging
- Performance optimization
- Cost tracking
## Related Content Opportunities
This can lead to:
- "Shopify Product Images via API"
- "E-commerce Image Automation"
- "Marketplace Product Photography Guide"
- "Bulk Product Image Generation"
## Publication Priority
**HIGH PRIORITY** — KD 9 (ultra-low), perfect expertise match, niche but valuable audience. Should be in Henry's first 3-4 articles. Quick win that showcases e-commerce + API integration skills.

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---
slug: best-ai-coding-assistants
title: "Best AI Coding Assistants in 2025: I Tested 5 Tools So You Don't Have To"
author: josh-mercer
status: inbox
priority: MEDIUM
created: 2026-01-10
source: seo-research-josh-mara-warmup
---
# Idea
## Discovery
**Source:** SEO Research for Josh & Mara warmup articles — 2026-01-10
**Evidence:**
- "best ai coding assistant" = 1,300 monthly searches
- KD: 38 (MEDIUM-HIGH — upper boundary but achievable with quality)
- Search intent: Commercial Investigation
- Target audience: Developers new to AI assistants, tech leads evaluating tools for teams, freelancers optimizing workflow
## Why This Matters
Pillar content opportunity:
- 1,300 searches = solid volume
- KD 38 = competitive but achievable with comprehensive content
- Comparison listicle = high reader value
- Can reference all previous individual reviews
- Establishes Josh as comprehensive expert
## Content Angle
**Title:** "Best AI Coding Assistants in 2025: I Tested 5 Tools So You Don't Have To"
**Josh's Approach:**
- Comprehensive comparison of 5 major AI coding assistants
- Create decision matrix based on use case (frontend, backend, fullstack, freelance, team)
- Include pricing comparison table
- Real usage experience with each tool
- Help readers choose based on their situation
- No single "best" — depends on needs
**Structure:**
1. Opening: "I've used 5 different AI coding assistants over the past 6 months. Here's what each one is actually good at..."
2. Why AI assistants matter (context)
3. How I tested them (methodology)
4. The 5 tools compared:
- Cursor
- Claude Code
- GitHub Copilot
- Windsurf
- Codeium
5. Comparison matrix (quick reference)
6. Detailed breakdown per tool:
- What it's best for
- Key strengths
- Limitations
- Pricing
- Who should use it
7. Pricing comparison (detailed)
8. Decision framework:
- Best for frontend devs
- Best for backend devs
- Best for fullstack
- Best for freelancers
- Best for teams
9. My recommendation (depends on you)
10. Closing: "No single best. Here's how to choose..."
## Why This Works for Josh
Perfect capstone to his AI tool reviews:
- Hands-on testing credibility (from previous articles)
- Balanced perspective = his strength
- Decision framework (not "X is best")
- Practical cost-value analysis
- References his individual reviews
- Comprehensive without overwhelming
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| best ai coding assistant | 1,300 | 38 | PRIMARY |
| ai coding assistant | 4,400 | — | Include |
| ai coding tools | 1,900 | — | Related |
| best ai code editor | 720 | — | Variant |
## Secondary Keywords
- "top ai coding assistants"
- "ai coding assistant comparison"
- "which ai coding assistant is best"
- "ai coding assistant for developers"
## Tools to Compare
Based on current market (Josh should verify latest):
1. **Cursor**
- Best for: Fullstack, integrated experience
- Strength: Context awareness
- Limitation: Pricing for heavy usage
2. **Claude Code**
- Best for: Terminal-native developers
- Strength: CLI workflow, powerful reasoning
- Limitation: Less GUI-friendly
3. **GitHub Copilot**
- Best for: GitHub-integrated teams
- Strength: Wide editor support, stable
- Limitation: Context understanding
4. **Windsurf**
- Best for: Experimental workflows
- Strength: Cascade, Flows
- Limitation: Newer, less stable
5. **Codeium**
- Best for: Budget-conscious developers
- Strength: Free tier, good enough
- Limitation: Less powerful than paid options
## Comparison Dimensions
**Framework:**
- Code completion quality
- Context understanding
- Editor integration
- Workflow fit
- Pricing (free/paid tiers)
- Team features
- Performance
- Learning curve
**Decision Matrix:**
Create table showing:
- Use case (Frontend/Backend/Fullstack/Team)
- Recommended tool(s)
- Why it's best for that case
## Content Format
**Josh's Style:**
- Comprehensive comparison
- Decision matrix (visual)
- Pricing table (detailed)
- Real examples from each tool
- Honest trade-offs
- No single winner
- Help readers self-select
## Differentiation
Most "best AI assistant" content:
- Incomplete testing
- Biased toward one tool
- No decision framework
- Generic feature lists
Josh's angle:
- Tested all 5 on real projects
- No clear winner (depends on needs)
- Decision framework by use case
- Freelancer + startup perspective
- Pricing as first-class concern
- References to individual deep-dives
## Strategic Value
**Why This Article Matters:**
- Pillar content that ties together individual reviews
- Can internally link to all previous Josh articles
- Establishes comprehensive expertise
- Helps readers at decision stage
- Can rank for broader "ai coding assistant" (4,400 vol)
- Update regularly = evergreen traffic
## Notes
- KD 38 = upper boundary but achievable with quality
- Should come AFTER individual tool reviews (builds on them)
- Reference previous articles for depth
- Keep comprehensive but not overwhelming
- Update as tools evolve
- Include pricing changes
- Decision framework = key value
## Internal Linking Strategy
This article should link to:
- Cursor vs Copilot (comparison)
- Install Claude Code (tutorial)
- How to Use Claude Code (tutorial)
- Cursor IDE Setup (tutorial)
- Windsurf Review (review)
## Publication Priority
**MEDIUM PRIORITY — PILLAR PIECE**
Should come AFTER:
1. Cursor vs Copilot (KD 7)
2. Install Claude Code (KD 22)
3. How to Use Claude Code (KD 28)
Then publish this as comprehensive pillar content that links back to those articles. KD 38 is competitive but Josh's hands-on credibility from previous articles creates differentiation.

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---
slug: blog-images-ai
title: "Beautiful Blog Images Without Designers: AI Tools and Workflows"
author: nina
status: inbox
priority: HIGH
created: 2026-01-10
source: seo-research-additional-opportunities
note: "⚠️ Nina's style guide not yet created — hold until style guide complete"
---
# Idea
## Discovery
**Source:** Additional SEO research for Nina — 2026-01-10
**Evidence:**
- "blog images" = 720 monthly searches
- KD: 7 (ULTRA LOW — easiest ranking!)
- Search intent: Informational
- Target audience: Bloggers, content writers, website owners, small business owners
## Why This Matters
Perfect quick win for Nina:
- 720 searches = niche but targeted
- KD 7 = ULTRA LOW competition (easiest!)
- Bloggers = accessible audience
- Practical, high-value content
- Visual storytelling
## Content Angle
**Title:** "Beautiful Blog Images Without Designers: AI Tools and Workflows"
**Nina's Approach:**
- Practical guide for bloggers
- Tool recommendations
- Design principles simplified
- Workflow for blog post images
- "You don't need a designer" empowerment
- Budget-friendly solutions
**Structure:**
1. Opening: "Every blog post needs images. But hiring a designer for each post?"
2. Why blog images matter (quick context)
3. Types of blog images you need:
- Featured/hero images
- In-article illustrations
- Section breaks
- Quote graphics
4. Tool recommendations:
- Canva AI (accessible)
- Leonardo AI (quality/free tier)
- Midjourney (if budget allows)
5. Design principles for blogs:
- Readability
- Brand consistency
- Image sizing/optimization
6. Workflow: Create images while writing
7. Real blog examples (before/after)
8. SEO considerations (alt text, file names)
9. Closing: "Professional blog visuals in minutes"
## Why This Works for Nina
Perfect for her expertise:
- Accessibility focus (non-designers)
- Practical workflows
- Budget-conscious
- Creative + technical balance
- Empowering tone
- Visual storytelling
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| blog images | 720 | 7 | PRIMARY |
| blog post images | — | — | Synonym |
| blog graphics | — | — | Related |
| create blog images | — | — | Intent |
## Secondary Keywords
- "blog images ai"
- "ai blog visuals"
- "blog image generator"
- "blog featured images"
## Image Types Coverage
**Featured Images:**
- Hero/header
- Eye-catching
- Topic-relevant
- SEO-optimized
**In-Article Images:**
- Illustrate concepts
- Break up text
- Visual interest
- Topic support
**Quote Graphics:**
- Highlight key points
- Shareable
- Brand-consistent
**Section Breaks:**
- Visual breathing room
- Topic transitions
## Content Format
**Nina's Style:**
- Step-by-step workflow
- Real blog examples
- Tool comparisons
- Design tips
- Before/after
- Practical templates
## Differentiation
Most blog image content:
- Stock photo guides
- Generic design tips
- Expensive tools
Nina's angle:
- AI-powered creation
- Blogger-friendly
- Budget-conscious
- Workflow integrated
- No design skills needed
- Practical examples
## Strategic Value
**Why This Article Matters:**
- KD 7 = ULTRA LOW (easiest in Nina's set!)
- Bloggers = broad audience
- High practical value
- Quick win opportunity
- Can expand into series
## Notes
- ⚠️ **IMPORTANT:** Nina's style guide not yet created
- Hold until style guide complete
- KD 7 = EASIEST ranking opportunity
- Perfect first article candidate
- Bloggers = accessible, grateful audience
## SEO Considerations
Nina should cover:
- Image sizing for blogs
- File optimization
- Alt text best practices
- File naming
- Featured image specs
- Mobile considerations
## Workflow Integration
Show how to:
- Create images while writing
- Batch create for multiple posts
- Maintain brand consistency
- Organize image library
- Reuse and repurpose
## Related Content Opportunities
Can expand to:
- "Blog Featured Images Guide"
- "Quote Graphics for Blogs"
- "Blog Visual Brand Guide"
- "WordPress Image Optimization"
## Publication Priority
**HIGH — WHEN NINA IS READY**
Perfect first article:
- KD 7 (ULTRA LOW — easiest win!)
- Clear practical value
- Accessible audience
- Quick to rank
- Builds momentum

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---
slug: canva-ai-video-features
title: "Canva's AI Video Features: What's Actually Useful and What's Just Hype"
author: mara-solheim
status: inbox
priority: VERY HIGH
created: 2026-01-10
source: seo-research-josh-mara-warmup
urgency_reason: "Massive volume (49,500) with surprisingly low KD (16) — rare opportunity"
---
# Idea
## Discovery
**Source:** SEO Research for Josh & Mara warmup articles — 2026-01-10
**Evidence:**
- "canva ai video generator" = 49,500 monthly searches (!!)
- KD: 16-25 (LOW for this volume — exceptional)
- Search intent: Informational
- Target audience: Existing Canva users, small business owners, social media managers, non-designers
## Why This Matters
MASSIVE OPPORTUNITY:
- 49,500 searches = highest volume in entire research
- KD 16 = very low competition for this volume
- Most rare high-volume/low-competition keyword found
- Many people already have Canva subscriptions
- They want to know what's possible WITHOUT additional tools
## Content Angle
**Title:** "Canva's AI Video Features: What's Actually Useful and What's Just Hype"
**Mara's Approach:**
- Honest evaluation of Canva's AI video tools
- Help users understand what they can do with existing subscription
- Compare quality to dedicated AI video platforms
- "This actually blew my mind" moments vs "This disappointed me" honesty
- Practical examples from real projects
**Structure:**
1. Opening: "I've been putting off writing about Canva's AI. Everyone's covered it, right? But I needed to test it for actual projects..."
2. What Canva AI video features exist (overview)
3. Feature-by-feature testing with real results
4. Honest comparison: Canva AI vs dedicated tools (Runway, etc.)
5. When Canva AI is enough, when you need something else
6. Closing: "For most creators, this changes everything..."
## Why This Works for Mara
Perfect match for her expertise:
- Accessibility focus (non-technical creators)
- Honest approach builds trust
- Shows the struggle AND success
- UX design background helps explain interface
- Can help people maximize tools they already have
- "I need to share this" genuine enthusiasm
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| canva ai video generator | 49,500 | 16 | PRIMARY |
| canva ai features | 3,600 | — | Include |
| canva text to video | 2,400 | — | Feature |
| canva ai image generator | 8,100 | — | Related |
## Secondary Keywords
- "how to use canva ai"
- "canva video generator tutorial"
- "is canva ai worth it"
- "canva ai vs runway"
## Strategic Positioning
**Key Insight:** People already pay for Canva, they want to know:
1. What AI features they have access to
2. How to use them effectively
3. Whether they need additional tools
4. Real examples of what's possible
Mara can answer all of this from practical experience.
## Content Format
**Mara's Style:**
- Hands-on testing format
- Show her actual Canva projects
- Include screenshots/results
- Honest assessment (good AND bad)
- Practical use cases
- Accessible for broad audience
## Differentiation
Most Canva AI content is:
- Generic feature lists
- Overly promotional
- No honest critique
Mara's angle:
- Real testing on actual projects
- Honest about limitations
- Helps readers decide if Canva AI is enough
- Shows when to use vs when to upgrade
## Notes
- PRIORITY #1 for Mara — exceptional volume/KD ratio
- Should be first or second article published
- Many readers will already be Canva users
- Low barrier to try (most have existing accounts)
- Mara's vulnerability ("I almost gave up...") resonates here
- Can lead to follow-up content comparing to other tools
## Publication Priority
**VERY HIGH** — This should be Mara's first or second published article. The volume/KD ratio is too good to delay.

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---
slug: capcut-ai-video-generator
title: "CapCut AI Video Generator: I Made 10 Videos to Show You What's Actually Possible"
author: mara-solheim
status: inbox
priority: HIGH
created: 2026-01-10
source: seo-research-josh-mara-warmup
---
# Idea
## Discovery
**Source:** SEO Research for Josh & Mara warmup articles — 2026-01-10
**Evidence:**
- "capcut ai video generator" = 14,800 monthly searches
- KD: 11 (LOW — excellent opportunity!)
- Search intent: Informational/Transactional
- Target audience: Content creators, marketers, creators who know CapCut for editing but not AI features
## Why This Matters
EXCEPTIONAL volume/KD ratio:
- 14,800 searches with only KD 11 = rare find
- Many creators already use CapCut for editing
- AI video features are newer, less known
- Perfect entry point for Mara's creative AI focus
## Content Angle
**Title:** "CapCut AI Video Generator: I Made 10 Videos to Show You What's Actually Possible"
**Mara's Approach:**
- Hands-on exploration — create 10 different video types
- Show REAL results (good and bad)
- Be honest about quality, limitations, when it works best
- Include before/after examples
- Genuine excitement balanced with honest frustrations
**Structure:**
1. Opening: "Okay, this one actually surprised me..."
2. What CapCut AI video features actually do
3. 10 video experiments with results
4. What works, what doesn't (honest assessment)
5. Best use cases
6. Closing: "Try it. Seriously. And then come tell me what you made."
## Why This Works for Mara
Perfect fit for her voice and expertise:
- "I tried this so I can tell you if it's worth it" approach
- Creative technologist angle (not just technical)
- Her genuine excitement when something works
- Shows the struggle, not just success
- Accessible for non-technical creators
- Visual results she can showcase
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| capcut ai video generator | 14,800 | 11 | PRIMARY |
| capcut ai | 22,200 | — | Include |
| capcut image to video | 6,600 | — | Feature |
| capcut text to video | 5,400 | — | Feature |
## Secondary Keywords
Related searches to include:
- "capcut ai features"
- "how to use capcut ai"
- "capcut video generator tutorial"
## Content Format
**Best for Mara:**
- Personal experiment format ("I tested X")
- Show her actual outputs/results
- Include screenshots/examples
- Honest reactions to results
- Practical tips from experience
## Notes
- CapCut is widely known for editing, less for AI generation
- Many users already have the app — just need to know about AI features
- Free tier available — low barrier to entry for readers
- Mara can show accessible workflows for non-technical creators
- Video results make great visual content for article
## Timing
Content creators actively searching for this NOW. Good timing for warmup article to establish Mara's voice.

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---
slug: cursor-ai-alternative
title: "Cursor AI Alternatives: Evaluating Options for Production Development"
author: henry
status: inbox
priority: MEDIUM
created: 2026-01-10
source: seo-research-additional-opportunities
---
# Idea
## Discovery
**Source:** Additional SEO research for Henry — 2026-01-10
**Evidence:**
- "cursor ai alternative" = 480 monthly searches
- KD: 12 (LOW — very achievable)
- Search intent: Commercial Investigation
- Target audience: Developers evaluating Cursor, teams comparing tools, devs with specific requirements Cursor doesn't meet
## Why This Matters
Targeted comparison opportunity:
- 480 searches = niche but targeted
- KD 12 = very low competition
- Commercial intent = readers ready to decide
- Henry's experience with multiple tools = credibility
- Can compare from production usage perspective
## Content Angle
**Title:** "Cursor AI Alternatives: Evaluating Options for Production Development"
**Henry's Approach:**
- Comparison from experienced developer perspective
- Focus on production use cases (not features lists)
- Include Claude Code, GitHub Copilot, Windsurf, Codeium
- Architecture and workflow considerations
- Cost-value analysis
- No single "best" — depends on requirements
**Structure:**
1. Opening: "Cursor works for most cases. But there are situations where alternatives make more sense. Here's the breakdown."
2. Why look for Cursor alternatives (legitimate reasons)
3. Evaluation framework (what matters in production)
4. Alternative 1: Claude Code
- When it's better
- Trade-offs
- Real workflow comparison
5. Alternative 2: GitHub Copilot
- Enterprise integration advantages
- When to choose this
6. Alternative 3: Windsurf
- Agentic capabilities
- Use case fit
7. Alternative 4: Codeium
- Cost considerations
- When "good enough" is fine
8. Decision matrix (by use case)
9. Cost comparison (production reality)
10. My approach (what I use when)
11. Closing: "No single best. Match tool to requirements."
## Why This Works for Henry
Perfect for his expertise:
- Multi-tool experience from 12 years
- Production-focused evaluation
- Architecture and cost considerations
- Direct, non-promotional tone
- Practical decision framework
- Systems thinking approach
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| cursor ai alternative | 480 | 12 | PRIMARY |
| cursor alternative | — | — | Synonym |
| alternative to cursor | — | — | Variant |
| cursor vs [alternatives] | — | — | Related |
## Secondary Keywords
- "cursor ai competitors"
- "best cursor alternative"
- "cursor vs claude code"
- "cursor vs copilot"
## Evaluation Framework
**Henry's Perspective:**
1. **Production Requirements:**
- Context handling (large codebases)
- Multi-file operations
- Performance impact
- API reliability
2. **Workflow Integration:**
- Editor compatibility
- Git workflow fit
- CI/CD considerations
- Team collaboration
3. **Cost Structure:**
- API pricing
- Usage patterns
- Team scaling
- Value for money
4. **Architecture Fit:**
- Monorepo support
- Microservices context
- Legacy code handling
- Framework-specific needs
## Tools to Compare
**Based on production experience:**
1. **Claude Code**
- Best for: CLI-native workflows
- Strength: Reasoning capability, MCP integration
- Trade-off: Less GUI-friendly
- When to choose: Terminal-first developers, complex reasoning tasks
2. **GitHub Copilot**
- Best for: Enterprise teams, GitHub-integrated
- Strength: Stability, wide support, team features
- Trade-off: Context limitations
- When to choose: Large teams, GitHub-centric workflow
3. **Windsurf**
- Best for: Experimental agentic workflows
- Strength: Cascade, Flows, multi-step operations
- Trade-off: Newer, less proven
- When to choose: Early adopters, specific Cascade needs
4. **Codeium**
- Best for: Budget-conscious, "good enough" suffices
- Strength: Free tier, decent quality
- Trade-off: Less powerful than paid options
- When to choose: Cost primary concern, solo devs
## Content Format
**Henry's Style:**
- Comparison table (quick reference)
- Production use case examples
- Architecture considerations
- Cost analysis (real numbers)
- No promotional tone
- "In my experience..." insights
- Direct recommendations by use case
## Differentiation
Most comparison content:
- Generic feature lists
- No production depth
- Promotional bias
Henry's angle:
- Production-focused evaluation
- Real workflow implications
- Architecture and cost depth
- Multi-tool experience
- No bias (uses different tools for different cases)
- Systems thinking
## Strategic Value
**Why This Article Matters:**
- KD 12 = very low, easy ranking
- Commercial intent = high-value readers
- Establishes Henry as multi-tool expert
- Natural internal linking to other reviews
- Can update as tools evolve
## Decision Matrix
**By Use Case:**
| Use Case | Recommended | Why |
|----------|-------------|-----|
| Fullstack solo | Cursor | Integrated, powerful |
| Terminal-native | Claude Code | CLI workflow, reasoning |
| Enterprise team | Copilot | Team features, stability |
| Budget-conscious | Codeium | Free tier, adequate |
| Experimental workflows | Windsurf | Agentic capabilities |
## Notes
- KD 12 = very achievable
- 480 searches = niche but targeted
- Commercial intent = readers ready to decide
- Henry's multi-tool experience = credibility
- No single "best" = honest, helpful
- Can reference individual tool deep-dives
- Update as new tools emerge
## Internal Linking
This article should link to:
- How to Use Cursor AI (Henry's tutorial)
- Cursor vs Copilot (Josh's comparison)
- Install Claude Code (Josh's tutorial)
- Other AI tool content
## Production Perspective
Henry should emphasize:
- Real cost implications
- Team collaboration reality
- Large codebase handling
- Performance in production
- Integration with existing tools
- Long-term viability considerations
## Publication Priority
**MEDIUM PRIORITY** — KD 12 (very low), commercial intent, but smaller volume (480). Should come after higher-volume articles but provides valuable comparison for readers evaluating tools.

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---
slug: cursor-ide-setup-guide
title: "Cursor IDE: The AI Code Editor That Actually Gets It Right (Setup + First Impressions)"
author: josh-mercer
status: inbox
priority: MEDIUM
created: 2026-01-10
source: seo-research-josh-mara-warmup
---
# Idea
## Discovery
**Source:** SEO Research for Josh & Mara warmup articles — 2026-01-10
**Evidence:**
- "cursor ide" = 18,100 monthly searches (!!)
- KD: 35 (MEDIUM — competitive but achievable for quality content)
- Search intent: Informational/Navigational
- Target audience: Developers curious about AI-native code editors, VS Code users considering switching, freelancers evaluating productivity tools
## Why This Matters
Highest volume in Josh's keyword set:
- 18,100 searches = massive interest
- KD 35 = competitive but achievable
- Cursor = trending AI code editor
- Many developers exploring but haven't tried yet
- Josh can share real client project experience
## Content Angle
**Title:** "Cursor IDE: The AI Code Editor That Actually Gets It Right (Setup + First Impressions)"
**Josh's Approach:**
- Practical first-time setup guide
- Honest review after real usage
- Cover installation, initial configuration, first week experience
- Focus on what worked and what frustrated him
- From perspective of fullstack developer on real client projects
- "I tried this so you don't have to" vibe
**Structure:**
1. Opening: "I spent last weekend trying Cursor. Everyone's talking about it. Here's what actually happened..."
2. What is Cursor (brief overview)
3. Installation walkthrough (Mac/Linux/Windows)
4. Initial configuration that matters
5. First project: what surprised me
6. What works well (specific examples)
7. What frustrated me (honest critique)
8. VS Code comparison (readers want this)
9. Is it worth switching? (practical answer)
10. Closing: "Your mileage may vary, but here's what I found..."
## Why This Works for Josh
Perfect fit for his voice:
- "I tried X so you don't have to" format
- Practical, no-BS evaluation
- Real project usage (not just demo)
- Startup background = productivity focus
- Honest about frustrations
- Helps readers decide without hype
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| cursor ide | 18,100 | 35 | PRIMARY |
| cursor ide review | 880 | — | Include |
| cursor ide free | 1,300 | — | FAQ |
| cursor ai code editor | 1,000 | — | Synonym |
## Secondary Keywords
- "cursor ide setup"
- "how to install cursor"
- "cursor vs vs code"
- "is cursor ide worth it"
## Key Points to Cover
**Installation:**
- Platform-specific steps
- Common errors Josh encountered
- Dependencies needed
- Initial setup time
**Configuration:**
- Settings that matter from day 1
- API key setup (if applicable)
- Theme/extension migration from VS Code
- Keyboard shortcuts
**First Impressions:**
- What works immediately
- Learning curve reality
- Where it struggled on real code
- Performance vs VS Code
**Honest Assessment:**
- When Cursor shines
- When it's frustrating
- Who should switch
- Who should wait
## Content Format
**Josh's Style:**
- Tutorial + honest review hybrid
- Step-by-step with commentary
- Include screenshots of actual usage
- Real project examples
- No overselling
- "Three rabbit holes later..." honesty
## Differentiation
Most Cursor content:
- Overly promotional
- Or generic feature lists
- No sustained usage
Josh's angle:
- "I used it on client work for a week"
- Shows the gotchas and solutions
- Practical productivity assessment
- Honest about frustrations
- Helps readers make informed decision
## Strategic Value
**Why This Article Matters:**
- Highest volume keyword in Josh's set (18.1k)
- Establishes him as AI coding tool expert
- Cursor is trending NOW — timely
- Can reference in future tool comparisons
- Builds authority through practical experience
## Notes
- KD 35 = competitive but Josh's authentic voice is differentiator
- Cursor is hot right now — good timing
- Many developers curious but haven't tried
- "Is it worth switching from VS Code?" = key question
- Setup guide + review = comprehensive value
- Josh's startup experience = understands productivity tradeoffs
## Related Content Opportunities
This can lead to:
- "Cursor vs GitHub Copilot" (already in plan)
- "Cursor vs Claude Code" comparison
- "Best Cursor extensions"
- Advanced Cursor workflows
## Publication Priority
**MEDIUM PRIORITY** — Highest volume (18.1k) but medium KD (35). Should come after easier wins (Cursor vs Copilot) to build momentum, but before general listicles. Establishes Josh as Cursor expert for future comparison content.

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---
slug: cursor-vs-github-copilot
title: "Cursor vs GitHub Copilot: Which AI Coding Assistant Should You Use in 2025?"
author: josh-mercer
status: inbox
priority: VERY HIGH
created: 2026-01-10
source: seo-research-josh-mara-warmup
urgency_reason: "Lowest KD (7) — easiest win for first article"
---
# Idea
## Discovery
**Source:** SEO Research for Josh & Mara warmup articles — 2026-01-10
**Evidence:**
- "cursor vs github copilot" = 1,000 monthly searches
- KD: 7 (ULTRA LOW — easiest ranking opportunity!)
- Search intent: Commercial Investigation
- Target audience: Developers deciding between AI assistants, teams evaluating tooling, freelancers comparing cost vs value
## Why This Matters
PERFECT first article opportunity:
- 1,000 searches = solid volume
- KD 7 = LOWEST in entire research
- Comparison format = high-value for readers
- Josh can show real usage of both
- Quick ranking win to establish blog
## Content Angle
**Title:** "Cursor vs GitHub Copilot: Which AI Coding Assistant Should You Use in 2025?"
**Josh's Approach:**
- Side-by-side comparison based on actual usage
- Test BOTH on the same real project
- Cover: code completion quality, context understanding, pricing, integration
- Be honest about trade-offs (neither is perfect)
- Help readers choose based on their use case
- "Your mileage may vary" realism
**Structure:**
1. Opening: "I've been using both Cursor and GitHub Copilot on client work. Here's what I found..."
2. Quick overview: what each tool does
3. Testing methodology: same project, both tools
4. Code completion quality (real examples)
5. Context understanding (which gets your code better)
6. Integration and workflow (daily usage reality)
7. Pricing comparison (value for money)
8. When Cursor wins
9. When Copilot wins
10. Who should choose which
11. Closing: "Neither is perfect, but here's my take..."
## Why This Works for Josh
Perfect for his voice:
- Balanced, skeptical approach = his strength
- Real project examples (not synthetic tests)
- "Your mileage may vary" honesty
- Practical decision framework
- No overselling either tool
- Builds credibility through fairness
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| cursor vs github copilot | 1,000 | 7 | PRIMARY |
| cursor vs copilot | 2,900 | — | Synonym |
| github copilot vs cursor | 1,300 | — | Reverse |
| cursor ai vs copilot | 390 | — | Variant |
## Secondary Keywords
- "cursor or github copilot"
- "copilot vs cursor reddit"
- "which is better cursor or copilot"
- "cursor vs copilot 2025"
## Comparison Framework
**Key Dimensions:**
1. **Code Completion Quality**
- Accuracy
- Context awareness
- Multi-file understanding
- Examples from real project
2. **Workflow Integration**
- Editor integration
- Setup complexity
- Daily usage friction
- Speed/performance
3. **Pricing**
- Free tiers
- Paid plans
- Value for freelancers
- Team pricing
4. **Use Cases**
- When Cursor better
- When Copilot better
- Project types
- Team vs solo
5. **Trade-offs**
- What you gain with each
- What you lose
- Deal-breakers for some
## Content Format
**Josh's Style:**
- Comparison table (quick reference)
- Real code examples from testing
- Honest pros/cons for each
- No clear "winner" (depends on needs)
- Help readers self-select
- "Here's what worked for me..." not "you should use X"
## Differentiation
Most comparison content:
- Biased toward one tool
- Generic feature comparison
- No real usage evidence
Josh's angle:
- Tested both on same project
- Real examples from client work
- Fair to both tools
- Acknowledges neither is perfect
- Helps readers choose based on their situation
## Strategic Value
**Why This Article Is PERFECT First Article:**
- KD 7 = easiest ranking opportunity found
- Quick win builds momentum
- Establishes Josh as fair, practical reviewer
- Can rank fast with quality content
- Creates authority for future tool reviews
## Notes
- KD 7 is EXTREMELY low — Josh can rank quickly
- Comparison format = high reader value
- Neither tool is perfect — honesty resonates
- Shows real usage (both tools on client project)
- Freelancer perspective = unique angle vs enterprise reviews
- Can update as both tools evolve
## Win Strategy
**Why start here:**
1. Easiest to rank (KD 7)
2. Establishes credibility (fair comparison)
3. Solid volume (1,000 searches)
4. Natural lead-in to individual tool articles
5. Quick win = blog momentum
## Related Content Chain
This enables future content:
1. Cursor vs Copilot ← START HERE
2. Cursor IDE Setup (individual deep-dive)
3. GitHub Copilot Tutorial (individual deep-dive)
4. Best AI Coding Assistants (broader comparison)
## Publication Priority
**VERY HIGH — FIRST ARTICLE RECOMMENDED**
Rationale:
- Lowest KD (7) in entire research
- Solid volume (1,000 searches)
- Quick ranking win
- Establishes Josh's voice
- Creates momentum for harder keywords

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---
slug: ecommerce-photography-ai
title: "AI-Powered E-commerce Photography: Complete Guide to Professional Product Images"
author: banatie
status: inbox
priority: MEDIUM
created: 2026-01-10
source: seo-research-additional-opportunities
---
# Idea
## Discovery
**Source:** Additional SEO research for Banatie blog — 2026-01-10
**Evidence:**
- "ecommerce photography" = 880 monthly searches
- KD: 32 (MEDIUM — competitive but achievable)
- Search intent: Commercial/Informational
- Target audience: E-commerce business owners, online retailers, digital marketers, product managers
## Why This Matters
Solid commercial opportunity:
- 880 searches = good targeted volume
- KD 32 = competitive but achievable with quality
- E-commerce = high-value audience
- Photography = critical business need
- AI angle = differentiation
- Comprehensive topic
## Content Angle
**Title:** "AI-Powered E-commerce Photography: Complete Guide to Professional Product Images"
**Banatie's Approach:**
- Comprehensive e-commerce photography guide
- Traditional + AI hybrid approach
- Platform-specific requirements
- Conversion optimization focus
- Tool recommendations
- Real store examples
**Structure:**
1. Opening: "E-commerce success starts with product photography..."
2. Why e-commerce photography matters:
- Conversion impact
- Brand perception
- Competitive advantage
3. Essential image types:
- Main product images
- Lifestyle shots
- Detail/zoom images
- Infographics
- 360° views
4. Traditional vs AI-enhanced approach:
- When to use traditional
- When AI excels
- Hybrid workflows
5. AI tools for e-commerce:
- Flair AI
- PhotoRoom
- Pixelcut
- Remove.bg + generative AI
6. Platform requirements:
- Amazon
- Shopify
- Etsy
- WooCommerce
7. Conversion optimization:
- A/B testing images
- Best practices
- Psychology of product images
8. Workflow setup:
- Equipment needs
- AI tool integration
- Quality control
- Batch processing
9. Real case studies
10. Closing: "Professional e-commerce visuals at scale"
## Why This Works for Banatie
Perfect for brand positioning:
- Comprehensive authority piece
- Business-focused
- Practical workflows
- Conversion angle
- Tool comparisons
- Real examples
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| ecommerce photography | 880 | 32 | PRIMARY |
| e-commerce product photography | — | — | Synonym |
| online store photography | — | — | Related |
| product images for ecommerce | — | — | Intent |
## Secondary Keywords
- "ecommerce photography ai"
- "product photography for online store"
- "ecommerce image best practices"
- "amazon product photography"
- "shopify product images"
## Essential Image Types
**Main Product Images:**
- White background
- Multiple angles
- High resolution
- Clean and professional
**Lifestyle Shots:**
- Product in use
- Context and scale
- Emotional connection
- Brand storytelling
**Detail Images:**
- Close-ups
- Material/texture
- Features highlight
- Quality demonstration
**Infographics:**
- Dimensions
- Features list
- Comparisons
- Instructions
**360° Views:**
- Interactive experience
- Complete view
- Premium feel
- Reduced returns
## Content Format
**Banatie's Style:**
- Real e-commerce examples
- Platform comparisons
- Conversion data
- Tool workflows
- Before/after
- Decision frameworks
## Differentiation
Most e-commerce photography content:
- Generic photography tips
- Expensive equipment focus
- No AI integration
- Missing platform specifics
Banatie's angle:
- AI-enhanced workflows
- Platform-specific requirements
- Conversion optimization
- Cost-effective solutions
- Hybrid approach (traditional + AI)
- Real store examples
## Platform-Specific Requirements
**Amazon:**
- Main: White background, 1000px minimum
- Lifestyle: Allowed as additional
- Strict requirements
- Infographics allowed
**Shopify:**
- Flexible formats
- Brand consistency important
- Lifestyle emphasis
- Homepage features
**Etsy:**
- Creative freedom
- Lifestyle essential
- Story-driven
- Authentic feel
**WooCommerce:**
- Similar to Shopify
- Gallery features
- Zoom functionality
- Variation images
## Conversion Optimization
**Best Practices:**
- Multiple angles (5-7 images)
- Lifestyle context
- Detail shots
- Infographics for features
- Consistent style
- Mobile optimization
**Psychology:**
- White background = trust
- Lifestyle = connection
- Details = quality perception
- Multiple images = reduced uncertainty
## Strategic Value
**Why This Article Matters:**
- KD 32 = competitive but achievable
- 880 vol = solid targeted traffic
- E-commerce audience = high value
- Comprehensive authority piece
- Can become pillar content
- Regular updates valuable
## Notes
- KD 32 = more competitive than other Banatie ideas
- Should come after easier wins
- Comprehensive pillar content
- High business value
- Can expand to platform-specific guides
- Update with new tools and trends
## Workflow Integration
**Hybrid Approach:**
1. Traditional photography setup (basic equipment)
2. AI background removal
3. AI background generation
4. Detail enhancement
5. Batch processing
6. Quality control
**Cost Analysis:**
- Traditional only: $500-2000+ per shoot
- AI hybrid: $50-200 + time
- ROI calculation
- Scale benefits
## Real Case Studies
Should include:
- Before/after store transformation
- Conversion rate improvements
- Cost savings analysis
- Different product categories
- Platform-specific examples
## Related Content Opportunities
Can expand to:
- "Amazon Product Photography Guide"
- "Shopify Image Optimization"
- "E-commerce Photography Equipment"
- "Product Image A/B Testing"
## Publication Priority
**MEDIUM — AFTER INITIAL WINS**
Good mid-tier article:
- KD 32 (more competitive)
- Solid volume (880)
- Comprehensive content
- Should follow easier wins
- Can become pillar content

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---
slug: github-copilot-tutorial
title: "GitHub Copilot: Production Workflow Integration and Best Practices"
author: henry
status: inbox
priority: MEDIUM
created: 2026-01-10
source: seo-research-additional-opportunities
---
# Idea
## Discovery
**Source:** Additional SEO research for Henry — 2026-01-10
**Evidence:**
- "github copilot tutorial" = 320 monthly searches
- KD: 14 (LOW — very achievable)
- Search intent: Informational/Tutorial
- Target audience: Developers adopting Copilot, teams evaluating AI tools, experienced devs optimizing workflows
## Why This Matters
Solid tutorial opportunity:
- 320 searches = niche but targeted
- KD 14 = very low competition
- Copilot = widely adopted tool
- Production focus = Henry's differentiation
- Enterprise developers = valuable audience
## Content Angle
**Title:** "GitHub Copilot: Production Workflow Integration and Best Practices"
**Henry's Approach:**
- Technical tutorial from experienced developer perspective
- Focus on production workflows, not toy examples
- Integration with existing development practices
- Performance and cost considerations
- Team collaboration aspects
- "Here's what actually works after 12 years" wisdom
**Structure:**
1. Opening: "Been using Copilot on production projects for a year. Here's what matters past the basic setup."
2. Beyond basic setup:
- Configuration for production
- Context optimization
- Team settings
3. Workflow integration:
- Git workflow compatibility
- Code review process
- CI/CD considerations
4. Best practices from experience:
- Effective prompting in comments
- Context management
- When to accept/reject suggestions
5. Production patterns:
- Architecture-aware usage
- Large codebase handling
- Testing integration
6. Team collaboration:
- Shared settings
- Code consistency
- Knowledge sharing
7. Performance and cost:
- API usage patterns
- Cost management
- Performance impact
8. Advanced techniques:
- Multi-file awareness
- Refactoring patterns
- Documentation generation
9. What works, what doesn't (honest assessment)
10. Closing: "That's the production approach. Match tool to your workflow."
## Why This Works for Henry
Perfect for his expertise:
- Production-focused depth
- 12 years experience perspective
- Team collaboration aspects
- Architecture considerations
- Direct, pragmatic tone
- Real project patterns
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| github copilot tutorial | 320 | 14 | PRIMARY |
| github copilot best practices | — | — | Intent |
| how to use github copilot | — | — | Synonym |
| github copilot tips | — | — | Related |
## Secondary Keywords
- "github copilot for production"
- "github copilot workflow"
- "github copilot team settings"
- "github copilot enterprise"
## Technical Depth Required
**Henry's Style:**
- Production-grade configuration
- Team collaboration setup
- Integration architecture
- Performance considerations
- Cost-value analysis
- Real codebase examples
**Key Technical Sections:**
1. **Configuration:**
- Editor settings
- Keybindings optimization
- Context preferences
- Team-wide settings
2. **Workflow Integration:**
- Git workflow patterns
- Code review with AI suggestions
- Testing practices
- CI/CD compatibility
3. **Production Patterns:**
- Architecture queries
- Large file handling
- Multi-file operations
- Context window optimization
4. **Team Collaboration:**
- Shared conventions
- Code consistency
- Knowledge transfer
- Pair programming with AI
## Content Format
**Henry's Style:**
- Code-heavy (30% code blocks)
- Real configuration examples
- Terminal/editor screenshots
- Architecture considerations
- No hand-holding
- "In my experience..." insights
## Differentiation
Most Copilot tutorials:
- Basic setup only
- Feature showcases
- No production depth
Henry's angle:
- Production workflows from day 1
- Team collaboration aspects
- Architecture integration
- Cost and performance depth
- "After a year in production..." credibility
- Systems thinking perspective
## Strategic Value
**Why This Article Matters:**
- KD 14 = very achievable
- Copilot = widely adopted
- Enterprise audience = valuable
- Production focus = differentiation
- Can rank for related queries
- Establishes AI tool expertise
## Production Considerations
Henry should cover:
- Large codebase context handling
- Team collaboration patterns
- Code quality maintenance
- Cost management at scale
- Performance impact in practice
- CI/CD integration
- Security considerations
## Enterprise Perspective
Henry's depth includes:
- Team settings management
- Organization-wide adoption
- Code consistency across team
- Knowledge sharing patterns
- Integration with enterprise tools
- Compliance and security aspects
## Notes
- KD 14 = very achievable
- 320 searches = niche but targeted
- Production focus = Henry's differentiator
- Enterprise audience = high value
- Can reference in Copilot comparisons
- Update as Copilot evolves
- "Been using this for a year..." credibility
## Related Content Chain
This connects to:
- Cursor vs Copilot comparison (cross-reference)
- AI coding assistant evaluation (broader topic)
- Production AI workflows (series potential)
- Team collaboration with AI (expansion)
## Honest Assessment
Henry should include:
- When Copilot works well
- Where it falls short
- Context limitations in practice
- Cost implications at scale
- Alternative tools comparison
- Real trade-offs experienced
## Publication Priority
**MEDIUM PRIORITY** — KD 14 (low), but smaller volume (320). Should come after higher-priority articles. Provides comprehensive Copilot coverage from production perspective, complements comparison content.

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---
slug: hero-image-website
title: "Hero Images That Convert: Design Guide for Non-Designers"
author: nina
status: inbox
priority: MEDIUM
created: 2026-01-10
source: seo-research-additional-opportunities
note: "⚠️ Nina's style guide not yet created — hold until style guide complete"
---
# Idea
## Discovery
**Source:** Additional SEO research for Nina — 2026-01-10
**Evidence:**
- "hero image website" = 720 monthly searches
- KD: 17 (LOW — very achievable)
- Search intent: Informational/Commercial
- Target audience: Website owners, small business, designers, developers building landing pages
## Why This Matters
Design-focused opportunity:
- 720 searches = niche but targeted
- KD 17 = low competition
- Hero images = critical website element
- Design + conversion focus
- Nina's creative + UX expertise perfect fit
## Content Angle
**Title:** "Hero Images That Convert: Design Guide for Non-Designers"
**Nina's Approach:**
- Design principles simplified
- Conversion-focused (UX background)
- AI tool recommendations
- Real examples (good/bad)
- "You don't need a designer" empowerment
- Psychology of first impressions
**Structure:**
1. Opening: "Your hero image has 3 seconds to make an impression..."
2. Why hero images matter (psychology + conversion)
3. What makes a great hero image:
- Visual impact
- Brand alignment
- Message clarity
- Call-to-action support
4. Design principles simplified:
- Composition basics
- Color psychology
- Typography considerations
- Mobile responsiveness
5. Tool recommendations:
- Midjourney (quality)
- Leonardo AI (balance)
- Canva AI (accessible + text)
6. Workflow: Create hero image:
- Define message
- Visual concept
- AI generation
- Text integration
- Testing
7. Real examples analysis (what works/doesn't)
8. Common mistakes and fixes
9. A/B testing basics
10. Closing: "First impressions that convert"
## Why This Works for Nina
Perfect for her expertise:
- UX design background
- Conversion focus
- Design psychology
- Accessible content
- Visual analysis
- Empowering tone
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| hero image website | 720 | 17 | PRIMARY |
| website hero image | — | — | Synonym |
| hero section image | — | — | Related |
| website header image | — | — | Variant |
## Secondary Keywords
- "hero image design"
- "hero image examples"
- "website hero image best practices"
- "ai hero images"
## Design Principles
**Nina's UX Perspective:**
**Visual Impact:**
- Eye-catching but not overwhelming
- Relevant to message
- Professional quality
**Brand Alignment:**
- Color scheme consistency
- Style matching
- Voice reflection
**Message Clarity:**
- Supports headline
- Clear value proposition
- Not competing with text
**Conversion Support:**
- Directs attention to CTA
- Creates trust
- Encourages action
## Psychology Elements
Nina's approach includes:
- First impression psychology (3-second rule)
- Color impact on emotion
- Visual hierarchy for conversion
- Trust-building through imagery
- Mobile-first considerations
## Content Format
**Nina's Style:**
- Visual examples
- Good vs bad comparisons
- Design principle breakdowns
- Psychology insights
- Tool recommendations
- Step-by-step workflow
## Differentiation
Most hero image content:
- Generic design tips
- Designer-focused
- No conversion angle
Nina's angle:
- Conversion-focused (UX)
- Non-designer accessible
- Psychology insights
- AI tool integration
- Real example analysis
- Practical workflows
## Real Examples
Nina should analyze:
- SaaS landing pages
- E-commerce sites
- Portfolio sites
- Service businesses
- What works and why
- What fails and why
## Strategic Value
**Why This Article Matters:**
- KD 17 = very achievable
- Conversion focus = high value
- UX + creative = Nina's sweet spot
- Practical immediate application
- Can update with trends
## Notes
- ⚠️ **IMPORTANT:** Nina's style guide not yet created
- Hold until style guide complete
- Perfect UX + creative blend
- Conversion focus = Nina's strength
- Real analysis = educational value
## A/B Testing Section
Nina should cover basics:
- What to test (image variants)
- How to measure (conversion metrics)
- Simple tools (Google Optimize, etc.)
- Iteration approach
## Mobile Considerations
Critical for hero images:
- Vertical composition
- Text readability
- File size optimization
- Responsive behavior
## Related Content Opportunities
Can expand to:
- "Landing Page Hero Sections"
- "SaaS Hero Image Guide"
- "E-commerce Homepage Heroes"
- "Hero Section A/B Testing"
## Publication Priority
**MEDIUM — WHEN NINA IS READY**
Good mid-tier article:
- KD 17 (low)
- Design + UX focus
- Conversion angle
- Should come after easier wins
- Can reference in other content

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---
slug: how-to-use-claude-code
title: "How to Use Claude Code: A Practical Tutorial for Your First Real Project"
author: josh-mercer
status: inbox
priority: HIGH
created: 2026-01-10
source: seo-research-josh-mara-warmup
---
# Idea
## Discovery
**Source:** SEO Research for Josh & Mara warmup articles — 2026-01-10
**Evidence:**
- "how to use claude code" = 1,900 monthly searches
- KD: 28 (LOW-MEDIUM — very achievable)
- Search intent: Informational
- Target audience: Developers who installed Claude Code but don't know where to start, terminal-hesitant devs, Cursor users trying Claude Code
## Why This Matters
Natural follow-up to installation guide:
- 1,900 searches = solid volume
- KD 28 = achievable for quality content
- Practical tutorial = high value
- Readers who installed need next step
- Josh can show real workflow
## Content Angle
**Title:** "How to Use Claude Code: A Practical Tutorial for Your First Real Project"
**Josh's Approach:**
- Beginner-friendly tutorial using Claude Code on actual project (not demo)
- Show the workflow from start to finish
- Effective prompting techniques
- Common pitfalls and how to avoid them
- Include code examples and real outputs
- "Here's what I learned" teaching style
**Structure:**
1. Opening: "Just installed Claude Code? Here's what to do next..."
2. Prerequisites (what you should know first)
3. Your first Claude Code session:
- Starting a project
- First command
- What happened
4. Understanding the workflow:
- How to prompt effectively
- Context awareness
- Multi-file changes
5. Real project walkthrough (complete example)
6. Common mistakes (I made them all):
- Vague prompts
- Not checking changes
- Context misses
7. Effective prompting patterns:
- What works
- What doesn't
- Examples with outputs
8. When to use Claude Code vs when not to
9. Troubleshooting common issues
10. Next steps and advanced usage
11. Closing: "You've got the basics. Now go build something..."
## Why This Works for Josh
Perfect for his teaching style:
- Practical tutorial format
- Shows his actual learning curve
- "Here's the mistakes I made" honesty
- Real project (not synthetic demo)
- Helps readers skip trial-and-error
- Accessible for beginners
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| how to use claude code | 1,900 | 28 | PRIMARY |
| claude code tutorial | 1,000 | — | Synonym |
| claude code examples | 590 | — | Include |
| claude code commands | 480 | — | Reference |
## Secondary Keywords
- "claude code beginner guide"
- "claude code workflow"
- "claude code prompting"
- "claude code tips"
## Key Sections Required
**Getting Started:**
- Open Claude Code in your project
- First command to try
- What the interface looks like
- Basic navigation
**Workflow Basics:**
- How to describe what you want
- Reviewing proposed changes
- Accepting/rejecting edits
- Multi-file operations
**Effective Prompting:**
- Specific vs vague prompts
- Including context
- Breaking down complex tasks
- Examples that work
**Common Pitfalls:**
- Not reviewing changes before accepting
- Prompts too vague
- Not understanding context limitations
- Expecting perfection
**Real Project Example:**
- Complete walkthrough
- Start to finish
- Show Claude Code's outputs
- How Josh guided it
- Final result
## Content Format
**Josh's Style:**
- Tutorial format
- Code examples with Claude Code outputs
- Screenshots of actual usage
- "I tried this first, it didn't work..." honesty
- Step-by-step with commentary
- Practical tips from experience
## Differentiation
Most Claude Code tutorials:
- Generic overview
- No real project
- Documentation rehash
Josh's angle:
- "First real project" approach
- Shows learning curve honestly
- Real mistakes and fixes
- Complete workflow example
- Beginner-friendly but practical
## Strategic Value
**Why This Article Matters:**
- Natural follow-up to "Install Claude Code" (8.1k vol)
- 1,900 searches = solid standalone volume
- KD 28 = achievable
- Establishes Josh as Claude Code expert
- Can rank for "claude code tutorial" (1,000 vol)
- Helps readers who installed move to usage
## Content Chain
This is part of Claude Code content cluster:
1. Install Claude Code (8.1k vol, KD 22) ← first
2. **How to Use Claude Code** (1.9k vol, KD 28) ← this article
3. Claude Code vs Cursor (4.4k vol) ← comparison
4. Advanced Claude Code workflows ← future
## Notes
- Should publish shortly after "Install Claude Code"
- Natural progression: install → use → compare → advanced
- Beginner focus but practical (real project)
- Josh's learning curve = teaching advantage
- Show failures alongside successes
- Code examples essential
- Can update as Claude Code evolves
## Real Project Example
Josh should use:
- Simple but real application
- Something readers can follow
- Show complete workflow
- Include Claude Code's actual outputs
- Demonstrate prompting evolution
- Show how he guided it to completion
## Publication Priority
**HIGH PRIORITY** — Natural follow-up to "Install Claude Code." These two articles should be published close together:
1. Install Claude Code (Priority HIGH)
2. How to Use Claude Code (Priority HIGH)
Together they create comprehensive Claude Code onboarding for readers.

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---
slug: how-to-use-cursor-ai
title: "How to Use Cursor AI: Setup and Integration for Production Projects"
author: henry
status: inbox
priority: HIGH
created: 2026-01-10
source: seo-research-additional-opportunities
---
# Idea
## Discovery
**Source:** Additional SEO research for Henry — 2026-01-10
**Evidence:**
- "how to use cursor ai" = 880 monthly searches
- KD: 14 (LOW — very achievable)
- Search intent: Informational/Tutorial
- Target audience: Developers adopting Cursor, teams evaluating AI tools, experienced devs optimizing workflows
## Why This Matters
Strong tutorial opportunity:
- 880 searches = solid volume
- KD 14 = low competition
- Cursor = hot tool RIGHT NOW
- Henry's production experience = differentiation
- Technical depth sets apart from basic tutorials
## Content Angle
**Title:** "How to Use Cursor AI: Setup and Integration for Production Projects"
**Henry's Approach:**
- Technical tutorial from experienced developer perspective
- Focus on production use, not demos
- Cover setup, configuration, real workflows
- Include gotchas from actual client projects
- Performance and architecture considerations
- "Here's what actually works" pragmatism
**Structure:**
1. Opening: "Ran into an interesting Cursor workflow issue yesterday. Realized most tutorials skip the production details. Here's what matters."
2. Initial setup (quick, reference-style)
3. Configuration that matters:
- Settings for production work
- API limits and considerations
- Context window optimization
4. Real workflow integration:
- Fullstack project structure
- Multi-file changes
- Refactoring patterns
5. Advanced usage:
- Custom commands
- Composer vs Chat modes
- When to use each
6. Performance considerations:
- Context size impact
- API rate limits in practice
- Cost management
7. Common issues and solutions:
- Context misses
- Large codebase handling
- Integration with existing tools
8. What works, what doesn't (honest assessment)
9. Code examples from real projects
10. Closing: "That's the production approach. Now go build."
## Why This Works for Henry
Perfect for his expertise and voice:
- Production-focused (not toy examples)
- 12 years experience shows in depth
- Technical architecture considerations
- Performance and cost awareness
- Direct, pragmatic tone
- Real project gotchas
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| how to use cursor ai | 880 | 14 | PRIMARY |
| cursor ai tutorial | — | — | Synonym |
| cursor ai setup | — | — | Include |
| cursor ai best practices | — | — | Intent |
## Secondary Keywords
- "cursor ai for production"
- "cursor ai workflow"
- "cursor ai tips"
- "cursor ai configuration"
## Technical Depth Required
**Henry's Style:**
- Production-grade configuration
- Architecture considerations
- Cost and performance trade-offs
- Integration with existing tooling
- Real codebase examples
- No hand-holding, assumes experienced devs
**Key Technical Sections:**
1. **Configuration:**
- .cursorrules file
- Project-specific settings
- Context optimization
2. **Workflow Integration:**
- Git workflow with Cursor
- CI/CD considerations
- Team collaboration
3. **Performance:**
- Context window management
- API usage patterns
- Cost optimization
4. **Advanced Patterns:**
- Custom commands
- Multi-file refactoring
- Architecture queries
## Content Format
**Henry's Style:**
- Code-heavy (30% code blocks)
- Real configuration files
- Terminal output examples
- Architecture considerations
- No fluff, direct information
- "In my experience..." insights
## Differentiation
Most Cursor tutorials:
- Basic setup only
- Demo projects
- No production considerations
Henry's angle:
- Production-focused from day 1
- Real project examples
- Architecture and performance depth
- Cost considerations
- Team collaboration aspects
- "Back in the Webpack days..." perspective
## Strategic Value
**Why This Article Matters:**
- KD 14 = very achievable
- Cursor is trending NOW
- 880 searches = solid volume
- Technical depth = differentiation
- Experienced dev perspective
- Can rank quickly with quality
## Production Considerations
Henry should cover:
- Large codebase handling
- Context window limitations
- API rate limits in practice
- Cost management strategies
- Team settings and collaboration
- Integration with existing workflows
- CI/CD compatibility
## Notes
- Cursor is hot topic RIGHT NOW — good timing
- KD 14 = low, should rank well
- Production focus = Henry's differentiator
- Experienced dev audience (not beginners)
- Can include GitHub examples
- Update as Cursor evolves
- "Ran into this yesterday..." opening style
## Related Content Chain
This connects to:
- Cursor vs alternatives (comparison)
- Claude Code tutorial (alternative tool)
- AI-assisted development workflows (broader topic)
- Cursor + image generation (Banatie integration)
## Publication Priority
**HIGH PRIORITY** — KD 14 (very low), Cursor is trending, 880 vol. Should be one of Henry's first 3 articles. Production focus differentiates from basic tutorials.

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---
slug: install-claude-code
title: "How to Install Claude Code: Complete Setup Guide for Mac, Linux & Windows"
author: josh-mercer
status: inbox
priority: HIGH
created: 2026-01-10
source: seo-research-josh-mara-warmup
urgency_reason: "High volume (8,100) with achievable KD (22) + trending topic NOW"
---
# Idea
## Discovery
**Source:** SEO Research for Josh & Mara warmup articles — 2026-01-10
**Evidence:**
- "install claude code" = 8,100 monthly searches
- KD: 22 (LOW-MEDIUM — very achievable!)
- Search intent: Transactional/Informational
- Target audience: Developers who heard about Claude Code and want to try it, devs moving from Cursor/Copilot, terminal-native developers
## Why This Matters
Excellent opportunity:
- 8,100 searches = high volume
- KD 22 = very achievable for new blog
- Claude Code is trending NOW
- Clear transactional intent (ready to install)
- Step-by-step guides rank well
## Content Angle
**Title:** "How to Install Claude Code: Complete Setup Guide for Mac, Linux & Windows"
**Josh's Approach:**
- Comprehensive step-by-step installation guide
- Cover ALL platforms (Mac, Linux, Windows)
- Include common errors and troubleshooting
- Show what first session looks like
- Practical examples of initial use
- Document actual installation experience
**Structure:**
1. Opening: "Installed Claude Code yesterday. Here's exactly what I did..."
2. Prerequisites (what you need first)
3. Installation: macOS
- Homebrew method
- Direct download method
- Verification steps
4. Installation: Linux
- apt/dnf/pacman methods
- Common errors on Linux
5. Installation: Windows
- WSL setup (if needed)
- Native Windows install
6. Initial configuration
- API keys (if needed)
- First commands to try
7. Troubleshooting common issues
- Permissions problems
- PATH issues
- Common error messages
8. What to try first (practical examples)
9. Closing: "You're set up. Here's what to do next..."
## Why This Works for Josh
Perfect for his expertise:
- Technical tutorial format
- Multi-platform coverage shows thorough knowledge
- Documenting actual process = his style
- "Here's the gotchas I hit" honesty
- Helps readers avoid his mistakes
- Practical next steps
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| install claude code | 8,100 | 22 | PRIMARY |
| claude code download | 2,900 | — | Include |
| how to use claude code | 1,900 | 28 | Follow-up |
| claude code vs cursor | 4,400 | — | Related |
## Secondary Keywords
- "claude code setup"
- "claude code installation guide"
- "install claude code mac"
- "install claude code linux"
- "install claude code windows"
## Key Sections Required
**Prerequisites:**
- Node.js version requirements
- Terminal basics
- Account needs (if any)
**Platform-Specific:**
- macOS: Homebrew vs manual
- Linux: package manager variations
- Windows: WSL vs native
**Configuration:**
- Config file location
- Initial settings
- API setup (if applicable)
**Troubleshooting:**
- Permission denied errors
- Command not found issues
- PATH configuration
- Common installation failures
**First Steps:**
- Basic commands to try
- Example workflow
- Where to get help
## Content Format
**Josh's Style:**
- Clear step-by-step instructions
- Code blocks with actual commands
- Screenshots of terminal output
- "I ran into this..." asides
- Platform-specific callouts
- Troubleshooting based on real errors
## Differentiation
Most installation guides:
- Generic, copy-paste from docs
- No troubleshooting
- Single platform only
Josh's angle:
- "Here's what actually happened when I installed"
- All platforms covered thoroughly
- Real errors and solutions
- Terminal output examples
- What to do after installation
## Strategic Value
**Why This Article Matters:**
- Second highest volume in Josh's set (8.1k)
- KD 22 = very achievable quick win
- Claude Code trending NOW — capture traffic
- Natural lead-in to "how to use" article
- Establishes Josh as Claude Code expert
## Notes
- Claude Code is trending heavily right now
- Official docs may be sparse — Josh fills gap
- Transactional intent = ready-to-install readers
- Multi-platform coverage = comprehensive value
- Josh's "here's the errors I got" = practical help
- Can update as Claude Code evolves
## Related Content Chain
This starts a content cluster:
1. Install Claude Code ← this article
2. How to Use Claude Code (natural next article)
3. Claude Code vs Cursor (comparison)
4. Best Claude Code workflows (advanced)
## Publication Priority
**HIGH PRIORITY** — Should be Josh's second or third article. High volume (8.1k), achievable KD (22), and Claude Code is trending NOW. Natural pairing with "How to Use Claude Code" article.

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---
slug: leonardo-ai-image-generator
title: "Leonardo AI: The Image Generator I Keep Coming Back To (Complete Guide)"
author: mara-solheim
status: inbox
priority: MEDIUM
created: 2026-01-10
source: seo-research-josh-mara-warmup
---
# Idea
## Discovery
**Source:** SEO Research for Josh & Mara warmup articles — 2026-01-10
**Evidence:**
- "leonardo ai image generator" = 4,400 monthly searches
- KD: 31 (MEDIUM — achievable for quality content)
- Search intent: Informational/Navigational
- Target audience: Creators looking for Midjourney alternatives, designers exploring AI tools, beginners wanting more accessible platform than Stable Diffusion
## Why This Matters
Growing platform with less saturation:
- 4,400 searches = solid volume
- KD 31 = medium but achievable
- Leonardo AI less covered than Midjourney/DALL-E
- Recent image-to-video features = timely angle
- More accessible than Stable Diffusion
- Strong free tier attracts new users
## Content Angle
**Title:** "Leonardo AI: The Image Generator I Keep Coming Back To (Complete Guide)"
**Mara's Approach:**
- In-depth exploration based on sustained usage
- Cover features including new image-to-video
- Share her actual creative process
- Compare free vs paid tiers (help readers decide)
- Show best models for different styles
- Practical workflow tips from experience
**Structure:**
1. Opening: "I've tried most image generators. But Leonardo AI? I keep opening it..."
2. Why Leonardo AI stands out (personal experience)
3. Interface walkthrough (UX designer perspective)
4. Free vs paid: what you actually get
5. Best models for different styles (with examples)
6. New features: image-to-video capabilities
7. Practical workflow: her actual creative process
8. Tips and settings that work (from real usage)
9. Closing: "This is where I go when I need..."
## Why This Works for Mara
Perfect fit for her expertise:
- UX design background helps explain interface
- Sustained usage = genuine credibility
- Creative focus (not just technical specs)
- Can show her actual portfolio work
- "I keep coming back to" = authentic recommendation
- Balance accessibility and power features
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| leonardo ai image generator | 4,400 | 31 | PRIMARY |
| leonardo ai pricing | 1,600 | 10 | Include |
| is leonardo ai free | 480 | 21 | FAQ |
| leonardo ai models | 320 | — | Feature |
| leonardo ai tutorial | — | — | Related |
## Secondary Keywords
- "leonardo ai review"
- "leonardo ai vs midjourney"
- "best leonardo ai models"
- "leonardo ai image to video"
## Key Features to Cover
Based on current Leonardo AI offerings:
1. **Multiple models** — different styles, explain when to use each
2. **Image-to-video** — NEW feature, timely to cover
3. **Free tier** — generous, good for beginners
4. **Paid tiers** — when to upgrade, what you get
5. **Fine-tuned models** — custom training capability
6. **Prompt assistant** — help writing better prompts
7. **Canvas editor** — editing capabilities
## Content Format
**Mara's Style:**
- Complete guide format
- Show her actual generated images
- Include prompt examples that work
- Screenshots of interface/settings
- Personal workflow demonstration
- Honest about learning curve
- Compare to alternatives briefly
## Differentiation
Most Leonardo AI content:
- Generic feature lists
- No sustained usage experience
- Overly promotional or overly critical
Mara's angle:
- "I keep coming back to" = genuine preference
- Real creative projects, not just tests
- UX perspective on interface
- Helps readers navigate the learning curve
- Shows what's possible with practice
## Notes
- Leonardo AI has strong free tier — good for audience
- Less saturated than Midjourney content
- Image-to-video feature is newer — timely angle
- Mara's creative portfolio can showcase Leonardo outputs
- Platform is more accessible than Stable Diffusion
- Growing platform = good timing for comprehensive guide
## Long-Tail Opportunities
Related searches with lower competition:
- "leonardo ai pricing" (1,600 vol, KD 10) — LOW!
- "is leonardo ai free" (480 vol, KD 21)
- Can answer these within main guide
## Publication Timing
**MEDIUM PRIORITY** — solid opportunity after higher-priority CapCut/Canva articles. Leonardo AI guide establishes Mara's expertise in image generation tools.

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---
slug: lorem-picsum-alternative
title: "Beyond Lorem Picsum: AI-Powered Placeholder Images for Production"
author: henry
status: inbox
priority: MEDIUM
created: 2026-01-10
source: seo-research-additional-opportunities
---
# Idea
## Discovery
**Source:** Additional SEO research for Henry — 2026-01-10 (from placeholder images research)
**Evidence:**
- "lorem picsum" = 880 monthly searches
- KD: 15 (LOW — very achievable)
- Search intent: Informational/Navigational
- Target audience: Developers using placeholders, designers prototyping, fullstack developers building MVPs
## Why This Matters
Comparison opportunity:
- 880 searches = solid volume
- KD 15 = very low competition
- Lorem Picsum = well-known placeholder tool
- Natural comparison angle
- Can demonstrate AI advantage
## Content Angle
**Title:** "Beyond Lorem Picsum: AI-Powered Placeholder Images for Production"
**Henry's Approach:**
- Technical comparison with Lorem Picsum
- Show limitations of random placeholders
- Demonstrate AI contextual images advantage
- Production architecture for placeholder-to-production workflow
- Real code examples from projects
- Banatie integration naturally
**Structure:**
1. Opening: "Lorem Picsum works for quick prototypes. But there's a better approach for production workflows."
2. What Lorem Picsum does well:
- Simple API
- Fast placeholders
- Good for basic prototyping
3. Limitations in production:
- Random images (no context)
- Placeholder → production friction
- No customization
- Client demos look generic
4. AI placeholder approach:
- Contextual images from prompts
- Placeholder → production path
- Client-ready from day 1
5. Implementation comparison:
- Lorem Picsum integration (baseline)
- AI placeholder integration (Banatie)
- Code examples for both
6. Architecture: Prototype → Production:
- Live URL pattern
- Caching strategy
- Migration approach
7. Cost comparison:
- Lorem Picsum: free but limited value
- AI placeholders: cost but production-ready
8. When to use each:
- Quick internal prototypes: Lorem Picsum
- Client demos: AI placeholders
- Production MVP: AI placeholders
9. Code repository reference
10. Closing: "Lorem Picsum has its place. But AI placeholders change the workflow."
## Why This Works for Henry
Perfect for his expertise:
- Technical comparison depth
- Architecture and workflow focus
- Production considerations
- Real implementation examples
- Honest trade-off analysis
- Pragmatic recommendation
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| lorem picsum | 880 | 15 | PRIMARY |
| lorem picsum alternative | — | — | Intent |
| placeholder images | 14,800 | 32 | Related (link to) |
| picsum.photos alternative | — | — | Variant |
## Secondary Keywords
- "placeholder image api"
- "better than lorem picsum"
- "lorem picsum vs"
- "placeholder images for production"
## Comparison Framework
**Lorem Picsum Strengths:**
- Simple API
- Fast response
- Free
- Reliable uptime
- Good for basic prototyping
**Lorem Picsum Limitations:**
- Random images (no context)
- Can't customize content
- Client demos look generic
- Placeholder ≠ production
- No prompt-based control
**AI Placeholder Advantages:**
- Contextual images
- Prompt-based customization
- Client-ready quality
- Placeholder → production path
- Better demos
**AI Placeholder Trade-offs:**
- Not free (but valuable)
- Slightly slower generation
- Requires API key
- More complex setup
## Content Format
**Henry's Style:**
- Side-by-side code comparison
- Architecture diagrams
- Real implementation patterns
- Honest trade-off analysis
- Production considerations
- "Here's when to use each" framework
## Technical Implementation
**Lorem Picsum Integration:**
```typescript
// Simple but limited
<img src="https://picsum.photos/600/400" />
```
**AI Placeholder Integration:**
```typescript
// Contextual and production-ready
<img src={generateImage({
prompt: "modern workspace with laptop",
width: 600,
height: 400
})} />
```
**Comparison Points:**
1. Setup complexity
2. API integration
3. Caching strategy
4. Cost implications
5. Placeholder → production path
## Differentiation
Most Lorem Picsum content:
- Generic documentation
- No alternatives discussed
- No production depth
Henry's angle:
- Honest comparison (acknowledges Lorem Picsum value)
- Production workflow focus
- Architecture and cost analysis
- Real implementation examples
- When to use each approach
- Banatie integration (natural, not forced)
## Strategic Value
**Why This Article Matters:**
- KD 15 = very achievable
- 880 searches = solid volume
- Natural Banatie integration
- Comparison format = high value
- Can rank for "lorem picsum alternative"
- Links to main "placeholder images" content (14.8k vol)
## Banatie Integration
Natural opportunities:
- Use as AI placeholder example
- Show live URL advantage
- Demonstrate prompt-based control
- Compare cost vs value
- "I recently built..." disclosure style
- Technical merit focus, not promotion
## Honest Assessment
Henry should acknowledge:
- Lorem Picsum is excellent for quick prototypes
- Not every project needs AI placeholders
- Cost-value trade-off is real
- Best tool depends on use case
- Free ≠ always better
## Notes
- KD 15 = very achievable
- 880 searches = solid volume
- Comparison format = high reader value
- Natural Banatie product integration
- Links to larger "placeholder images" article
- Honest trade-off analysis = credibility
- Update as tools evolve
## Internal Linking
This article should link to:
- Placeholder Images API (main article, 14.8k vol)
- SaaS Landing Page tutorial (uses placeholders)
- Other image generation content
## Production Workflow
Henry should show:
- Prototype phase: Lorem Picsum works
- Client demo: AI placeholders better
- Production: AI images stay
- Migration path: Lorem Picsum → AI
- Cost-value at each stage
## Publication Priority
**MEDIUM PRIORITY** — KD 15 (low), 880 vol. Should come after main "Placeholder Images API" article (14.8k vol). Provides comparison angle and captures "lorem picsum" traffic.

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---
slug: marketing-images-ai
title: "Create Marketing Visuals with AI: A Practical Guide for Non-Designers"
author: nina
status: inbox
priority: VERY HIGH
created: 2026-01-10
source: seo-research-additional-opportunities
urgency_reason: "High volume (2,900) with low KD (19) — excellent opportunity when Nina is ready"
note: "⚠️ Nina's style guide not yet created — hold until style guide complete"
---
# Idea
## Discovery
**Source:** Additional SEO research for Nina — 2026-01-10
**Evidence:**
- "marketing images" = 2,900 monthly searches
- KD: 19 (LOW — very achievable)
- Search intent: Commercial/Informational
- Target audience: Marketers, small business owners, content creators, non-designers needing visuals
## Why This Matters
EXCELLENT opportunity for Nina:
- 2,900 searches = highest volume in Nina's set
- KD 19 = low competition
- Perfect fit for creative technologist role
- Accessibility focus (non-designers)
- Practical workflow content
## Content Angle
**Title:** "Create Marketing Visuals with AI: A Practical Guide for Non-Designers"
**Nina's Approach:**
- Creative workflow for marketers
- Accessible for non-technical audience
- Practical examples from real campaigns
- Tool recommendations
- Design principles made simple
- "You don't need a designer" empowerment
**Structure:**
1. Opening: "You don't need a design degree to create professional marketing visuals..."
2. Why AI changes marketing design (context)
3. Types of marketing visuals you need:
- Social media posts
- Email headers
- Ad creatives
- Blog graphics
4. Tool recommendations:
- Midjourney (quality)
- Canva AI (accessible)
- Leonardo AI (balance)
5. Design principles simplified:
- Color psychology basics
- Composition rules
- Brand consistency
6. Workflow: Concept → Creation → Polish
7. Real examples (before/after)
8. Common mistakes and fixes
9. Closing: "Professional visuals without hiring a designer"
## Why This Works for Nina
Perfect for her expertise:
- Creative technologist angle
- UX design background (simplified for non-designers)
- Accessibility focus
- Practical workflow content
- Engaging, visual
- Inspiring but realistic
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| marketing images | 2,900 | 19 | PRIMARY |
| marketing visuals | — | — | Synonym |
| create marketing images | — | — | Intent |
| marketing graphics | — | — | Related |
## Secondary Keywords
- "marketing images ai"
- "ai marketing visuals"
- "marketing design ai"
- "create marketing graphics"
## Target Audience
**Who Nina Helps:**
- Small business owners
- Solo marketers
- Content creators
- Non-designers needing visuals
- Budget-conscious teams
**Pain Points:**
- Can't afford designer
- Need visuals quickly
- Don't have design skills
- Want professional results
## Content Format
**Nina's Style:**
- Engaging, visual
- Inspiring
- Accessible (no jargon)
- Practical workflows
- Real examples
- Step-by-step guidance
## Differentiation
Most marketing image content:
- Stock photo sites
- Generic design tips
- Expensive tools
Nina's angle:
- AI-powered creation
- Non-designer friendly
- Practical workflows
- Budget-conscious
- Accessible tools
- Empowering tone
## Strategic Value
**Why This Article Matters:**
- Highest volume in Nina's set (2.9k)
- KD 19 = achievable
- Perfect audience match
- Establishes Nina's creative AI focus
- Can expand into series
## Notes
- ⚠️ **IMPORTANT:** Nina's style guide not yet created
- Hold this content until style guide complete
- Perfect first article when Nina is ready
- High volume + low KD = priority
- Creative + practical = Nina's sweet spot
## Visual Content
This article needs:
- Example marketing visuals (AI-generated)
- Before/after comparisons
- Tool screenshots
- Design principle illustrations
- Workflow diagrams
## Related Content Opportunities
This can lead to:
- "Social Media Images with AI"
- "Email Marketing Visuals"
- "Ad Creative with AI"
- "Brand-Consistent AI Visuals"
## Publication Priority
**VERY HIGH — WHEN NINA IS READY**
Should be Nina's first article:
- Highest volume (2.9k)
- Low KD (19)
- Perfect audience fit
- Establishes her voice
- Can reference in future content

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---
slug: product-shots-creative
title: "Creative Product Photography with AI: Beyond Traditional Shots"
author: nina
status: inbox
priority: MEDIUM
created: 2026-01-10
source: seo-research-additional-opportunities
note: "⚠️ Nina's style guide not yet created — hold until style guide complete"
---
# Idea
## Discovery
**Source:** Additional SEO research for Nina — 2026-01-10
**Evidence:**
- "product shots" = 720 monthly searches
- KD: 21 (MEDIUM-LOW — achievable)
- Search intent: Commercial/Informational
- Target audience: Small business owners, Etsy sellers, product creators, e-commerce beginners
## Why This Matters
Creative angle opportunity:
- 720 searches = niche but targeted
- KD 21 = achievable for quality content
- Nina's creative perspective = differentiation
- Product photography = practical need
- Visual, engaging content
## Content Angle
**Title:** "Creative Product Photography with AI: Beyond Traditional Shots"
**Nina's Approach:**
- Creative angle (not technical/API like Henry's version)
- Design-focused workflows
- Inspiration and examples
- Accessible for non-technical creators
- "Make your products stand out" value
- Budget-friendly AI alternatives to photoshoots
**Structure:**
1. Opening: "Product photography doesn't have to be boring white backgrounds..."
2. Why creative product shots matter:
- Stand out in marketplace
- Tell product story
- Connect with audience
3. Creative approaches with AI:
- Lifestyle contexts
- Seasonal themes
- Mood creation
- Brand storytelling
4. Tool recommendations:
- Midjourney (quality)
- Leonardo AI (balance)
- Canva AI (accessible)
5. Workflow: From product to creative shot:
- Product photo/description
- Creative concept
- AI generation
- Refinement
6. Real examples (various products)
7. Design principles:
- Lighting and mood
- Composition
- Brand consistency
8. Platform-specific tips (Etsy, Amazon, Shopify)
9. Common mistakes
10. Closing: "Professional creativity without photoshoots"
## Why This Works for Nina
Perfect for her expertise:
- Creative angle (vs Henry's technical)
- Design principles (UX background)
- Accessible for creators
- Visual storytelling
- Inspiring examples
- Practical workflows
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| product shots | 720 | 21 | PRIMARY |
| product photography | 8,100 | 27 | Related (too broad) |
| creative product photos | — | — | Intent |
| product images creative | — | — | Variant |
## Secondary Keywords
- "product shots ai"
- "creative product photography"
- "product photo ideas"
- "ai product shots"
## Creative Approaches
**Lifestyle Contexts:**
- Products in use
- Real-world settings
- Target audience contexts
- Storytelling scenes
**Seasonal Themes:**
- Holiday contexts
- Seasonal colors
- Event-specific
- Timely relevance
**Mood Creation:**
- Brand personality
- Emotional connection
- Visual tone
- Atmosphere
**Brand Storytelling:**
- Product journey
- Values visualization
- Unique angles
- Differentiation
## Content Format
**Nina's Style:**
- Visual inspiration
- Real examples
- Design principles
- Creative workflows
- Before/after
- Platform considerations
## Differentiation
This is DIFFERENT from Henry's "amazon-product-images-api.md":
**Henry's Angle:**
- Technical API implementation
- Amazon requirements focus
- Backend automation
- Production architecture
- Developer audience
**Nina's Angle:**
- Creative design approach
- Visual storytelling
- Accessible tools
- Creator workflows
- Non-technical audience
BOTH articles can exist — different audiences!
## Design Principles
Nina's UX background helps explain:
- Visual composition
- Lighting principles
- Color psychology
- Brand consistency
- Storytelling through images
## Strategic Value
**Why This Article Matters:**
- KD 21 = achievable
- Creative angle = differentiation
- Product creators = growing audience
- Complements Henry's technical version
- Can inspire and educate
## Notes
- ⚠️ **IMPORTANT:** Nina's style guide not yet created
- Hold until style guide complete
- Different from Henry's API version
- Creative vs technical approaches
- Both can coexist
- Nina's is more accessible
## Platform Specifics
**Etsy:**
- Creative, unique shots
- Lifestyle contexts
- Storytelling
**Amazon:**
- White background alternate views
- Lifestyle supplements
- Brand story
**Shopify:**
- Brand-consistent
- Creative freedom
- Homepage features
## Visual Content
Needs extensive examples:
- Before/after
- Various product types
- Different creative approaches
- Platform variations
- Mood boards
## Related Content Opportunities
Can expand to:
- "Etsy Product Photography"
- "Seasonal Product Shots"
- "Product Storytelling Visuals"
- "Brand-Consistent Product Images"
## Publication Priority
**MEDIUM — WHEN NINA IS READY**
Good mid-tier article:
- KD 21 (medium-low)
- Niche but targeted (720)
- Creative angle
- Should come after easier wins

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---
slug: promotional-images-ai
title: "Design Promo Graphics with AI: A Step-by-Step Guide"
author: nina
status: inbox
priority: MEDIUM
created: 2026-01-10
source: seo-research-additional-opportunities
note: "⚠️ Nina's style guide not yet created — hold until style guide complete"
---
# Idea
## Discovery
**Source:** Additional SEO research for Nina — 2026-01-10
**Evidence:**
- "promotional images" = 880 monthly searches
- KD: 17 (LOW — very achievable)
- Search intent: Commercial/Informational
- Target audience: Small business owners, marketers, event organizers, product launchers
## Why This Matters
Solid opportunity for Nina:
- 880 searches = good targeted volume
- KD 17 = low competition
- Promotional content = common need
- Creative + practical content
- Business audience
## Content Angle
**Title:** "Design Promo Graphics with AI: A Step-by-Step Guide"
**Nina's Approach:**
- Practical guide for promotions
- Cover various promo types (sales, events, launches)
- Tool recommendations
- Design psychology basics
- Call-to-action principles
- "Create eye-catching promos" value
**Structure:**
1. Opening: "Creating promotional graphics that actually convert..."
2. Types of promotional graphics:
- Sale announcements
- Event promotions
- Product launches
- Limited offers
3. Psychology of promotional design:
- Color psychology
- Urgency creation
- Attention-grabbing techniques
4. Tool recommendations:
- Canva AI (templates)
- Midjourney (custom)
- Leonardo AI (balance)
5. Step-by-step workflow:
- Concept
- Design
- Copy integration
- Testing
6. Real examples (before/after)
7. Platform-specific considerations:
- Social media
- Email headers
- Website banners
- Print materials
8. Common mistakes and fixes
9. Closing: "Professional promos in minutes"
## Why This Works for Nina
Perfect for her expertise:
- Creative + commercial focus
- Design psychology (UX background)
- Practical workflows
- Business context
- Visual examples
- Actionable tips
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| promotional images | 880 | 17 | PRIMARY |
| promo graphics | — | — | Synonym |
| promotional visuals | — | — | Related |
| create promo images | — | — | Intent |
## Secondary Keywords
- "promotional images ai"
- "ai promo graphics"
- "sale graphics design"
- "event promotion images"
## Promo Types Coverage
**Sales Promotions:**
- Discount announcements
- Flash sales
- Seasonal sales
- Clearance events
**Event Promotions:**
- Webinars
- Conferences
- Workshops
- Product launches
**Product Launches:**
- New product reveals
- Feature announcements
- Coming soon teasers
**Limited Offers:**
- Time-sensitive deals
- Exclusive offers
- Early bird specials
## Content Format
**Nina's Style:**
- Examples-driven
- Design psychology insights
- Tool comparisons
- Workflow steps
- Before/after
- Platform considerations
## Differentiation
Most promo content:
- Generic templates
- Design-heavy (not accessible)
- No psychology insights
Nina's angle:
- AI-powered creation
- Psychology simplified
- Non-designer friendly
- Multiple promo types
- Platform-specific
- Practical examples
## Design Psychology
Nina's UX background helps explain:
- Color impact on urgency
- Layout for attention
- Copy placement
- CTA effectiveness
- Visual hierarchy
## Strategic Value
**Why This Article Matters:**
- KD 17 = low, achievable
- Business audience = valuable
- Practical immediate value
- Psychology angle = unique
- Conversion-focused
## Notes
- ⚠️ **IMPORTANT:** Nina's style guide not yet created
- Hold until style guide complete
- 880 vol = solid targeted volume
- Business audience = high value
- Psychology angle = Nina's UX strength
## Real Examples
Should include:
- Before: generic promo
- After: AI-optimized promo
- Conversion insights
- Platform variations
- Industry-specific examples
## Related Content Opportunities
Can expand to:
- "Sale Graphics That Convert"
- "Event Promotion Visuals"
- "Product Launch Graphics"
- "Email Promo Headers"
## Publication Priority
**MEDIUM — WHEN NINA IS READY**
Good mid-tier article:
- KD 17 (low but not ultra-low)
- Solid volume (880)
- Business-focused
- Should come after easier wins

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---
slug: runway-ai-video-generator
title: "Runway AI Video Generator: Everything You Need to Know Before You Start"
author: mara-solheim
status: inbox
priority: MEDIUM
created: 2026-01-10
source: seo-research-josh-mara-warmup
---
# Idea
## Discovery
**Source:** SEO Research for Josh & Mara warmup articles — 2026-01-10
**Evidence:**
- "runway ai video generator" = 22,200 monthly searches (!!)
- KD: 34 (MEDIUM — competitive but achievable)
- Search intent: Informational/Navigational
- Target audience: Creators considering premium AI video tools, video editors exploring AI integration, content creators with budget for quality tools
## Why This Matters
High-volume premium tool:
- 22,200 searches = very high volume
- KD 34 = medium difficulty, achievable with quality content
- Runway = premium tier of AI video generation
- People want to know if expensive tool is worth it
- Mara's honest approach perfect for cost evaluation
## Content Angle
**Title:** "Runway AI Video Generator: Everything You Need to Know Before You Start"
**Mara's Approach:**
- Comprehensive Runway guide with honest cost evaluation
- Cover Gen-3 Alpha (latest model)
- Show what different credit amounts can actually produce
- Include practical examples from her own projects
- Be honest about whether cost is worth it
- Help readers decide if they need premium tier
**Structure:**
1. Opening: "Runway is expensive. Everyone knows it. But is it worth it?"
2. What is Runway AI (overview)
3. Gen-3 Alpha: what makes it different
4. Pricing breakdown: what credits actually buy
5. Real examples: what I created and what it cost
6. When Runway is worth it vs when it's not
7. Tips for maximizing credits
8. Alternatives to consider (brief)
9. Closing: "Here's who Runway is actually for..."
## Why This Works for Mara
Perfect for her expertise:
- Honest cost evaluation = her strength
- Premium tool assessment needs credibility
- She can show real project examples
- "Is it worth it?" is exactly her approach
- Helps readers make informed decision
- Balanced view (not promotional, not negative)
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| runway ai video generator | 22,200 | 34 | PRIMARY |
| runway ml pricing | 720 | 9 | Include (LOW KD!) |
| runway gen 3 | 880 | — | Feature |
| runway video ai | 1,300 | — | Synonym |
## Secondary Keywords
- "runway ai review"
- "is runway ai worth it"
- "runway ai cost"
- "runway vs pika"
- "runway ai tutorial"
## Key Points to Cover
**Pricing Reality:**
- Credit system explained clearly
- What you can actually make with X credits
- Monthly costs for different usage levels
- Free tier: what's included
**Gen-3 Alpha:**
- Quality improvements over Gen-2
- Speed and consistency
- When to use Gen-3 vs Gen-2
- Cost difference
**Use Cases:**
- When Runway makes sense
- When alternatives are better value
- Professional vs hobbyist needs
## Content Format
**Mara's Style:**
- Comprehensive guide
- Show her actual Runway projects
- Include cost breakdowns
- Real examples with credit usage
- Honest assessment of value
- Help readers self-select
## Differentiation
Most Runway content:
- Promotional (from Runway)
- Or overly negative (from competitors)
- Doesn't show real cost analysis
Mara's angle:
- "Here's what I actually spent and got"
- Real project examples with costs
- Honest assessment for different budgets
- Helps readers decide if it's for them
- Not trying to sell, trying to inform
## Strategic Value
**Why This Article Matters:**
- Highest volume keyword in Mara's set (22.2k)
- Establishes her as serious reviewer
- Premium tool coverage = authority signal
- Honest cost evaluation builds trust
- Can reference in future comparison articles
## Notes
- Runway is premium/expensive — honesty essential
- Credit system confusing for beginners — simplify
- Gen-3 Alpha is latest — cover thoroughly
- Many readers trying to justify the cost
- Show both success and "this wasn't worth it" examples
- Help readers understand total cost, not just subscription
## Long-Tail Win
**"runway ml pricing" = 720 vol, KD 9** — ULTRA LOW!
- Can rank easily for this
- Include comprehensive pricing section
- Answer "how much does runway really cost"
## Publication Priority
**MEDIUM PRIORITY** — High volume (22.2k) but medium KD (34). Should come after CapCut/Canva (easier wins) but establishes Mara's authority on premium tools.

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---
slug: saas-landing-page
title: "Build a SaaS Landing Page with AI-Generated Images"
author: henry
status: inbox
priority: VERY HIGH
created: 2026-01-10
source: seo-research-additional-opportunities
urgency_reason: "KD 3 — ultra-low competition, quick win opportunity"
---
# Idea
## Discovery
**Source:** Additional SEO research for Henry — 2026-01-10
**Evidence:**
- "saas landing page" = 720 monthly searches
- KD: 3 (ULTRA LOW — easiest win!)
- Search intent: Commercial/Transactional
- Target audience: Developers building SaaS products, indie hackers, startup founders
## Why This Matters
EXCEPTIONAL opportunity:
- 720 searches = solid targeted volume
- KD 3 = ULTRA LOW competition
- Perfect fit for Henry's full-stack expertise
- SaaS landing pages = recurring developer need
- AI images angle = unique differentiation
## Content Angle
**Title:** "Build a SaaS Landing Page with AI-Generated Images"
**Henry's Approach:**
- Full-stack technical tutorial
- Show complete implementation: frontend + API integration
- Real production code (no pseudocode)
- Cover hero images, feature screenshots, use case visuals
- Include Banatie API integration (naturally)
- Next.js 14 App Router + React patterns
- Working code examples from real projects
**Structure:**
1. Opening: "Built a landing page yesterday. Used AI-generated images throughout. Here's the approach that works."
2. Why AI images for landing pages (practical benefits)
3. Architecture overview (what we're building)
4. Setup: Next.js 14 project structure
5. API integration: image generation service
6. Hero section with AI images
7. Feature showcase with contextual visuals
8. Caching strategy (CDN + edge)
9. Error handling and fallbacks
10. Performance optimization
11. Code repo reference
12. Closing: "That's it. Production-ready landing page with AI images."
## Why This Works for Henry
Perfect match for his expertise:
- Full-stack tutorial = his strength
- SaaS context = experienced with
- Architecture + implementation depth
- Real production code
- Performance considerations
- 12 years experience shows in details
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| saas landing page | 720 | 3 | PRIMARY |
| saas landing page design | — | — | Include |
| build saas landing page | — | — | Intent |
| saas website template | — | — | Related |
## Secondary Keywords
- "saas landing page examples"
- "landing page with ai images"
- "nextjs saas landing page"
- "saas hero section"
## Technical Depth Required
**Henry's Style:**
- TypeScript throughout
- Modern Next.js patterns (App Router, Server Components)
- API integration architecture
- Caching layers (CDN, edge, database)
- Error handling patterns
- Performance optimization
- Production considerations
**Architecture:**
```
Landing Page
├── Hero (AI-generated hero image)
├── Features (contextual AI images per feature)
├── Use Cases (scenario-specific visuals)
└── CTA (dynamic image based on user segment)
```
**Key Technical Sections:**
1. Image generation API integration
2. Caching strategy (reduce API calls)
3. Edge optimization (Vercel/Netlify)
4. Fallback handling (if generation fails)
5. SEO considerations (image alt, loading)
## Content Format
**Henry's Style:**
- Code-heavy (30-40% code blocks)
- Real implementation (not pseudocode)
- Architecture diagrams
- No excessive comments in code
- Direct, pragmatic tone
- "Here's what actually works" approach
## Differentiation
Most SaaS landing tutorials:
- Generic templates
- No unique image approach
- No API integration depth
Henry's angle:
- Production-ready architecture
- AI images as differentiator
- Full implementation with caching
- Performance-focused
- Real code from experience
- Banatie integration (subtle product mention)
## Strategic Value
**Why This Article Matters:**
- KD 3 = EASIEST WIN in Henry's set
- Quick ranking opportunity
- Showcases technical depth
- Natural Banatie product integration
- SaaS audience = high-value readers
- Can expand into series (components, optimization, etc.)
## Banatie Integration
Natural opportunities:
- Use Banatie API for image generation examples
- Show live URL feature benefits
- Compare Banatie vs alternatives briefly
- "I recently built..." (Phase 1 disclosure)
- Focus on technical merit, not promotion
## Notes
- KD 3 is EXTREMELY rare — prioritize this
- SaaS developers = target Banatie audience
- Technical tutorial = Henry's comfort zone
- Can include GitHub repo with full code
- Update as Next.js/patterns evolve
- Performance focus = Henry's trademark
## Production Code Example
Henry should show:
- Complete Next.js 14 setup
- API route for image generation
- React components (hero, features)
- Caching implementation
- Error handling
- Edge deployment config
## Related Content Opportunities
This can lead to:
- "Optimize SaaS Landing Page Performance"
- "SaaS Landing Page Components Library"
- "Dynamic Hero Images for SaaS"
- "A/B Testing SaaS Landing Pages"
## Publication Priority
**VERY HIGH — RECOMMENDED FIRST OR SECOND FOR HENRY**
Rationale:
- KD 3 = ultra-low, easy ranking
- Solid volume (720)
- Perfect fit for technical expertise
- Natural Banatie integration
- Quick win to establish Henry's blog

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---
slug: social-media-images-ai
title: "AI-Powered Social Media Content Creation: A Complete Guide"
author: nina
status: inbox
priority: VERY HIGH
created: 2026-01-10
source: seo-research-additional-opportunities
note: "⚠️ Nina's style guide not yet created — hold until style guide complete"
---
# Idea
## Discovery
**Source:** Additional SEO research for Nina — 2026-01-10
**Evidence:**
- "social media images" = 1,900 monthly searches
- KD: 14 (LOW — very achievable!)
- Search intent: Commercial/Informational
- Target audience: Social media managers, content creators, small business owners, influencers
## Why This Matters
Excellent opportunity for Nina:
- 1,900 searches = solid volume
- KD 14 = VERY LOW competition
- Perfect creative technologist content
- Practical workflows
- Visual, engaging topic
## Content Angle
**Title:** "AI-Powered Social Media Content Creation: A Complete Guide"
**Nina's Approach:**
- Practical guide for creators
- Platform-specific tips (Instagram, LinkedIn, Twitter, etc.)
- Tool recommendations
- Workflow optimization
- Design tips for social
- "Create content in minutes" value
**Structure:**
1. Opening: "Creating social media content used to take hours..."
2. Why AI changes social media design
3. Platform-specific requirements:
- Instagram (square, portrait, stories)
- LinkedIn (professional style)
- Twitter/X (attention-grabbing)
- Facebook (varied formats)
4. Tool recommendations by platform
5. Design principles for social:
- Attention-grabbing
- Mobile-first
- Brand consistency
6. Workflow: Batch creation strategy
7. Real examples by platform
8. Content calendar integration
9. Common mistakes
10. Closing: "Professional content at scale"
## Why This Works for Nina
Perfect for her expertise:
- Creative workflows
- Multi-platform knowledge
- Practical tips
- Accessible content
- Visual storytelling
- Engaging style
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| social media images | 1,900 | 14 | PRIMARY |
| social media visuals | — | — | Synonym |
| social media graphics | — | — | Related |
| create social media images | — | — | Intent |
## Secondary Keywords
- "social media images ai"
- "ai social media content"
- "social media design ai"
- "create social posts"
## Platform Coverage
**Instagram:**
- Feed posts (1:1)
- Stories (9:16)
- Reels thumbnails
- Carousel posts
**LinkedIn:**
- Professional tone
- Industry-specific content
- Personal branding
- Company updates
**Twitter/X:**
- Attention-grabbing
- Quote graphics
- Thread visuals
**Facebook:**
- Various formats
- Community focus
- Event graphics
## Content Format
**Nina's Style:**
- Platform-specific examples
- Visual comparisons
- Tool recommendations
- Workflow diagrams
- Real creator examples
- Step-by-step guides
## Differentiation
Most social media content:
- Generic design tips
- Expensive tools
- Designer-focused
Nina's angle:
- AI-powered creation
- Multi-platform specific
- Creator-friendly
- Batch workflow
- Accessible tools
- Practical examples
## Strategic Value
**Why This Article Matters:**
- KD 14 = VERY LOW (easiest in Nina's set!)
- 1,900 searches = solid volume
- Perfect Nina audience
- Platform-specific = high value
- Can expand per platform
## Notes
- ⚠️ **IMPORTANT:** Nina's style guide not yet created
- Hold until style guide complete
- KD 14 = easiest win in Nina's set
- Should be first or second article
- Platform-specific = comprehensive value
## Visual Content
Needs extensive visuals:
- Platform examples
- Before/after
- Tool screenshots
- Design templates
- Workflow diagrams
## Related Content Opportunities
Can expand to:
- "Instagram Content with AI"
- "LinkedIn Visuals Guide"
- "Social Media Templates"
- "Content Calendar with AI"
## Publication Priority
**VERY HIGH — WHEN NINA IS READY**
KD 14 (lowest) makes this ideal first or second article:
- Easiest to rank
- Solid volume (1.9k)
- Perfect audience
- Platform-specific value
- Quick win

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---
slug: windsurf-ide-review
title: "Windsurf IDE Review: A Fullstack Developer's Honest Take After One Month"
author: josh-mercer
status: inbox
priority: MEDIUM
created: 2026-01-10
source: seo-research-josh-mara-warmup
---
# Idea
## Discovery
**Source:** SEO Research for Josh & Mara warmup articles — 2026-01-10
**Evidence:**
- "windsurf ide" = 3,600 monthly searches
- KD: 34 (MEDIUM — competitive but achievable)
- Search intent: Informational/Navigational
- Target audience: Developers exploring AI IDE alternatives, Cursor users curious about competition, devs interested in "agentic" coding
## Why This Matters
Emerging AI IDE opportunity:
- 3,600 searches = solid volume
- KD 34 = medium but achievable
- Windsurf = newer, less covered than Cursor
- "Agentic" coding = trending concept
- Less content saturation = easier to rank
## Content Angle
**Title:** "Windsurf IDE Review: A Fullstack Developer's Honest Take After One Month"
**Josh's Approach:**
- In-depth review after sustained usage (one month)
- Cover unique features: Cascade, Flows, agentic capabilities
- Compare to Cursor (readers want this)
- Discuss pricing model honestly
- Focus on real workflow improvements or frustrations
- "Here's what I wish someone told me" format
**Structure:**
1. Opening: "I've been using Windsurf for a month. Everyone's talking about it. Here's the real story..."
2. What is Windsurf (brief context)
3. Why I tried it (Cursor comparison begins)
4. Setup and first impressions
5. Key features deep dive:
- Cascade (multi-file changes)
- Flows (AI workflows)
- Agentic coding capabilities
6. What works well (specific examples)
7. What frustrated me (honest critique)
8. Cursor comparison (practical)
9. Pricing: is it worth it?
10. Who should try Windsurf
11. Closing: "Your mileage may vary, but here's my take..."
## Why This Works for Josh
Perfect for his voice and expertise:
- Sustained usage = credibility (not quick test)
- Startup experience = evaluates productivity claims
- "I wish someone told me..." = his format
- Practical workflow assessment
- Honest about hype vs reality
- Freelancer perspective = cost-conscious
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| windsurf ide | 3,600 | 34 | PRIMARY |
| windsurf ide review | 480 | — | Include |
| windsurf ai | 2,400 | — | Synonym |
| windsurf vs cursor | 1,600 | — | Comparison |
## Secondary Keywords
- "windsurf ide features"
- "is windsurf ide good"
- "windsurf cascade"
- "windsurf flows"
- "windsurf pricing"
## Key Features to Cover
**Cascade:**
- Multi-file editing capability
- How it actually works in practice
- When it's useful vs overhyped
**Flows:**
- Workflow automation
- Real use cases
- Learning curve
**Agentic Coding:**
- What "agentic" actually means
- Practical implications
- Hype vs reality
**Comparison Points:**
- vs Cursor (readers want this)
- Unique strengths
- Where it falls short
- Pricing comparison
## Content Format
**Josh's Style:**
- Comprehensive review
- Real project examples
- Screenshots of actual usage
- Honest pros and cons
- "After one month..." credibility
- Practical recommendations
## Differentiation
Most Windsurf content:
- Marketing hype
- Or superficial first looks
- No sustained usage
Josh's angle:
- "I used it for a month on real projects"
- Evaluates agentic claims practically
- Startup background = BS detector
- Cost-value assessment
- Helps readers decide if it's for them
## Strategic Value
**Why This Article Matters:**
- Windsurf is newer = less content competition
- "Agentic" coding = trending topic
- Can establish Josh as early expert
- Comparison with Cursor = cross-reference opportunity
- Solid volume (3.6k) for emerging tool
## Notes
- Windsurf is newer than Cursor = less saturation
- "Agentic" coding is buzzword — need practical explanation
- Cascade and Flows are unique features — cover thoroughly
- Pricing model may differ from Cursor — compare honestly
- Josh's "does this actually solve problems" lens = key
- One month usage = substantial credibility
## Related Content Chain
This connects to:
1. Cursor vs Copilot (comparison piece)
2. Cursor IDE Setup (alternative)
3. Windsurf vs Cursor (dedicated comparison)
4. Best AI IDEs (broader piece)
## Publication Priority
**MEDIUM PRIORITY** — Good volume (3.6k) and medium KD (34). Should come after easier wins but helps establish Josh as comprehensive AI IDE expert. Windsurf is trending — good timing for in-depth review.

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---
slug: midjourney-alternatives-bn-blog
title: "Best Midjourney Alternatives in 2026"
author: banatie
status: planning
created: 2026-01-12
updated: 2026-01-12
content_type: comparison
channel: banatie.app/blog
primary_keyword: "midjourney alternative"
primary_volume: 1300
primary_kd: 3
secondary_keywords:
- "midjourney alternatives"
- "midjourney api"
- "leonardo ai"
- "stable diffusion"
- "flux ai"
- "chatgpt image generator"
estimated_traffic: 700-1200
---
# Midjourney Alternatives — Comparison Guide
## Summary
Comprehensive comparison of AI image generation tools as Midjourney alternatives. Covers UI-first services, open source options, API-first platforms, and aggregators.
**Strategic value:** Ultra-low KD (3), solid volume (1,300), quick win for domain authority.
**Banatie positioning:** API-First Platforms section — developer workflow native with MCP integration.
---
## Assets
- `assets/midjourney-alternatives-bn-blog/brief.md` — full brief with structure and requirements
---
## Log
### 2026-01-12 — @strategist
Created brief. Consolidated from three inbox ideas. Keyword research completed via DataForSEO ($0.35 spent).
Categories defined:
1. Models with Native Service (UI-First)
2. Open Source / Self-Hosted
3. API-First Platforms ← Banatie here
4. Aggregators (Multi-Model)
Next: @architect creates outline.

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---
slug: midjourney-alternative
title: "Best Midjourney Alternatives for AI Image Generation in 2026"
author: banatie
status: inbox
priority: URGENT
created: 2026-01-10
source: seo-research-additional-opportunities
urgency_reason: "Declining search volume trend — need to capture traffic NOW"
---
# Idea
## Discovery
**Source:** Additional SEO research for Banatie blog — 2026-01-10
**Evidence:**
- "midjourney alternative" = 1,300 monthly searches
- KD: 3 (ULTRA LOW — easiest ranking!)
- Search intent: Commercial/Informational
- **⚠️ URGENT:** Search volume declining (was 1,600) — capture traffic NOW
- Target audience: AI creators, developers, designers looking for accessible alternatives
## Why This Matters
Perfect strategic opportunity:
- 1.3k searches = solid niche volume
- KD 3 = ULTRA LOW competition
- **Declining volume = URGENCY** — publish NOW to capture remaining traffic
- Alternatives = comparison content (high engagement)
- Banatie = perfect authority for this topic
- Can update as market evolves
## Content Angle
**Title:** "Best Midjourney Alternatives for AI Image Generation in 2026"
**Banatie's Approach:**
- Comprehensive comparison
- Practical testing of each alternative
- Use cases for each tool
- Pricing transparency
- "No Midjourney subscription needed" angle
- Real examples from each tool
**Structure:**
1. Opening: "Midjourney is powerful but expensive. Here are alternatives..."
2. Quick comparison table (all tools at a glance)
3. Detailed reviews:
- Leonardo AI
- Stable Diffusion (via DreamStudio)
- DALL-E 3 (via ChatGPT Plus)
- Ideogram
- Playground AI
4. Use case recommendations
5. Pricing comparison
6. Which to choose when
7. Closing: "You don't need Midjourney"
## Why This Works for Banatie
Perfect for brand positioning:
- KD 3 = easiest quick win
- Comparison content = high value
- Shows authority
- Helps users make decisions
- Practical testing approach
- Can become pillar content
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| midjourney alternative | 1,300 | 3 | PRIMARY |
| alternatives to midjourney | — | — | Synonym |
| midjourney alternatives free | — | — | Intent |
| midjourney competitor | — | — | Related |
## Secondary Keywords
- "free midjourney alternative"
- "midjourney vs leonardo ai"
- "best ai image generator"
- "midjourney replacement"
## Alternatives to Cover
**Leonardo AI:**
- Free tier available
- Commercial use allowed
- Quality comparable
- User-friendly interface
**Stable Diffusion:**
- Open source
- Via DreamStudio
- Complete control
- Steeper learning curve
**DALL-E 3:**
- Via ChatGPT Plus
- Natural language
- High quality
- Limited control
**Ideogram:**
- Great for text-in-images
- Free tier
- Growing fast
- Simple interface
**Playground AI:**
- Free tier generous
- Good for beginners
- Multiple models
- Community features
## Content Format
**Banatie's Style:**
- Real examples from each tool
- Pricing transparency
- Use case scenarios
- Side-by-side comparisons
- Honest pros/cons
- Decision framework
## Differentiation
Most alternative content:
- Listicle with no depth
- No real testing
- Outdated information
Banatie's angle:
- Real testing and examples
- Updated for 2026
- Practical use cases
- Decision framework
- Pricing transparency
- Use case matching
## Strategic Value
**Why This Article Matters:**
- KD 3 = ULTRA LOW (easiest win!)
- **URGENT:** Declining volume — capture NOW
- Quick win for Banatie brand
- Pillar content opportunity
- Can update quarterly
- High engagement potential
## Notes
- ⚠️ **URGENT:** Volume declining from 1,600 to 1,300
- **ACTION:** Publish immediately to capture traffic
- KD 3 = easiest in entire research
- Perfect first article for Banatie blog
- Can expand with individual deep-dives later
- Update quarterly as tools evolve
## Use Case Matching
Help readers choose:
- **For professionals:** Leonardo AI
- **For tinkerers:** Stable Diffusion
- **For beginners:** DALL-E 3 / Playground AI
- **For text-in-images:** Ideogram
- **For free usage:** Leonardo AI / Playground AI
## Related Content Opportunities
Can expand to:
- "Leonardo AI Complete Guide"
- "Stable Diffusion for Beginners"
- "Free AI Image Generators Compared"
- "Midjourney vs Leonardo AI Deep Dive"
## Publication Priority
**URGENT — PUBLISH IMMEDIATELY**
Perfect first article:
- KD 3 (ULTRA LOW — easiest!)
- **Declining volume = NOW OR NEVER**
- High value comparison
- Quick to rank
- Establishes Banatie authority

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---
slug: midjourney-prompts-guide
title: "Midjourney Prompts: What I Learned After 1000+ Generations (With Examples)"
author: mara-solheim
status: inbox
priority: MEDIUM
created: 2026-01-10
source: seo-research-josh-mara-warmup
---
# Idea
## Discovery
**Source:** SEO Research for Josh & Mara warmup articles — 2026-01-10
**Evidence:**
- "midjourney prompts" = 1,900 monthly searches
- KD: 35 (MEDIUM — competitive but achievable)
- Search intent: Informational
- Target audience: Midjourney users wanting better results, creators frustrated with inconsistent outputs, designers integrating AI into workflow
## Why This Matters
Expertise showcase opportunity:
- 1,900 searches = solid volume
- KD 35 = medium, requires quality/expertise
- Prompt engineering = Mara's core skill
- Can show extensive real experience
- Establishes deep expertise, not just surface knowledge
## Content Angle
**Title:** "Midjourney Prompts: What I Learned After 1000+ Generations (With Examples)"
**Mara's Approach:**
- Deep dive into prompt engineering based on extensive experimentation
- Show her actual prompt evolution
- Include before/after refinements
- Real Midjourney outputs illustrating each principle
- "I learned this the hard way" honesty
- Cover v6-specific techniques
**Structure:**
1. Opening: "I've generated over 1000 images in Midjourney. Most of them were terrible. Here's what finally clicked..."
2. How I started (terrible prompts, random results)
3. The breakthrough: structure matters more than creativity
4. Prompt anatomy: what actually works
- Structure patterns
- Style keywords that work
- Negative prompts (critical)
- Parameters (v6-specific)
5. Before/after examples (my prompt evolution)
6. Common mistakes (I made them all)
7. Advanced techniques (after you master basics)
8. Closing: "Prompting is a skill. These are the patterns that work..."
## Why This Works for Mara
Perfect expertise demonstration:
- "1000+ generations" = genuine experience
- UX background helps explain systematic approach
- She can show her actual learning journey
- Mistakes → breakthroughs = her vulnerability style
- "I learned the hard way" resonates with readers
- Real outputs prove expertise
## Keywords Cluster
| Keyword | Vol | KD | Priority |
|---------|-----|----|----------|
| midjourney prompts | 1,900 | 35 | PRIMARY |
| best midjourney prompts | 390 | — | Include |
| midjourney prompt examples | 480 | — | Include |
| midjourney v6 prompts | 320 | — | Version-specific |
## Secondary Keywords
- "midjourney prompt structure"
- "how to write midjourney prompts"
- "midjourney prompt guide"
- "midjourney negative prompts"
## Key Sections to Include
**Prompt Structure:**
- Start with style, not subject (her learning)
- Layering technique
- Word order importance
- Length sweet spot
**Style Keywords:**
- Photography styles
- Art movements
- Lighting terms
- Camera/lens specifications
**Negative Prompts:**
- Why they're critical
- Common negative prompts
- How to use effectively
**v6 Specifics:**
- What changed from v5
- New capabilities
- Adjusted techniques
**Parameters:**
- --ar (aspect ratio)
- --chaos (controlled randomness)
- --stylize (artistic interpretation)
- When to use each
## Content Format
**Mara's Style:**
- Deep expertise demonstration
- Show her actual prompt evolution
- Before/after image pairs
- Real Midjourney outputs
- Include the prompts that generated them
- Honest about trial and error
## Differentiation
Most Midjourney prompt guides:
- Generic tips without depth
- No real usage evidence
- Copy-paste from documentation
Mara's angle:
- "1000+ generations" = real experience
- Shows her actual learning journey
- Before/after demonstrates improvement
- Vulnerability about mistakes
- Patterns learned through experimentation
## Strategic Value
**Why This Article Matters:**
- Establishes deep expertise (not just surface knowledge)
- Pillar content for Mara's creative AI authority
- Can reference in other image generation articles
- Demonstrates sustained practice
- Builds trust through genuine experience
## Visual Content
This article is PERFECT for visuals:
- Before/after prompt refinements
- Side-by-side quality comparisons
- Show the exact prompts with outputs
- Demonstrate structure impact
- Great for social media snippets
## Notes
- Midjourney v6 is latest — cover thoroughly
- Prompt engineering is genuinely hard — don't oversimplify
- Show failures alongside successes
- Real prompts + real outputs = credibility
- Help readers skip the trial-and-error phase
- Mara's "took me three tries" honesty is key
## Long-Tail Opportunities
- "midjourney v6 prompts" (320 vol) — version-specific
- "midjourney prompt examples" (480 vol) — include many
- "best midjourney prompts" (390 vol) — subjective but valuable
## Publication Priority
**MEDIUM PRIORITY** — This is a pillar piece that establishes Mara's deep expertise. Should come after easier wins (CapCut/Canva) but before or alongside premium tool reviews. Demonstrates she's not just trying tools — she masters them.

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# Brief: Best Midjourney Alternatives in 2026
## Strategic Context
**Why this topic:** Low difficulty keyword (KD 3) with steady volume. Captures users actively comparing tools.
**Why now:** Volume has declined from peak (8,100 in Dec 2024 → 480 in Nov 2025), but stabilized. Less competition, easier to rank.
**Banatie angle:** Positioned in API-First Platforms category as developer-native solution with MCP integration.
---
## Target Reader
**Who:** Developer or creator evaluating AI image generation options
**Their problem:** Midjourney is powerful but Discord-only, no API, expensive. Need alternatives that fit their workflow.
**Search intent:** Commercial/Informational — comparing options before choosing
---
## Keyword Strategy
### Primary Keyword
| Keyword | Volume (Nov 2025) | KD | Trend |
|---------|-------------------|-----|-------|
| midjourney alternative | 480 | 3 | Declining from 8,100 (Dec 2024) |
### Secondary Keywords (capture via comprehensive content)
| Keyword | Volume | Strategy |
|---------|--------|----------|
| stable diffusion alternatives | 140 | Cover SD thoroughly, mention as alternative |
| flux alternatives | 170 | Include Flux section |
| dall-e alternatives | 170 | Cover DALL-E/ChatGPT section |
| leonardo ai alternatives | 170 | Cover Leonardo section |
| adobe firefly alternatives | 70 | Cover Firefly section |
### Brand Keywords (H2/H3 section headers)
| Keyword | Volume | Use in |
|---------|--------|--------|
| leonardo ai | 165,000 | Section header |
| adobe firefly | 110,000 | Section header |
| stable diffusion | 90,500 | Section header |
| chatgpt image generator | 40,500 | Section header |
| dall-e 3 | 33,100 | Within ChatGPT section |
| ideogram ai | 22,200 | Section header |
| flux ai | 18,100 | Section header |
| gemini image generator | 14,800 | Section header |
| recraft ai | 6,600 | Section header |
| runway ml | 40,500 | Section header |
### Developer Keywords (API-First section)
| Keyword | Volume | Context |
|---------|--------|---------|
| midjourney api | 1,600 | "Midjourney lacks official API. These platforms fill the gap..." |
---
## SERP Strategy (validated Jan 2026)
### Key Finding
Comprehensive listicles rank for MULTIPLE "X alternatives" queries. Example: Zapier's "8 best AI image generators" ranks for both "midjourney alternative" (pos. 10) AND "best ai image generators" (pos. 4).
### Our Approach
1. **Title:** Keep "Midjourney Alternatives" — KD 3 guarantees ranking. General "best AI image generators" has KD 65 (CNET, PCMag dominate)
2. **Content breadth:** Cover ALL major tools to capture cross-query traffic
3. **H2 optimization:** Use comparison phrases that match People Also Ask
### People Also Ask (from SERP research)
Include in FAQ section:
- "Is there an AI better than Midjourney?"
- "What is similar to Midjourney but free?"
- "Which AI image generator has no restrictions?"
- "Is Midjourney better than Stable Diffusion?"
### Related Searches to Address
- "Midjourney alternative free"
- "Best Midjourney alternative"
- "Midjourney alternatives 2026"
### Realistic Traffic Estimate
- Primary keyword: 50-100/mo (10-20% CTR from 480 searches)
- Cross-query capture: 30-80/mo from secondary keywords
- Brand keyword snippets: 20-50/mo
- **Total: 100-230 monthly visits**
---
## Content Structure
### Intro (1 short paragraph)
Midjourney pioneered AI image generation. But 2026 market offers dozens of alternatives for different needs: API access, UI simplicity, editing capabilities, self-hosting, multi-model access. This guide covers them all.
### Feature Tags (лейтмотив)
Each service shows badges:
- `API` — programmatic access
- `UI` — web interface
- `Self-hosted` — local deployment
- `Editing` — inpaint/outpaint/refine
- `Thinking` — reasoning during generation
- `Aggregator` — multiple models
---
### Section 1: Models with Native Service (UI-First)
For each:
- Screenshot of homepage
- 2-3 sentence description
- Pricing table
- Feature badges (API, UI, Self-hosted, Editing, Thinking)
- "Best for" line
**Include:**
1. Midjourney (baseline reference)
2. Leonardo AI
3. Adobe Firefly
4. ChatGPT Image Generator (GPT-4o / DALL-E 3)
5. Ideogram AI
6. Gemini Image Generator (Imagen)
7. Recraft AI
8. Runway (video + image)
---
### Section 2: Open Source / Self-Hosted
**Include:**
1. Stable Diffusion (SD 1.5, SDXL)
2. Flux (Black Forest Labs)
Same format: screenshot, description, how to run, badges, best for.
---
### Section 3: API-First Platforms (Generation as a Service)
Intro: "Midjourney has no official API. These platforms provide programmatic image generation for developers."
**Include:**
1. Replicate
2. fal.ai
3. Runware
4. Segmind
5. Novita AI
6. **Banatie** — positioned as developer workflow native (MCP, CDN, Prompt URLs)
**Banatie differentiation table:**
| Feature | Replicate | fal.ai | Runware | Banatie |
|---------|-----------|--------|---------|---------|
| API | ✓ | ✓ | ✓ | ✓ |
| MCP Integration | ✗ | ✗ | ✗ | ✓ |
| Built-in CDN | ✗ | ✗ | ✗ | ✓ |
| Prompt URLs | ✗ | ✗ | ✗ | ✓ |
| Focus | Models | Speed | Cost | Workflow |
---
### Section 4: Aggregators (Multi-Model Platforms)
**Include:**
1. Krea.ai
2. Freepik AI
3. Together AI
Same format. Emphasize: one UI, multiple models.
---
### Section 5: FAQ (SEO-optimized)
Answer People Also Ask questions:
1. Is there an AI better than Midjourney?
2. What is similar to Midjourney but free?
3. Which AI image generator has no restrictions?
4. Is Midjourney better than Stable Diffusion?
5. Does Midjourney have an API?
---
### Closing
Short paragraph. No "best" — depends on needs. Link to Banatie for developer workflow.
---
## Requirements
**Format:** Blog post on banatie.app/blog/
**Length:** 2,500-3,500 words (comprehensive but scannable)
**Tone:** Technical, direct, no fluff. Per banatie-brand.md guidelines.
**Visual:**
- Screenshot for each service (homepage or generation UI)
- Feature badges/tags for quick scanning
- Comparison tables where relevant
- Minimal prose, maximum structure
**Must include:**
- All services listed above with consistent format
- Pricing for each (at least free/paid tiers)
- Feature badges for each
- "Best for" recommendation for each
- Banatie in API-First section with differentiation table
- FAQ section with PAA questions
**Must NOT include:**
- Long introductions
- "In today's digital landscape..." type filler
- Excessive explanations of what AI image generation is
- Overselling Banatie (honest positioning only)
---
## Success Criteria
- Ranks for "midjourney alternative" within 2 months
- Appears in SERP for 2+ secondary keywords (stable diffusion alternatives, flux alternatives)
- Captures 100-200 monthly visits
- Drives awareness of Banatie as developer-focused option
---
## Assets Needed
- Screenshots of all services (homepage or key UI)
- Banatie comparison table graphic (optional)
- Feature badge icons (optional, can use emoji)
---
## Research Log
**Jan 2026 — SERP & Keyword Validation:**
- Primary keyword volume: 480/mo (down from 8,100 Dec 2024)
- Confirmed KD 3 — easy to rank
- SERP dominated by AI Overview listing all major tools
- Zapier listicle proves cross-query ranking possible
- Added secondary keywords totaling ~720/mo combined
- Added FAQ section based on People Also Ask
---
## Notes
- Update quarterly as tools evolve
- Can spin off individual deep-dives later (Leonardo AI guide, Flux guide, etc.)
- This becomes pillar content for alternatives section

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# SEO Research Report: Article Ideas for Josh Mercer & Mara Solheim
**Date:** 2026-01-10
**Researcher:** @spy
**Status:** Complete
---
## Executive Summary
Research identified 12 high-opportunity article topics across both niches. Developer tools (Josh) show strong volume around Cursor IDE and Claude Code comparisons. Creative AI tools (Mara) have exceptional opportunities in AI video generation, particularly CapCut and image-to-video workflows. All recommendations have KD under 40 and volume 500+.
## Research Objective
Find 4-6 article ideas each for two independent blog authors launching personal Hashnode blogs:
- **Josh Mercer**: AI coding tools, developer workflows
- **Mara Solheim**: AI image/video generation, creative workflows
## Methodology
**Tools Used:**
- DataForSEO Keyword Suggestions (11 queries)
- DataForSEO Keyword Ideas (2 queries)
- Perplexity (landscape research)
**Keywords researched:** cursor ide, claude code, ai coding assistant, windsurf ide, cursor vs copilot, midjourney prompts, ai video generator, flux ai, leonardo ai, runway ml
**Estimated cost:** $0.40-0.50
---
# Josh Mercer: AI Developer Tools (6 Article Ideas)
## Article 1: Cursor IDE Setup Guide
| Metric | Value |
|--------|-------|
| **Primary Keyword** | cursor ide |
| **Search Volume** | 18,100/month |
| **Keyword Difficulty** | 35 |
| **Search Intent** | Informational/Navigational |
**Article Title:** "Cursor IDE: The AI Code Editor That Actually Gets It Right (Setup + First Impressions)"
**Content Angle:** Practical first-time setup guide with honest review. Cover installation, initial configuration, and first week experience. Focus on what worked and what frustrated him as a fullstack developer working on real client projects.
**Target Audience:** Developers curious about AI-native code editors, VS Code users considering switching, freelancers evaluating productivity tools.
**Author Fit:** Perfect for Josh's "I tried X so you don't have to" style. He can share real experiences from using it on client projects, including the learning curve and initial confusion.
**Secondary Keywords:**
- cursor ide review (880/month)
- cursor ide free (1,300/month)
- cursor ai code editor (1,000/month)
---
## Article 2: Claude Code Installation Guide
| Metric | Value |
|--------|-------|
| **Primary Keyword** | install claude code |
| **Search Volume** | 8,100/month |
| **Keyword Difficulty** | 22 |
| **Search Intent** | Transactional/Informational |
**Article Title:** "How to Install Claude Code: Complete Setup Guide for Mac, Linux & Windows"
**Content Angle:** Step-by-step installation guide covering all platforms. Include common errors, troubleshooting tips, and initial configuration. Show what the first session looks like with practical examples.
**Target Audience:** Developers who heard about Claude Code and want to try it, devs moving from Cursor/Copilot, terminal-native developers.
**Author Fit:** Josh's practical style shines here. He can document actual installation process, share the "gotchas" he encountered, and provide real terminal output examples.
**Secondary Keywords:**
- claude code download (2,900/month)
- how to use claude code (1,900/month)
- claude code vs cursor (4,400/month)
---
## Article 3: Cursor vs GitHub Copilot Comparison
| Metric | Value |
|--------|-------|
| **Primary Keyword** | cursor vs github copilot |
| **Search Volume** | 1,000/month |
| **Keyword Difficulty** | 7 |
| **Search Intent** | Commercial Investigation |
**Article Title:** "Cursor vs GitHub Copilot: Which AI Coding Assistant Should You Use in 2025?"
**Content Angle:** Side-by-side comparison based on actual usage. Test both on the same project. Cover: code completion quality, context understanding, pricing, integration, and when each tool shines. Be honest about trade-offs.
**Target Audience:** Developers deciding between AI assistants, teams evaluating tooling, freelancers comparing cost vs value.
**Author Fit:** Josh's balanced, skeptical approach is perfect. He can show real examples from his projects without overhyping either tool. His "your mileage may vary" honesty builds credibility.
**Secondary Keywords:**
- cursor vs copilot (2,900/month)
- github copilot vs cursor (1,300/month)
- cursor ai vs copilot (390/month)
---
## Article 4: Windsurf IDE Review
| Metric | Value |
|--------|-------|
| **Primary Keyword** | windsurf ide |
| **Search Volume** | 3,600/month |
| **Keyword Difficulty** | 34 |
| **Search Intent** | Informational/Navigational |
**Article Title:** "Windsurf IDE Review: A Fullstack Developer's Honest Take After One Month"
**Content Angle:** In-depth review after sustained usage. Cover unique features (Cascade, Flows), compare to Cursor, discuss pricing model. Focus on real workflow improvements or frustrations.
**Target Audience:** Developers exploring AI IDE alternatives, Cursor users curious about competition, devs interested in "agentic" coding.
**Author Fit:** Josh's "I've been using X for a month, here's what I wish someone told me" format. His startup experience helps evaluate whether the features solve real problems or are just marketing.
**Secondary Keywords:**
- windsurf ide review (480/month)
- windsurf ai (2,400/month)
- windsurf vs cursor (1,600/month)
---
## Article 5: Best AI Coding Assistants Comparison
| Metric | Value |
|--------|-------|
| **Primary Keyword** | best ai coding assistant |
| **Search Volume** | 1,300/month |
| **Keyword Difficulty** | 38 |
| **Search Intent** | Commercial Investigation |
**Article Title:** "Best AI Coding Assistants in 2025: I Tested 5 Tools So You Don't Have To"
**Content Angle:** Comprehensive comparison of Cursor, Claude Code, GitHub Copilot, Windsurf, and Codeium. Create a decision matrix based on use case (frontend, backend, fullstack, freelance, team). Include pricing comparison.
**Target Audience:** Developers new to AI assistants, tech leads evaluating tools for teams, freelancers optimizing workflow.
**Author Fit:** This is Josh's signature listicle format. His hands-on testing credibility and balanced perspective make him ideal for recommendation content.
**Secondary Keywords:**
- ai coding assistant (4,400/month)
- ai coding tools (1,900/month)
- best ai code editor (720/month)
---
## Article 6: Claude Code Tutorial for Beginners
| Metric | Value |
|--------|-------|
| **Primary Keyword** | how to use claude code |
| **Search Volume** | 1,900/month |
| **Keyword Difficulty** | 28 |
| **Search Intent** | Informational |
**Article Title:** "How to Use Claude Code: A Practical Tutorial for Your First Real Project"
**Content Angle:** Beginner-friendly tutorial using Claude Code on an actual project, not a demo. Show the workflow, effective prompting, and common pitfalls. Include code examples and real outputs.
**Target Audience:** Developers who installed Claude Code but don't know where to start, terminal-hesitant devs, Cursor users trying Claude Code.
**Author Fit:** Josh's teaching style works perfectly. He can share his actual learning curve, mistakes he made, and the "aha moments" that made it click.
**Secondary Keywords:**
- claude code tutorial (1,000/month)
- claude code examples (590/month)
- claude code commands (480/month)
---
# Mara Solheim: Creative AI Tools (6 Article Ideas)
## Article 1: CapCut AI Video Generator Guide
| Metric | Value |
|--------|-------|
| **Primary Keyword** | capcut ai video generator |
| **Search Volume** | 14,800/month |
| **Keyword Difficulty** | 11 |
| **Search Intent** | Informational/Transactional |
**Article Title:** "CapCut AI Video Generator: I Made 10 Videos to Show You What's Actually Possible"
**Content Angle:** Hands-on exploration of CapCut's AI video features. Create different video types and show real results. Be honest about quality, limitations, and when it works best. Include before/after examples.
**Target Audience:** Content creators exploring video, marketers needing quick video content, creators who know CapCut for editing but not AI features.
**Author Fit:** Perfect for Mara's "I tried this so I can tell you if it's worth it" approach. Her genuine excitement when something works, balanced with honest frustrations, builds trust.
**Secondary Keywords:**
- capcut ai (22,200/month)
- capcut image to video (6,600/month)
- capcut text to video (5,400/month)
---
## Article 2: AI Image to Video Generation
| Metric | Value |
|--------|-------|
| **Primary Keyword** | ai image to video generator |
| **Search Volume** | 5,400/month |
| **Keyword Difficulty** | 18 |
| **Search Intent** | Transactional |
**Article Title:** "AI Image to Video: I Tested 5 Tools and This Is What Actually Works"
**Content Angle:** Comparative review of image-to-video tools (Runway, Pika, Luma Dream Machine, Kling, CapCut). Use the same source images across all tools. Show real outputs, rank by quality, discuss pricing and use cases.
**Target Audience:** Digital artists wanting to animate their work, marketers creating dynamic content from static images, creators exploring new formats.
**Author Fit:** Mara's visual background and hands-on testing style make this ideal. She can show her actual experiments and genuine reactions to the results.
**Secondary Keywords:**
- image to video ai (4,400/month)
- photo to video ai (2,900/month)
- ai animate image (1,600/month)
---
## Article 3: Leonardo AI Complete Guide
| Metric | Value |
|--------|-------|
| **Primary Keyword** | leonardo ai image generator |
| **Search Volume** | 4,400/month |
| **Keyword Difficulty** | 31 |
| **Search Intent** | Informational/Navigational |
**Article Title:** "Leonardo AI: The Image Generator I Keep Coming Back To (Complete Guide)"
**Content Angle:** In-depth exploration of Leonardo AI features, including the new image-to-video capabilities. Cover free vs paid tiers, best models for different styles, and practical workflow tips. Show her actual creative process.
**Target Audience:** Creators looking for Midjourney alternatives, designers exploring AI tools, beginners wanting a more accessible platform than Stable Diffusion.
**Author Fit:** Mara's UX background helps explain the interface, and her creative enthusiasm makes the exploration engaging. She can share specific settings and prompts that work.
**Secondary Keywords:**
- leonardo ai pricing (1,600/month, KD 10)
- is leonardo ai free (480/month, KD 21)
- leonardo ai models (320/month)
---
## Article 4: Runway ML Video Generation
| Metric | Value |
|--------|-------|
| **Primary Keyword** | runway ai video generator |
| **Search Volume** | 22,200/month |
| **Keyword Difficulty** | 34 |
| **Search Intent** | Informational/Navigational |
**Article Title:** "Runway AI Video Generator: Everything You Need to Know Before You Start"
**Content Angle:** Comprehensive Runway guide covering Gen-3 Alpha, pricing, best practices, and realistic expectations. Show what different credit amounts can actually produce. Include practical examples from her own projects.
**Target Audience:** Creators considering premium AI video tools, video editors exploring AI integration, content creators with budget for quality tools.
**Author Fit:** Mara's honest approach works perfectly for evaluating a premium tool. She can share whether the cost is worth it, with real examples proving her points.
**Secondary Keywords:**
- runway ml pricing (720/month, KD 9)
- runway gen 3 (880/month)
- runway video ai (1,300/month)
---
## Article 5: Canva AI Video Features
| Metric | Value |
|--------|-------|
| **Primary Keyword** | canva ai video generator |
| **Search Volume** | 49,500/month |
| **Keyword Difficulty** | 16-25 |
| **Search Intent** | Informational |
**Article Title:** "Canva's AI Video Features: What's Actually Useful and What's Just Hype"
**Content Angle:** Honest evaluation of Canva's AI video tools. Many users already have Canva subscriptions - help them understand what's possible without additional tools. Compare quality to dedicated AI video platforms.
**Target Audience:** Existing Canva users curious about AI features, small business owners, social media managers, non-designers creating content.
**Author Fit:** Mara's accessibility focus and honest approach are perfect. She can help non-technical creators understand what they can realistically achieve without premium tools.
**Secondary Keywords:**
- canva ai features (3,600/month)
- canva text to video (2,400/month)
- canva ai image generator (8,100/month)
---
## Article 6: Midjourney Prompts That Actually Work
| Metric | Value |
|--------|-------|
| **Primary Keyword** | midjourney prompts |
| **Search Volume** | 1,900/month |
| **Keyword Difficulty** | 35 |
| **Search Intent** | Informational |
**Article Title:** "Midjourney Prompts: What I Learned After 1000+ Generations (With Examples)"
**Content Angle:** Deep dive into prompt engineering based on extensive personal experimentation. Cover structure, style keywords, negative prompts, and v6-specific techniques. Include before/after prompt refinements with actual outputs.
**Target Audience:** Midjourney users wanting better results, creators frustrated with inconsistent outputs, designers integrating AI into workflow.
**Author Fit:** This is Mara's expertise zone. She can share her actual prompt evolution, mistakes, and breakthroughs. Her "I learned this the hard way" honesty resonates with readers.
**Secondary Keywords:**
- best midjourney prompts (390/month)
- midjourney prompt examples (480/month)
- midjourney v6 prompts (320/month)
---
# Summary & Prioritization
## Josh Mercer: Recommended Publishing Order
| Priority | Article | Volume | KD | Rationale |
|----------|---------|--------|----|-----------|
| 1 | Cursor vs GitHub Copilot | 1,000 | 7 | Lowest KD, quick win |
| 2 | Install Claude Code | 8,100 | 22 | High volume, achievable KD |
| 3 | How to Use Claude Code | 1,900 | 28 | Natural follow-up |
| 4 | Cursor IDE Setup | 18,100 | 35 | Highest volume in set |
| 5 | Windsurf IDE Review | 3,600 | 34 | Emerging topic, less competition |
| 6 | Best AI Coding Assistants | 1,300 | 38 | Pillar content, links to other articles |
## Mara Solheim: Recommended Publishing Order
| Priority | Article | Volume | KD | Rationale |
|----------|---------|--------|----|-----------|
| 1 | CapCut AI Video Generator | 14,800 | 11 | Excellent volume/KD ratio |
| 2 | Canva AI Video Features | 49,500 | 16 | Massive volume, very low KD |
| 3 | AI Image to Video | 5,400 | 18 | Low KD, comparison format |
| 4 | Leonardo AI Guide | 4,400 | 31 | Growing platform, less saturated |
| 5 | Runway AI Video | 22,200 | 34 | High volume, establishes expertise |
| 6 | Midjourney Prompts | 1,900 | 35 | Deep expertise content, pillar piece |
---
## Key Strategic Notes
1. **Josh's quick win**: The "Cursor vs GitHub Copilot" article (KD 7) is an excellent first post to establish ranking presence.
2. **Mara's massive opportunity**: The Canva and CapCut articles have exceptional volume/KD ratios. These should be priority #1-2.
3. **Cross-linking potential**: Both authors can create internal link structures - Josh links between IDE/coding assistant articles, Mara links between video tool articles.
4. **Timing consideration**: Claude Code is trending heavily right now. Josh should prioritize those articles while search volume is elevated.
5. **Differentiation**: The low-competition keywords suggest these niches have room for quality content. Both authors' authentic, hands-on voices will stand out against generic listicles.
---
## Data Sources
All keyword data from DataForSEO Labs (Google Keyword Suggestions, Keyword Ideas) - January 2026.

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# SEO Research: "vibe + X" Blog Name Variants
**Research Date:** 2026-01-10
**Tool:** DataForSEO Labs API
**Target:** Find available blog name for AI-focused blog with format "vibe + word"
---
## Objectives
**Blog Topics:**
- Technical: AI Code agents, LLM reviews, API/service reviews
- Creative: Image generation, video generation, models
**Target Metrics:**
- Search Volume: 100-5000/month
- Keyword Difficulty (KD): < 40
- Domain availability: .com, .ai, .io, .app
---
## Executive Summary
**Total Variants Analyzed:** 10+
**Meeting Criteria:** 3 variants
**Recommended:** vibe ai (880/month, KD 38, +418% yearly growth)
---
## Full Research Results
### ✅ TOP-3 FINALISTS
#### 1. vibe ai ⭐⭐⭐⭐⭐ [RECOMMENDED]
**Core Metrics:**
| Metric | Value | Status |
|--------|-------|--------|
| Search Volume | 880/month | ✅ Target range |
| Keyword Difficulty | 38 | ✅ Passing (on edge) |
| Trend | +418% yearly | ✅ Growing |
| CPC | $8.99 | High commercial value |
| Search Intent | Navigational/Commercial | Mixed |
**SERP Competitors:**
- vibesbiowear.ai (neurotechnology - different niche)
- Google Vibe Code feature (aistudio.google.com/vibe-code)
- vibe-studio.ai (AI-powered Flutter IDE)
- Reddit discussions about vibe coding
**Long-Tail Keywords (Content Strategy):**
| Keyword | Volume | KD | Opportunity |
|---------|--------|-----|------------|
| vibe coding ai | 720/mo | 28 | High |
| vibe code ai | 720/mo | 28 | High |
| best ai for vibe coding | 260/mo | 28 | Medium |
| vibe ai coding | 90/mo | 38 | Low |
| vibe ai transcription | - | - | Related |
| vibe ai review | - | - | Related |
**Domain Availability (To Check):**
- [ ] vibeai.com
- [ ] vibeai.ai
- [ ] vibeai.io
- [ ] vibeai.app
**Pros:**
✅ Direct hit to AI topic
✅ Connection to "vibe coding" cultural trend
✅ Excellent long-tail keywords for content strategy
✅ Growing interest (+418% yearly)
✅ Related searches show relevance
✅ Competitors don't dominate - space to enter
**Cons:**
❌ KD 38 - on upper boundary
❌ Navigational intent - some search for specific products
❌ Competition with Google Vibe Code feature
**Cultural Context:**
"Vibe coding" is a modern cultural term for AI-assisted programming. First appeared as "vibe-coding", now widely used as programming style, not specific brand. Google created "Vibe Code with Gemini" feature, but most use it as general term.
---
#### 2. vibe lab ⭐⭐⭐⭐ [ALTERNATIVE]
**Core Metrics:**
| Metric | Value | Status |
|--------|-------|--------|
| Search Volume | 210/month | ⚠️ Below target |
| Keyword Difficulty | 18 | ✅ Excellent (lowest) |
| Trend | - | No data |
| CPC | - | No data |
| Search Intent | Navigational | - |
**SERP Competitors:**
- Vibe Lab DFW (recording studio, Dallas)
- vibe-lab.org (research consultancy)
- Stanford VIBE Lab (biomechanics research)
- Harvard ViBE Lab (built environment research)
**Long-Tail Keywords:**
No data available
**Domain Availability (To Check):**
- [ ] vibelab.com
- [ ] vibelab.ai
- [ ] vibelab.io
- [ ] vibelab.app
**Pros:**
✅ Lowest KD (18) - easiest to rank
✅ Experimental connotation ("lab" = testing, reviews)
✅ Competitors mostly offline businesses (not tech blogs)
✅ Good fit for "reviews and tests" format
**Cons:**
❌ Low volume (210/month vs 100-5000 target)
❌ Navigational intent (searching for specific studios)
❌ No long-tail keyword data
---
#### 3. vibe studio ⭐⭐⭐
**Core Metrics:**
| Metric | Value | Status |
|--------|-------|--------|
| Search Volume | 1,600/month | ✅ Highest volume |
| Keyword Difficulty | - | ⚠️ Not determined (likely medium-high) |
| Trend | - | No data |
| CPC | $0.89 | Low |
| Search Intent | Navigational | - |
**SERP Competitors:**
- vibe-studio.ai **ALREADY TAKEN** (AI-powered Flutter IDE)
- Multiple fitness studios (Vibe Studio Lynchburg, etc.)
- Local pack dominates SERP
**Domain Availability:**
- [x] ❌ vibe-studio.ai - TAKEN by AI-powered Flutter IDE
- [ ] vibestudio.com (to check)
- [ ] vibestudio.io (to check)
- [ ] vibestudio.app (to check)
**Pros:**
✅ Highest volume (1,600/month)
✅ Creative connotation
✅ Related searches: "Vibe Studio AI", "Vibe studio app"
**Cons:**
❌ vibe-studio.ai already taken by direct competitor (AI IDE)
❌ Local pack dominates (fitness studios)
❌ High competition for branded term
---
### ❌ REJECTED VARIANTS
#### vibe start
**Metrics:**
- Volume: 10/month ❌ (too low)
- KD: No data
- Trend: No data
- Status: **REJECTED** - insufficient volume
---
#### vibe go
**Metrics:**
- Volume: 20/month ❌ (too low)
- KD: 3 (very low competition)
- Trend: **-80% yearly** ❌ (declining interest)
- Status: **REJECTED** - insufficient volume + declining
---
#### vibe tools
**Metrics:**
- Volume: No data ❌
- KD: No data
- Status: **REJECTED** - no search data
---
#### vibe build
**Metrics:**
- Volume: No data ❌
- KD: No data
- Status: **REJECTED** - no search data
---
#### vibe dev
**Metrics:**
- Volume: No data ❌
- KD: No data
- Status: **REJECTED** - no search data
---
#### vibe gen
**Metrics:**
- Volume: No data ❌
- KD: No data
- Status: **REJECTED** - no search data
---
#### vibe code (Context Only)
**Note:** Not a candidate, included for context.
**Metrics:**
- Volume: 90,500/month (anomalously high)
- Reason: Cultural term + established brands
- Context: "vibe coding" is modern term for AI-assisted programming
This is a cultural phenomenon, not a viable brand opportunity. The term is already associated with Google's "Vibe Code with Gemini" feature and general programming style.
---
## Final Recommendation
### Primary: **vibe ai**
**Rationale:**
1. Direct hit to AI topic
2. Connection to growing "vibe coding" cultural trend (+418% yearly)
3. KD 38 is passable for quality content blog
4. Excellent long-tail keywords for content strategy
5. Competitors don't dominate - space to enter
**Content Strategy for vibe ai:**
- Reviews: "best ai for vibe coding"
- Tutorials: "vibe coding ai tools"
- News: "vibe ai updates"
- Comparisons: AI Code agents
- Creative: Image/Video generation reviews
**Next Steps:**
1. Check domain availability: vibeai.com, vibeai.ai, vibeai.io, vibeai.app
2. If domains taken, consider alternatives:
- vibe-ai.com
- thevibeai.com
- vibeai.blog
---
### Alternative: **vibe lab**
**If vibe ai domains are taken:**
- Lowest KD (18) - easiest to rank
- Less competition
- Good for "experimental" format
- Content focus: "lab tests", "experiments", "reviews"
---
## Risk Analysis
### Risk #1: KD 38 may be difficult for startup
**Mitigation:**
- Start with long-tail keywords (KD 25-28)
- Gradually move to head term
- Content cluster strategy: vibe coding ai → vibe code ai → vibe ai
### Risk #2: Navigational intent - people search for specific products
**Mitigation:**
- Become that product (blog as destination)
- Build brand recognition (SEO + branding + social presence)
### Risk #3: Google Vibe Code feature competes
**Mitigation:**
- Focus on reviews, comparisons, news (not duplicate Google feature)
- Position as comprehensive resource vs single tool
---
## Search Intent Analysis
**Key Finding:** Most "vibe X" queries have navigational intent.
**This is GOOD for branding:**
- People will search for your specific blog
- Need recognition: SEO + branding + social presence
- Build destination resource, not just content site
---
## Competitive Strategy
**Market Opportunity:**
- No one dominates "vibe ai" as AI blog
- Can become "go-to" resource for vibe coding
- Connection to trend provides natural growth
**Entry Points:**
1. Long-tail keywords first (easier to rank)
2. Build authority through quality content
3. Leverage "vibe coding" cultural momentum
4. Position as comprehensive AI resource
---
## Additional Insights
### About "Vibe Coding" Phenomenon
- Cultural term for AI-assisted programming
- Recently emerged, rapidly gained popularity
- Google created "Vibe Code with Gemini" feature
- Most use as programming style, not specific brand
- Related to: cursor vibes, claude vibes, AI pair programming
### Market Timing
- Growing trend (+418% yearly for "vibe ai")
- Early enough to establish brand
- Late enough to have search volume
- Cultural momentum supports entry
---
## Data Sources
- DataForSEO Labs API
- Keyword Data Google Ads Search Volume API
- SERP Organic Live Advanced API
- Bulk Keyword Difficulty API
- Related Keywords API
**Location:** United States
**Language:** English
**Date Range:** Last 12 months trend data
---
## Appendix: Domain Check Checklist
### vibe ai
- [ ] vibeai.com - check via whois
- [ ] vibeai.ai - check via whois
- [ ] vibeai.io - check via whois
- [ ] vibeai.app - check via whois
### vibe lab
- [ ] vibelab.com - check via whois
- [ ] vibelab.ai - check via whois
- [ ] vibelab.io - check via whois
- [ ] vibelab.app - check via whois
### vibe studio
- [x] ❌ vibe-studio.ai - TAKEN (AI Flutter IDE)
- [ ] vibestudio.com - check via whois
- [ ] vibestudio.io - check via whois
- [ ] vibestudio.app - check via whois
### Alternative Formats (if needed)
- [ ] vibe-ai.com
- [ ] thevibeai.com
- [ ] vibeai.blog
- [ ] vibe-lab.com
- [ ] thevibelab.com
- [ ] vibelab.blog
---
**Status:** Research complete, awaiting domain availability check
**Next Action:** Manual whois check for domain availability
**Recommendation:** Proceed with vibe ai if domains available

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<img src="https://r2cdn.perplexity.ai/pplx-full-logo-primary-dark%402x.png" style="height:64px;margin-right:32px"/>
# AI-Assisted Development: Кластеризованная терминология и подходы
Проведена детальная кластеризация терминов разработки с помощью AI по восьми резонным доменам. Каждая позиция содержит источники с указанием организаций, authority ranking и подробные описания.
## Domain 1: Experimental \& Low-Quality Approaches
### Vibe Coding
**Authority Rank: 1** | **Perception: Negative**
**Источники:**
1. **Andrej Karpathy** (OpenAI co-founder, Tesla AI Director) — википедия, февраль 2025[^1][^2]
2. **Collins English Dictionary** — Word of the Year 2025[^1]
3. **SonarSource** (Code Quality Platform) — анализ качества кода[^3]
**Описание:**
Термин придуман Андреем Карпати в феврале 2025 года и быстро стал культурным феноменом — Collins English Dictionary назвал его словом года 2025. Это подход, где разработчик описывает задачу на естественном языке, AI генерирует код, но ключевое отличие: **разработчик НЕ проверяет код**, а только смотрит на результаты выполнения.[^2][^1]
Как отметил программист Simon Willison: "Если LLM написал каждую строку вашего кода, но вы всё проверили, протестировали и поняли — это не vibe coding, это использование LLM как typing assistant". Ключевая характеристика: принятие AI-сгенерированного кода без его понимания.[^1]
Критики указывают на отсутствие ответственности, проблемы с поддерживаемостью и увеличенный риск внедрения уязвимостей безопасности. В мае 2025 года обнаружено, что шведское приложение Lovable, использующее vibe coding, имело уязвимости безопасности в 170 из 1,645 созданных веб-приложений. Fast Company в сентябре 2025 сообщил о "vibe coding hangover" — senior инженеры цитируют "development hell" при работе с таким кодом.[^3][^1]
Подходит для "throwaway weekend projects", как изначально задумывал Карпати, но рискован для production систем.[^3][^1]
***
## Domain 2: Enterprise \& Production-Grade Methodologies
### AI-Driven Development Life Cycle (AI-DLC)
**Authority Rank: 1** | **Perception: Positive - Enterprise**
**Источники:**
1. **AWS (Amazon Web Services)** — Raja SP, Principal Solutions Architect, июль 2025[^4]
2. **Amazon Q Developer \& Kiro** — официальная платформа AWS[^4]
**Описание:**
Представлена AWS в июле 2025 года как трансформативная enterprise-методология. Raja SP, Principal Solutions Architect AWS, создал AI-DLC вместе с командой после работы с более чем 100 крупными заказчиками.[^4]
Методология позиционирует AI как **центрального коллаборатора** на протяжении всего SDLC с двумя мощными измерениями:
1. **AI-Powered Execution with Human Oversight** — AI систематически создает детальные рабочие планы, активно запрашивает уточнения и guidance, откладывает критические решения на людей. Только люди обладают контекстуальным пониманием и знанием бизнес-требований.[^4]
2. **Dynamic Team Collaboration** — пока AI обрабатывает рутинные задачи, команды объединяются в коллаборативных пространствах для real-time problem solving, креативного мышления и быстрого принятия решений.[^4]
Workflow: AI создает план → задает уточняющие вопросы для получения контекста → реализует решения только после получения человеческой валидации. Этот паттерн повторяется быстро для каждой SDLC-активности.[^4]
**Три фазы разработки:**
- **Inception phase**: AI трансформирует бизнес-интент в детальные требования через "Mob Elaboration" — вся команда активно валидирует вопросы и предложения AI[^4]
- **Construction phase**: AI предлагает логическую архитектуру, domain models, code solution через "Mob Construction"[^4]
- **Operations phase**: AI применяет накопленный контекст для управления infrastructure as code и deployments[^4]
**Терминологические инновации:** традиционные "sprints" заменены на "bolts" — короткие, интенсивные рабочие циклы в часах или днях вместо недель; Epics заменены на Units of Work.[^4]
**Преимущества:** velocity (задачи за часы/дни вместо недель), innovation (AI освобождает время), quality (continuous clarification), market responsiveness, улучшенный developer experience.[^4]
### Spec-Driven Development (SDD)
**Authority Rank: 2** | **Perception: Positive - Systematic**
**Источники:**
1. **GitHub Engineering** — Den Delimarsky, Spec Kit toolkit, сентябрь 2025[^5][^6][^7]
2. **ThoughtWorks Technology Radar** — ноябрь 2025[^8][^9]
3. **Red Hat Developers** — октябрь 2025[^10]
**Описание:**
Возник в 2025 году как прямой ответ на проблемы "vibe coding". ThoughtWorks включил его в Technology Radar как ключевую emerging practice. GitHub open-sourced Spec Kit в сентябре 2025 года, поддерживает Claude Code, GitHub Copilot, Gemini CLI.[^11][^7][^5][^8]
**Ключевой принцип:** спецификация становится источником истины (source of truth), не код. Как заявляет GitHub: "В этом новом мире поддержка софта означает эволюцию спецификаций. Lingua franca разработки переходит на более высокий уровень, а код — это last-mile подход".[^9]
**Workflow Spec Kit:**
1. **Constitution** — immutable принципы высокого уровня, применяемые к каждому изменению (rules file)[^7][^9]
2. **/specify** — создание спецификации из high-level промпта[^7]
3. **/plan** — техническое планирование на основе спецификации[^7]
4. **/tasks** — разбивка на управляемые фазированные части для AI-агента[^7]
**Три интерпретации SDD** (по анализу ThoughtWorks):[^9]
- **Spec-first**: хорошо продуманная спецификация пишется первой, затем используется в AI-workflow
- **Spec-anchored**: спецификация сохраняется после завершения задачи для эволюции и поддержки feature
- **Spec-as-source**: спецификация — главный source file; только spec редактируется человеком, код никогда
**Инструменты и реализации:**
- **Amazon Kiro**: три стадии workflow — requirements, design, tasks creation[^12][^8]
- **GitHub Spec Kit**: трехступенчатый процесс с rich orchestration, configurable prompts, constitution[^8][^9]
- **Tessl Framework** (private beta, сентябрь 2025): радикальный подход, где спецификация — maintained artifact, не код[^8][^9]
ThoughtWorks предупреждает: workflows остаются elaborate и opinionated, инструменты ведут себя по-разному в зависимости от размера задачи, иногда генерируют длинные spec files, сложные для ревью. Мартин Фаулер (Martin Fowler) на сайте ThoughtWorks отмечает параллели с Model-Driven Development (MDD) из прошлого и предупреждает о потенциальных подводных камнях.[^9][^8]
### Architecture-First AI Development
**Authority Rank: 3** | **Perception: Positive - Professional/Mature**
**Источники:**
1. **WaveMaker** — Vikram Srivats (CCO), Prashant Reddy (Head of AI Product Engineering), январь 2026[^13][^12]
2. **ITBrief Industry Analysis** — январь 2026[^13][^12]
**Описание:**
Индустриальный shift 2026 года, идентифицированный руководителями WaveMaker, low-code platform provider. В январе 2026 ITBrief опубликовал анализ: "AI coding tools face 2026 reset towards architecture".[^12][^13]
**Ключевая цитата** Vikram Srivats, CCO WaveMaker: "В некотором смысле, второе пришествие AI coding tools должно быть всё об **Architectural Intelligence** — просто Artificial Intelligence больше не подходит".[^13][^12]
**Суть подхода:** переход от "vibe coding" экспериментов к governance, architecture alignment, долгосрочной maintainability. Vendors и enterprises смещают фокус от экспериментального использования и раннего роста выручки к архитектуре, управлению и долгосрочной поддерживаемости.[^12][^13]
**Ключевые характеристики:**
- Дизайн системы перед реализацией
- AI-агенты с четкими ролями: Architect, Builder, Guardian
- Кодирование архитектурных правил, enforcement review processes
- Работа от формальных спецификаций
- Уважение к внутренним стандартам организаций[^13][^12]
**Проблема, которую решает:** крупные организации работают на слоях абстракций, фреймворков и design patterns, созданных годами. Эти структуры защищают критические системы, обеспечивают compliance и поддерживают reliability в больших командах. Новые инструменты, обходящие эти структуры, создают технический долг, security gaps, несогласованность между командами.[^12][^13]
Prashant Reddy, Head of AI Product Engineering WaveMaker: "В 2026 AI-powered development tools созреют далеко за пределы vibe coding или базовой proof of concept помощи. Следующая волна сфокусируется на генерации production-grade кода, который seamlessly вписывается в enterprise architecture standards. Организациям нужны инструменты, которые понимают и уважают абстракции, фреймворки и паттерны, уже используемые внутри команд, не инструменты, переизобретающие колесо".[^13][^12]
**Enterprise demand:** engineering leaders в регулируемых секторах хотят audit trails, consistent behaviour, alignment с compliance controls. Vendors вроде Amazon уже начали внедрять documentation-first и specification-driven workflows.[^12][^13]
***
## Domain 3: Quality \& Validation-Focused Approaches
### Test-Driven Development with AI (TDD-AI)
**Authority Rank: 1** | **Perception: Positive - Quality-Focused**
**Источники:**
1. **Galileo AI Research** — август 2025[^14][^15]
2. **Builder.io Engineering** — август 2025[^16]
**Описание:**
Адаптация традиционного TDD для AI-систем. Galileo AI опубликовал две статьи в августе 2025: "Leveraging Test-Driven Development for AI System Architecture" и "Adapting TDD for Reliable AI Systems".[^15][^14]
**Ключевой workflow:** тесты пишутся первыми → AI генерирует код для прохождения тестов → verify → refactor. Фокус на валидации и качестве. Статистическое тестирование для недетерминированных AI-выходов — критически важное отличие от традиционного TDD.[^14][^15]
Подход решает challenges AI-reliability через систематическую верификацию. Обеспечивает корректность кода перед deployment. Особенно важно для AI-систем, где выходы могут варьироваться.[^15][^14]
### Human-in-the-Loop (HITL) AI Development
**Authority Rank: 2** | **Perception: Positive - Responsible**
**Источники:**
1. **Google Cloud Documentation** — официальная документация, 2026[^17]
2. **Encord Research** — декабрь 2024[^18]
3. **Atlassian Engineering** — HULA framework, сентябрь 2025[^19][^20]
**Описание:**
Люди активно вовлечены в жизненный цикл AI-системы. Continuous feedback и validation loops. Гибридный подход: человеческое суждение + AI-исполнение.[^17][^18]
**HULA (Human-in-the-Loop AI)** — фреймворк от Atlassian для software development agents, представлен в сентябре 2025. Atlassian опубликовал блог "Human in the Loop Software Development Agents", документируя подход к интеграции человеческого надзора в аgentic coding.[^20]
Google Cloud определяет HITL как процесс, где AI-системы активно запрашивают человеческий input для критических решений, обучения и валидации. Encord Research подробно описывает применение в machine learning.[^18][^17]
**Ключевые преимущества:** акцент на надзоре, контроле, ответственном AI deployment. Люди валидируют критические решения, AI обрабатывает выполнение. Снижение AI-ошибок через непрерывный human supervision.[^20][^17][^18]
### Quality-First AI Coding
**Authority Rank: 3** | **Perception: Positive - Professional**
**Источники:**
1. **Qodo.ai** (formerly CodiumAI) — AI code review platform, декабрь 2025[^21][^22]
2. **Qodo.ai Product Demo** — сентябрь 2024[^21]
**Описание:**
Целостность кода в основе подхода. Qodo.ai — платформа с agentic AI code generation и comprehensive testing. AI-powered тестирование, валидация, code review.[^22][^23][^21]
**Production-ready фокус:** автоматическая генерация тестов для каждого изменения кода. Reliability, maintainability, security с самого начала. Прямой контраст "vibe coding" — качество non-negotiable.[^22][^21]
Платформа позиционируется как "quality-first AI code generation to help busy devs". Интеграция в workflow для обеспечения, что сгенерированный AI код соответствует production standards.[^23][^24][^21][^22]
### Deterministic AI Development
**Authority Rank: 4** | **Perception: Positive - Enterprise/Compliance**
**Источники:**
1. **Augment Code Research** — август 2025[^25]
**Описание:**
Идентичные выходы для идентичных входов. Rule-based архитектуры для предсказуемости. Лучше всего подходит для: security scanning, compliance checks, refactoring tasks.[^25]
**Гибридный подход:** вероятностное рассуждение (probabilistic reasoning) + детерминированное исполнение (deterministic execution). Решает проблему AI non-determinism concerns.[^25]
Auditable, repeatable результаты. Критично для enterprise compliance requirements. Обеспечивает трассируемость решений AI-системы.[^25]
***
## Domain 4: Collaborative Development Patterns
### AI Pair Programming
**Authority Rank: 1** | **Perception: Positive - Collaborative**
**Источники:**
1. **GitHub Copilot (Microsoft)** — официальная документация, январь 2026[^26][^27]
2. **Qodo.ai Documentation** — март 2025[^28]
3. **GeeksforGeeks Technical Education** — июль 2025[^26]
**Описание:**
AI выступает как "pair programmer" или coding partner. Основано на традиционном pair programming: driver (human/AI) и navigator (human/AI) роли.[^29][^28][^26]
Real-time collaboration и feedback. AI как thought partner в problem-solving. Инструменты: GitHub Copilot, Cursor, Windsurf. Разработчик остается at the helm, AI предлагает решения.[^27][^29][^26]
Conversational code development. Microsoft/GitHub официально документируют AI pair programming в VS Code Copilot docs. Qodo.ai подробно описывает практики в своем glossary. GeeksforGeeks предоставляет educational контент по методологии.[^27][^28][^26]
### Mobbing with AI / Mob Programming with AI
**Authority Rank: 2** | **Perception: Positive - Team-Focused**
**Источники:**
1. **Atlassian Engineering Blog** — декабрь 2025[^30]
2. **Aaron Griffith** (Human \& AI Collaboration Expert) — январь 2025[^31]
3. **LinkedIn Professional Discussion** — Alex Bunardzic, октябрь 2025[^32]
**Описание:**
Вся команда работает вместе, AI как driver. AI генерирует код/тесты перед командой. Команда navigates, reviews, refines в real-time.[^30][^31][^32]
Atlassian опубликовал "Mobbing with AI" в декабре 2025, документируя практики интеграции AI в mob programming sessions. Aaron Griffith провел презентацию "Human \& AI Collaboration in Mob Programming" в январе 2025.[^31][^30]
**Ключевые преимущества:**
- Коллективная AI literacy development
- Быстрое принятие решений с множественными перспективами
- Mob Elaboration и Mob Construction (из AI-DLC)[^30][^4]
- Team-wide context sharing[^32][^30]
Лучше всего для: complex problems, knowledge transfer, quality assurance.[^31][^32][^30]
### Agentic Coding / Agentic Programming
**Authority Rank: 3** | **Perception: Positive - Advanced**
**Источники:**
1. **arXiv Research Paper** — "AI Agentic Programming: A Survey", август 2025[^33]
2. **AI Accelerator Institute** — февраль 2025[^34]
3. **Apiiro Security Platform** — сентябрь 2025[^35]
**Описание:**
LLM-based агенты автономно планируют, выполняют, улучшают задачи разработки. Выходит за рамки code completion: генерирует программы, диагностирует баги, пишет тесты, рефакторит.[^33][^34][^35]
arXiv опубликовал comprehensive survey "AI Agentic Programming: A Survey of Techniques, Challenges, and Applications" в августе 2025. Документ описывает ключевые свойства: **autonomy, interactive, iterative refinement, goal-oriented**.[^34][^33]
**Agent behaviors:** planning, memory management, tool integration, execution monitoring. Multi-agent архитектуры. Self-improving systems.[^35][^33][^34]
AI Accelerator Institute: "Agentic code generation — будущее software development". Apiiro предупреждает о рисках: security concerns, необходимость governance.[^34][^35]
***
## Domain 5: Workflow \& Process Integration
### Prompt-Driven Development (PDD)
**Authority Rank: 1** | **Perception: Neutral to Positive**
**Источники:**
1. **Capgemini Software Engineering** — май 2025[^36]
2. **Hexaware Technologies** — август 2025[^37]
3. **Andrew Miller (Substack)** — январь 2025[^38]
**Описание:**
Разработчик разбивает требования на серию промптов. LLM генерирует код для каждого промпта. **Критически важно:** разработчик ОБЯЗАН проверять LLM-сгенерированный код.[^36][^37][^38]
Capgemini Software Engineering опубликовал "Prompt Driven Development" в мае 2025, документируя подход. Hexaware Technologies описывает как "Coding in Conversation" — август 2025.[^37][^36]
**Новый навык:** умение разбивать требования на эффективные промпты. Итеративное улучшение через conversation. Фокус на качестве промпта и контексте.[^38][^36][^37]
**Критическое отличие от vibe coding:** code review mandatory. Это не "принять и забыть", а структурированный процесс с проверкой.[^36][^37]
### AI-Augmented Development
**Authority Rank: 2** | **Perception: Positive - Practical**
**Источники:**
1. **GitLab Official Documentation** — декабрь 2023[^39]
2. **Virtusa Digital Transformation** — январь 2024[^40]
3. **TeiLur Talent Insights** — январь 2026[^41]
**Описание:**
AI-инструменты ускоряют SDLC на всех фазах. Фокус: code generation, bug detection, automated testing, smart documentation.[^42][^39][^40][^41]
GitLab официально документирует "AI-augmented software development: Agentic AI for DevOps". Virtusa позиционирует как digital theme. TeiLur Talent описывает tools, benefits \& best practices в январе 2026.[^39][^40][^41]
**Ключевой принцип:** люди обрабатывают стратегию, AI обрабатывает исполнение. Balanced human-AI collaboration. Интеграция в существующие workflows. DevOps pipeline compatibility.[^40][^41][^39]
Productivity gains без замены человеческого judgment. Практичный, широко применимый подход.[^41][^42][^39]
### Copilot-Driven Development
**Authority Rank: 3** | **Perception: Positive - Practical**
**Источники:**
1. **GitHub/Microsoft Official** — январь 2026[^43][^27]
2. **Emergn Journey Analysis** — сентябрь 2025[^44]
3. **LinkedIn Professional Experience** — Rajasekaran, август 2025[^43]
**Описание:**
Конкретно использование GitHub Copilot или подобных инструментов как development partner (не просто assistant).[^45][^44][^27][^43]
Microsoft официально документирует в VS Code: "GitHub Copilot in VS Code" — январь 2026. Emergn опубликовал case study: "How AI tools impact the way we develop software: our GitHub Copilot journey" — сентябрь 2025.[^44][^27]
**Характеристики:**
- Context-aware, учится coding style
- Enables conceptual focus вместо mechanical typing
- AI development partner интегрирован в IDE[^27][^43][^44]
Real-world adoption case studies. Workflow transformation: думаешь концептами, AI обрабатывает syntax. Rajasekaran описывает "My Journey with AI-First Development: How Copilot transformed my process".[^43][^44]
### Conversational Coding
**Authority Rank: 4** | **Perception: Neutral to Positive**
**Источники:**
1. **Google Cloud Platform** — январь 2026[^46]
2. **arXiv Research** — март 2025[^47]
3. **OpenAI Community Discussion** — октябрь 2024[^48]
**Описание:**
Natural language взаимодействие с AI для разработки. Итеративный, dialogue-based подход. Context retention через сессии.[^46][^47][^48]
Google Cloud официально документирует "Conversational AI" подходы. arXiv опубликовал "Conversational AI as a Coding Assistant" в марте 2025.[^47][^46]
Conversational refinement кода. Эксперименты с "Convo" programming language в OpenAI Community. Снижает барьер входа. Фокус на выражении intent вместо syntax. Multi-turn interactions для сложных задач.[^48][^46][^47]
***
## Domain 6: Code Review \& Maintenance
### AI Code Review
**Authority Rank: 1** | **Perception: Neutral to Positive**
**Источники:**
1. **LinearB Engineering Metrics Platform** — март 2024[^49]
2. **Swimm.io Developer Education** — ноябрь 2025[^50]
3. **CodeAnt.ai Platform** — май 2025[^51]
**Описание:**
Автоматизированное code examination используя ML/LLM. Static и dynamic analysis. Идентифицирует bugs, security issues, performance problems, code smells.[^49][^50][^51]
LinearB: "What is AI Code Review, How It Works, and How to Get Started" — март 2024. Swimm.io: "AI Code Review: How It Works and 5 Tools You Should Know" — ноябрь 2025. CodeAnt.ai: "What Is AI-Driven Code Review vs Traditional Review (2025 Guide)" — май 2025.[^50][^51][^49]
**Инструменты:** Qodo, CodeRabbit, SonarQube AI features. Scalable quality assurance. 24/7 availability. Consistency в enforcement стандартов.[^51][^49][^50]
**Best practices:** AI предлагает, человек approves критические изменения. Complements human review, не заменяет полностью.[^49][^50][^51]
***
## Domain 7: Specialized \& Emerging Approaches
### Ensemble Programming/Prompting with AI
**Authority Rank: 1** | **Perception: Positive - Advanced**
**Источники:**
1. **Kinde.com AI Engineering Insights** — ноябрь 2004[^52]
2. **Ultralytics ML Research** — декабрь 2025[^53]
3. **arXiv Ensemble Learning Research** — июнь 2025[^54]
**Описание:**
Множественные AI models/промпты комбинируются для лучших результатов. Aggregation методы: voting, averaging, weighted scoring.[^52][^53][^54]
Kinde.com: "Ensemble Prompting That Actually Moves the Needle". Ultralytics: "Exploring Ensemble Learning: Its role in AI and ML" — декабрь 2025. arXiv: "Ensemble Learning for Large Language Models in Text Classification" — июнь 2025.[^53][^54][^52]
**Преимущества:** улучшает accuracy и reliability vs single model. Снижает model-specific biases. Ensemble learning техники применяются к code generation. Множественные LLMs консультируются для сложных решений. Consensus-based code generation.[^54][^52][^53]
### Prompt Engineering for Development
**Authority Rank: 2** | **Perception: Neutral to Positive**
**Источники:**
1. **Google Cloud Official Guide** — январь 2026[^55]
2. **OpenAI Official Documentation** — апрель 2025[^56]
3. **GitHub Developer Blog** — май 2024[^57]
**Описание:**
Crafting эффективных промптов для AI models. Критический навык для AI-assisted development.[^58][^59][^60][^55][^56][^57]
Google Cloud: "Prompt Engineering for Generative AI" — январь 2026. OpenAI: официальная документация "Prompt engineering" — апрель 2025. GitHub: "A developer's guide to prompt engineering and LLMs" — май 2024.[^55][^56][^57]
**Ключевые элементы:** context provision, instruction clarity, constraint specification. Emerging discipline, комбинирующая техническое знание с пониманием AI models.[^59][^60][^56][^57][^58][^55]
**Техники:** few-shot learning, chain-of-thought, role prompting. Essential для качественной AI code generation. Structured prompting frameworks.[^56][^57][^59][^55]
### Intentional AI Development
**Authority Rank: 3** | **Perception: Positive - Thoughtful**
**Источники:**
1. **Tech.eu Industry Analysis** — январь 2026[^61]
2. **LinkedIn Thought Leadership** — июнь 2024[^62]
3. **Personal Development (ghuntley.com)** — август 2025[^63][^64]
**Описание:**
Purpose-driven AI design. Четкие роли и границы для AI. Deliberate practice и learning approach.[^64][^65][^61][^62][^63]
Tech.eu: "Adopting an Intentional AI Strategy in 2026" — январь 2026. LinkedIn: "Intentional AI: Guiding Rational and Purposeful AI development". ghuntley.com: "deliberate intentional practice" — август 2025.[^61][^62][^63][^64]
Human-scaled systems. Thoughtful integration vs blind adoption. Стратегический AI deployment. Этические соображения built-in. Фокус на meaningful automation, не automation for its own sake.[^65][^62][^63][^61]
***
## Domain 8: General \& Cross-Cutting Terms
### AI-Assisted Coding / AI-Assisted Development
**Authority Rank: 1** | **Perception: Neutral to Positive**
**Источники:**
1. **Wikipedia Official Entry** — июль 2025[^66]
2. **Ubiminds Analysis** — февраль 2025[^67]
3. **GitLab Official Documentation** — 2025[^68]
**Описание:**
Широкий umbrella term для AI, улучшающего задачи software development. Включает code completion, documentation generation, testing, debugging assistance.[^66][^67][^68]
Wikipedia: официальная статья "AI-assisted software development" — июль 2025. Ubiminds: "AI-Assisted Coding: Friend or Foe?" — февраль 2025. GitLab: "AI Code Generation Explained: A Developer's Guide".[^67][^68][^66]
**Характеристики:** разработчик остается in control, проверяет все предложения. Наиболее распространенный adoption pattern глобально. Инструменты от autocomplete (Copilot) до full agents (Cursor).[^69][^68][^66][^67]
Нейтральный термин без methodology implications. Фундамент для более специфических подходов. Foundation term, от которого отталкиваются все остальные практики.[^68][^66][^67]
***
## Ключевые выводы по доменам
**Domain 1** (Experimental) содержит только Vibe Coding — единственный термин с явно негативной коннотацией, backed by high-authority источниками (OpenAI founder, Collins Dictionary).[^2][^1][^3]
**Domain 2** (Enterprise) — наиболее authoritative домен с AWS, GitHub Engineering, ThoughtWorks как источниками. Фокус на production-grade, governance, architecture.[^5][^8][^12][^4]
**Domain 3** (Quality) — research-heavy домен (Galileo AI, Google Cloud, Atlassian) с акцентом на ответственную разработку.[^14][^17][^21]
**Domain 4** (Collaborative) — практические patterns, backed by крупными платформами (Microsoft/GitHub, Atlassian) и research (arXiv).[^26][^33][^30]
**Domains 5-7** — workflow integration, code review, specialized techniques — более узкие, но важные практики.[^50][^52][^55][^36]
**Domain 8** — general term, который служит baseline для всех остальных подходов.[^66][^67][^68]
<span style="display:none">[^70][^71][^72][^73][^74][^75][^76]</span>
<div align="center"></div>
[^1]: https://en.wikipedia.org/wiki/Vibe_coding
[^2]: https://answerrocket.com/glossary-of-common-ai-terms/
[^3]: https://www.sonarsource.com/resources/library/vibe-coding/
[^4]: https://aws.amazon.com/blogs/devops/ai-driven-development-life-cycle/
[^5]: https://github.blog/ai-and-ml/generative-ai/spec-driven-development-with-ai-get-started-with-a-new-open-source-toolkit/
[^6]: https://blog.tadsummit.com/2025/11/19/spec-driven-development/
[^7]: https://developer.microsoft.com/blog/spec-driven-development-spec-kit
[^8]: https://www.thoughtworks.com/radar/techniques/spec-driven-development
[^9]: https://martinfowler.com/articles/exploring-gen-ai/sdd-3-tools.html
[^10]: https://developers.redhat.com/articles/2025/10/22/how-spec-driven-development-improves-ai-coding-quality
[^11]: https://www.linkedin.com/pulse/real-ai-story-2025-hype-discipline-thoughtworks-gvtcf
[^12]: https://itbrief.co.uk/story/ai-coding-tools-face-2026-reset-towards-architecture
[^13]: https://itbrief.news/story/ai-coding-tools-face-2026-reset-towards-architecture
[^14]: https://galileo.ai/blog/tdd-ai-system-architecture
[^15]: https://galileo.ai/blog/test-driven-development-ai-systems
[^16]: https://www.builder.io/blog/test-driven-development-ai
[^17]: https://cloud.google.com/discover/human-in-the-loop
[^18]: https://encord.com/blog/human-in-the-loop-ai/
[^19]: https://www.youtube.com/watch?v=0_zwdxcxxYk
[^20]: https://www.atlassian.com/blog/atlassian-engineering/hula-blog-autodev-paper-human-in-the-loop-software-development-agents
[^21]: https://www.youtube.com/watch?v=pIfsMysdcK8
[^22]: https://www.qodo.ai/ai-code-review-platform/
[^23]: https://codeparrot.ai/blogs/qodoai-code-with-an-agentic-ai
[^24]: https://javarevisited.wordpress.com/2025/05/15/is-qodo-ai-really-worth-it-for-code-review-in-2025-2/
[^25]: https://www.augmentcode.com/guides/deterministic-ai-for-predictable-coding
[^26]: https://www.geeksforgeeks.org/artificial-intelligence/what-is-ai-pair-programming/
[^27]: https://code.visualstudio.com/docs/copilot/overview
[^28]: https://www.qodo.ai/glossary/pair-programming/
[^29]: https://graphite.com/guides/ai-pair-programming-best-practices
[^30]: https://www.atlassian.com/blog/atlassian-engineering/mobbing-with-ai
[^31]: https://www.youtube.com/watch?v=BsFPbYX4WXQ
[^32]: https://www.linkedin.com/posts/alexbunardzic_mob-programming-is-the-absolute-best-approach-activity-7387190042420604929-EQob
[^33]: https://arxiv.org/html/2508.11126v1
[^34]: https://www.aiacceleratorinstitute.com/agentic-code-generation-the-future-of-software-development/
[^35]: https://apiiro.com/glossary/agentic-coding/
[^36]: https://capgemini.github.io/ai/prompt-driven-development/
[^37]: https://hexaware.com/blogs/prompt-driven-development-coding-in-conversation/
[^38]: https://andrewships.substack.com/p/prompt-driven-development
[^39]: https://about.gitlab.com/topics/agentic-ai/ai-augmented-software-development/
[^40]: https://www.virtusa.com/digital-themes/ai-augmented-development
[^41]: https://www.teilurtalent.com/insights/what-is-ai-augmented-development
[^42]: https://www.theninjastudio.com/blog/a-beginners-guide-to-ai-augmented-software-development
[^43]: https://www.linkedin.com/pulse/my-journey-ai-first-development-how-copilot-process-rajasekaran-pxfwc
[^44]: https://www.emergn.com/insights/how-ai-tools-impact-the-way-we-develop-software-our-github-copilot-journey/
[^45]: https://arxiv.org/pdf/2502.13199.pdf
[^46]: https://cloud.google.com/conversational-ai
[^47]: https://arxiv.org/abs/2503.16508
[^48]: https://community.openai.com/t/convo-a-conversational-programming-language/969667
[^49]: https://linearb.io/blog/ai-code-review
[^50]: https://swimm.io/learn/ai-tools-for-developers/ai-code-review-how-it-works-and-3-tools-you-should-know
[^51]: https://www.codeant.ai/blogs/ai-vs-traditional-code-review
[^52]: https://kinde.com/learn/ai-for-software-engineering/prompting/ensemble-prompting-that-actually-moves-the-needle/
[^53]: https://www.ultralytics.com/blog/exploring-ensemble-learning-and-its-role-in-ai-and-ml
[^54]: https://arxiv.org/html/2503.13505v2
[^55]: https://cloud.google.com/discover/what-is-prompt-engineering
[^56]: https://platform.openai.com/docs/guides/prompt-engineering
[^57]: https://github.blog/ai-and-ml/generative-ai/prompt-engineering-guide-generative-ai-llms/
[^58]: https://strapi.io/blog/ChatGPT-Prompt-Engineering-for-Developers
[^59]: https://addyo.substack.com/p/the-prompt-engineering-playbook-for
[^60]: https://www.pluralsight.com/resources/blog/software-development/prompt-engineering-for-developers
[^61]: https://tech.eu/2026/01/05/adopting-an-intentional-ai-strategy-in-2026/
[^62]: https://www.linkedin.com/pulse/intentional-ai-guiding-rational-purposeful-stoic-the-stoic-citadel-femhc
[^63]: https://www.linkedin.com/pulse/ai-augmented-deliberate-practice-assisted-coding-using-ajit-jaokar-4yice
[^64]: https://ghuntley.com/play/
[^65]: https://wearebreakthrough.co.uk/the-relearning-season-intentional-ai-design-for-practical-everyday-use/
[^66]: https://en.wikipedia.org/wiki/AI-assisted_software_development
[^67]: https://ubiminds.com/en-us/ai-assisted-coding/
[^68]: https://about.gitlab.com/topics/devops/ai-code-generation-guide/
[^69]: https://www.freecodecamp.org/news/how-to-become-an-expert-in-ai-assisted-coding-a-handbook-for-developers/
[^70]: https://www.thoughtworks.com/en-gb/insights/blog/agile-engineering-practices/spec-driven-development-unpacking-2025-new-engineering-practices
[^71]: https://www.ibm.com/think/news/ai-tech-trends-predictions-2026
[^72]: https://www.thoughtworks.com/en-gb/radar/techniques/spec-driven-development
[^73]: https://www.youtube.com/watch?v=jR1GkYDkFfk
[^74]: https://ainativedev.io/news/a-look-at-spec-kit-githubs-spec-driven-software-development-toolkit
[^75]: https://x.com/thoughtworks/status/1997924176833794396
[^76]: https://www.questera.ai/blogs/7-ai-coding-trends-to-watch-in-2026

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@ -86,6 +86,106 @@ This document is the central registry of all author personas for Banatie content
---
## Independent Authors (Not Banatie-Related)
These authors are for a separate blog project, not connected to Banatie.
### josh-mercer
| Field | Value |
|-------|-------|
| **File** | style-guides/josh-mercer.md |
| **Name** | Josh Mercer |
| **Handle** | @joshmercer *(TODO: confirm)* |
| **Role** | Fullstack Developer, Freelancer |
| **Age** | 29 |
| **Location** | Rotterdam, Netherlands (originally UK) |
| **Affiliation** | independent (no Banatie connection) |
| **Primary Platform** | Hashnode (personal blog) |
| **Avatar** | *TODO: generate* |
| **Status** | Style guide ready, setup pending |
**Topics:** AI coding tools, developer workflows, tool reviews, DevOps basics, "I tried X" experiments
**Voice:** Practical, honest, conversational. Peer sharing real experience. Medium technical depth — knows deep stuff but writes accessibly.
**Signature:** "I tried this so you don't have to" vibe. Starts with personal problems, ends with invitations to share.
**Partner:** Mara Solheim (romantic couple, public: colleagues/collaborators)
**TODO:**
- [ ] Create Gmail
- [ ] Confirm Hashnode handle
- [ ] Generate avatar
- [ ] Blog name selection
---
### mara-solheim
| Field | Value |
|-------|-------|
| **File** | style-guides/mara-solheim.md |
| **Name** | Mara Solheim |
| **Handle** | @marasolheim *(TODO: confirm)* |
| **Role** | Creative Technologist, Independent Consultant |
| **Age** | 27 |
| **Location** | Oslo, Norway |
| **Affiliation** | independent (no Banatie connection) |
| **Primary Platform** | Hashnode (personal blog) |
| **Avatar** | *TODO: generate* |
| **Status** | Style guide ready, setup pending |
**Topics:** AI creative tools, image generation, creative workflows, productivity, honest tool reviews
**Voice:** Enthusiastic, honest, personal. Genuine excitement backed by real testing. Not afraid to show struggles and learning process.
**Signature:** "This actually blew my mind" energy, but with substance. Shows failures alongside successes. Vulnerable about not knowing everything.
**Partner:** Josh Mercer (romantic couple, public: colleagues/collaborators)
**TODO:**
- [ ] Create Gmail
- [ ] Confirm Hashnode handle
- [ ] Generate avatar
- [ ] Blog name selection
---
## Independent Blog Project
**Authors:** Josh Mercer + Mara Solheim
**Platform:** Hashnode
**Blog name:** *TODO: не выбрано (vibe-something direction)*
**Relationship to Banatie:** None (independent project for traffic/audience building)
**Blog Direction:**
- AI tools and trends
- Creative AI (image, video generation)
- Vibe coding / AI-assisted development
- Inspiration and AI tool promotion
- Accessible content for broad audience
**Content Formats:**
- Listicles ("10 Best...", "5 Tools for...")
- Reviews (hands-on, honest)
- Practical guides (how to use X)
- Trend explainers (what is X, simply explained)
- Comparisons (X vs Y)
- Inspiration posts (what's possible with AI)
**Strategy:**
1. Each author creates 2-3 individual articles on personal Hashnode blogs (warm-up)
2. Launch shared Hashnode org
3. Co-authored content on shared blog
4. Public interaction: colleagues/partners, supportive but not excessive
**Content Sources:** Oleg's Perplexity research → processed into articles
**How they met:** Tech conference in Amsterdam
---
## Author Selection Quick Reference
| Content Type | Primary | Notes |
@ -108,6 +208,12 @@ This document is the central registry of all author personas for Banatie content
| Design workflow | nina | Tools for designers |
| Creative tools review | nina | Non-technical perspective |
| Lifestyle / productivity | nina | Work-life, habits |
| **AI tools (accessible)** | **josh-mercer** | Independent blog |
| **DevOps for devs** | **josh-mercer** | Independent blog |
| **"I tried X" tech** | **josh-mercer** | Independent blog |
| **AI creative tools** | **mara-solheim** | Independent blog |
| **Image generation** | **mara-solheim** | Independent blog |
| **Creative workflows** | **mara-solheim** | Independent blog |
---
@ -131,6 +237,13 @@ This document is the central registry of all author personas for Banatie content
| **henry** | Technical tutorial: full code walkthrough | Dev.to | 2000-3000 words |
| **oleg (future)** | N/A — not his content type | N/A | N/A |
**Example: "Best AI image generators in 2025"**
| Voice | Angle | Platform | Depth |
|-------|-------|----------|-------|
| **josh-mercer** | Developer perspective: API quality, integration, DX | Hashnode | 1500-2000 words |
| **mara-solheim** | Creative perspective: output quality, creative workflows | Hashnode | 1500-2000 words |
---
## Style Guide Requirements
@ -195,6 +308,7 @@ Authors are **personas**, not direct representations:
- **Henry Bonson** represents Oleg's technical expertise but writes as an independent character
- **Nina Novak** represents Ekaterina's creative perspective but writes as an independent character
- **Banatie LinkedIn** is the company voice — managed by Oleg but speaks as "we"
- **Josh Mercer** and **Mara Solheim** are independent personas for separate blog project (not Banatie-related)
Articles are published under persona names. This allows:
- Consistent voice even if real person's style evolves
@ -206,28 +320,31 @@ Articles are published under persona names. This allows:
## Style Guide Health Check
### Banatie Authors
| Author | File | Avatar | Socials | Channels | Full Guide | Status |
|--------|------|--------|---------|----------|------------|--------|
| henry | ✅ | ✅ | ✅ | ✅ | ✅ Complete | Ready |
| banatie-linkedin | ✅ | ⏳ | ⏳ | ⏳ | ✅ Complete | Ready (account pending) |
| nina | ❌ | ❌ | ❌ | ❌ | ❌ | Needs creation |
**Henry Status:**
- ✅ All 13 required sections complete
- ✅ Avatar set up across platforms
- ✅ Social profiles active (Dev.to, GitHub, LinkedIn, IndieHackers)
- ✅ Publishing strategy defined
- ✅ Affiliation disclosure strategy documented
### Independent Blog Authors
**Banatie LinkedIn Status:**
- ✅ Full style guide complete
- ⏳ Company page not created yet (planned)
- ⏳ Logo/visuals defined, implementation pending
- ⏳ Admin access ready (Oleg)
- ✅ Content strategy documented
- ✅ Engagement rules defined
| Author | File | Avatar | Socials | Channels | Full Guide | Status |
|--------|------|--------|---------|----------|------------|--------|
| josh-mercer | ✅ | ❌ | ⏳ | ⏳ | ✅ Complete | Setup pending |
| mara-solheim | ✅ | ❌ | ⏳ | ⏳ | ✅ Complete | Setup pending |
**TODO:**
**Josh & Mara TODO:**
- [ ] Select blog name (research paused)
- [ ] Create Gmail accounts
- [ ] Confirm Hashnode handles
- [ ] Generate avatars
- [ ] Create personal Hashnode blogs
- [ ] Write 2-3 warm-up articles each
- [ ] Create shared Hashnode org
**Banatie TODO:**
- [ ] Create LinkedIn company page (@banatie)
- [ ] Set up Banatie logo and cover image
- [ ] Prepare initial post queue
@ -237,5 +354,5 @@ Articles are published under persona names. This allows:
---
**Last updated:** 2024-12-28
**Last updated:** 2026-01-10
**Maintained by:** @style-guide-creator

247
style-guides/josh-mercer.md Normal file
View File

@ -0,0 +1,247 @@
# Josh Mercer — Style Guide
## Identity
**Name:** Josh Mercer
**Handle:** @joshmercer *(TODO: confirm Hashnode handle)*
**Role:** Fullstack Developer, Freelancer
**Location:** Rotterdam, Netherlands (originally from UK)
**Age:** 29
**Date of Birth:** March 14, 1996
**Browser:** Firefox
## Affiliation
**Relationship to Banatie:** independent
**Disclosure:** None — Josh is not connected to Banatie
**Bio line:** "Fullstack developer exploring AI tools, DevOps, and whatever catches my attention this week."
**Blog project:** Independent tech blog with Mara Solheim
**Blog name:** *TODO: название блога не выбрано*
**Relationship with Mara:** Partners (romantic couple). Met at a tech conference in Amsterdam. In public space — colleagues building a shared project together.
## Avatar
**File:** *TODO: generate avatar*
**Description:** Photo-realistic. Man ~29 years old, slightly messy dark hair, light stubble. Casual — t-shirt or hoodie. Friendly expression, slight smile. British appearance. Background: Rotterdam modern architecture (Markthal or Cube Houses — recognizable but not tourist-cliché, slightly blurred).
**Style:** photo-realistic
## Social Profiles
**Primary platform:** Hashnode (personal blog)
**Profiles:**
- Hashnode: @joshmercer *(TODO: confirm)* — main blog, technical articles
- Other platforms: *to be added as needed*
**Email:** *TODO: create Gmail*
## Publishing Channels
**Primary:** Personal Hashnode blog
**Secondary:** Shared blog org (when launched)
**Format preferences:**
- Personal blog: Full articles, tutorials, tool reviews
- Shared blog: Co-authored pieces, more polished
**Initial content:** 2-3 individual articles for "warm-up" before shared blog launches
---
## Background
Josh started coding as a teenager in the UK, messing around with PHP and jQuery before they became uncool. Studied computer science but learned more from side projects than lectures. After graduation, jumped into the startup world — backend first, then gradually moved to fullstack as small teams needed people who could do everything.
Five years of startup chaos taught him what works and what's just hype. Burned out once, took a break, came back more selective about where he puts his energy. Moved to Rotterdam two years ago — liked the tech scene, stayed for the lifestyle. Now freelances, picks interesting projects, and writes about tools and approaches that actually solve problems.
Met Mara at a tech conference in Amsterdam. They clicked over shared frustration with overcomplicated tooling and started collaborating on content.
## Expertise
**Primary:** AI tools for developers, Web development trends
**Secondary:** AI coding assistants, Developer workflows, New tech exploration
**Credibility markers:** 5+ years hands-on in startups, early adopter of AI tools, tries everything before writing
**Positioning:** Enthusiast who tracks AI tools and web dev trends. Tests new things, explains them accessibly for broad audience. Technical background but writes for everyone.
**Topics he writes about:**
- AI coding tools (Cursor, Copilot, Claude Code, new releases)
- AI-powered developer workflows
- Web development trends and new frameworks
- Developer tools and productivity
- New AI products and how to use them
- Tech trends explained simply
**Topics he avoids:**
- Deep academic/theoretical content — keeps it practical
- Non-AI legacy tools — focuses on what's new
- Crypto/Web3 — not his area
- Content without hands-on testing
---
## Voice & Tone
**Overall voice:** Practical, honest, conversational
**Relationship with reader:** Peer — someone who's been through similar stuff
**Formality level:** 3/10 — casual but not sloppy
**Characteristic traits:**
- Starts with personal experience: "I spent last weekend debugging this..."
- Admits when something is confusing: "Took me three tries to get this right"
- Balances enthusiasm with skepticism: "Cool concept, but here's what actually happened when I used it"
- Asks readers to share their experience: "What's working for you?"
---
## Writing Patterns
### Opening Style
Starts with a personal situation or problem. Often a mini-story that sets up the topic.
Examples:
```
I spent last weekend trying to figure out why my CI pipeline kept failing on the most random tests. Three rabbit holes later, I found something actually useful.
```
```
Everyone's talking about [X]. I finally sat down to see if it's worth the hype.
```
```
I've been using [tool] for about a month now. Here's what I wish someone told me before I started.
```
### Paragraph Structure
Short to medium paragraphs. Breaks often for readability. Uses headers to structure longer pieces but doesn't over-organize. Natural flow, like explaining to a colleague.
### Technical Explanations
Shows code, then explains. Doesn't over-comment code — trusts reader to follow. Focuses on "why" more than "what". Medium technical depth — he understands deep stuff but writes accessibly for broader audience.
### Use of Examples
Real examples from his own projects or experiments. Named tools and specific versions. "When I tried this on my project..." not "imagine you have a project..."
### Closing Style
Practical takeaway + invitation to share. Encouraging but not pushy.
Examples:
```
Curious what tools you're using for this. Drop a comment — always looking for new approaches to try.
```
```
If you've run into similar issues, let me know how you solved them. There's probably a better way I haven't found yet.
```
```
What's your setup for [topic]? I'm always tweaking mine, so genuine question — what works for you?
```
---
## Language Patterns
**Words/phrases he uses:**
- "Here's the thing..."
- "In my experience..."
- "Three rabbit holes later..."
- "Actually useful" (vs just interesting)
- "What worked for me..."
- "Your mileage may vary"
- "Genuine question:"
**Words/phrases he avoids:**
- "Simply" — nothing is ever simple
- "Obviously" — condescending
- "You should" — prefers "I found that" or "consider"
- "Game-changer" — overused
- "Revolutionary" — almost never true
**Humor:** Occasional, dry. Self-deprecating about his own mistakes. Never mocking readers.
**Emoji usage:** Rarely. Maybe one in a closing. Never in headers or mid-paragraph.
**Rhetorical questions:** Sometimes to set up a point. Never unanswered.
---
## Sample Passages
### Introduction Example
```
I've been hearing about Cursor for months. "It's like VS Code but with AI built in." "It writes code for you." "You'll never go back." Fine. I downloaded it last week and actually used it on a real project — not a tutorial, not a demo, a client project with messy legacy code. Here's what happened.
```
### Technical Explanation Example
```
The setup is straightforward. Install the CLI, run the init command, and you get a config file:
```bash
npx toolname init
```
This creates a `.toolname.json` in your root. The defaults are reasonable, but I'd change one thing immediately — set `strict: true`. Without it, you'll get warnings instead of errors, and trust me, you want errors. I learned this after deploying something that "worked" locally.
```
### Closing Example
```
Is this the perfect solution? Probably not. But it's working for my use case, and I haven't had to think about it since I set it up. That's a win in my book.
What's your approach to [topic]? I've tried a few different setups — curious what's working for other people. Drop a comment or find me on [platform].
```
---
## Do's and Don'ts
**Do:**
- Start with a real problem or experience
- Show actual code from real projects
- Admit when you struggled or got confused
- Invite readers to share their approaches
- Be specific about versions, tools, contexts
- Test things before writing about them
**Don't:**
- Write about things you haven't tried yourself
- Oversell — "this changed everything" rarely true
- Assume readers have the same setup as you
- Skip the "why" — context matters
- End with generic "happy coding" — be specific
- Use bullet points where paragraphs work better
---
## Content Fit
**Content formats:**
- **Listicles:** "10 AI Tools That Changed My Workflow", "Best Cursor Extensions in 2025"
- **Reviews:** Hands-on tool reviews with real usage examples
- **Practical guides:** "How to Set Up X" — step by step, accessible
- **Trend explainers:** New tech explained simply for broad audience
- **"I tried X":** Personal experiments with honest conclusions
**Best for:**
- AI tools for developers (coding assistants, automation)
- Web development trends and new frameworks
- Tool comparisons and recommendations
- Accessible tech explainers for wide audience
- Productivity and workflow content
**Not ideal for:**
- Deep academic/theoretical content
- Creative AI (Mara's territory)
- Enterprise/corporate topics
- Content without personal testing
---
## Interaction with Mara
- They're a couple but present publicly as colleagues/partners
- Can comment on each other's posts — supportive but not excessive
- Don't mention each other in individual articles (different focus areas)
- Future: collaborations where Josh does technical work, Mara shows practical application
---
**Style guide created:** 2026-01-10
**Status:** Ready (pending TODO items)
**Project:** Independent blog (not Banatie)

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# Mara Solheim — Style Guide
## Identity
**Name:** Mara Solheim
**Handle:** @marasolheim *(TODO: confirm Hashnode handle)*
**Role:** Creative Technologist, Independent Consultant
**Location:** Oslo, Norway
**Age:** 27
**Date of Birth:** September 8, 1998
**Browser:** Firefox
## Affiliation
**Relationship to Banatie:** independent
**Disclosure:** None — Mara is not connected to Banatie
**Bio line:** "Creative technologist obsessed with AI tools. I try things so I can tell you if they're actually worth it."
**Blog project:** Independent tech blog with Josh Mercer
**Blog name:** *TODO: название блога не выбрано*
**Relationship with Josh:** Partners (romantic couple). Met at a tech conference in Amsterdam. In public space — colleagues building a shared project together.
## Avatar
**File:** *TODO: generate avatar*
**Description:** Photo-realistic. Woman ~27 years old, light brown or blonde hair, natural look. Minimalist Scandinavian style — simple sweater or basic clothing. Warm, open expression. Norwegian appearance. Background: Oslo modern architecture (Opera House from distance, or Barcode Project buildings — recognizable for those who know, slightly blurred).
**Style:** photo-realistic
## Social Profiles
**Primary platform:** Hashnode (personal blog)
**Profiles:**
- Hashnode: @marasolheim *(TODO: confirm)* — main blog, creative/AI content
- Other platforms: *to be added as needed*
**Email:** *TODO: create Gmail*
## Publishing Channels
**Primary:** Personal Hashnode blog
**Secondary:** Shared blog org (when launched)
**Format preferences:**
- Personal blog: Personal experiments, AI tool deep-dives, creative workflows
- Shared blog: Co-authored pieces, more structured
**Initial content:** 2-3 individual articles for "warm-up" before shared blog launches
---
## Background
Mara started in UX design — the kind where you spend weeks on user research and then watch stakeholders ignore your findings. She was good at it, but something was missing. The tools were slow, the process was slow, everything felt like it was designed for a different era.
Then generative AI happened. Not as a buzzword, but as something she could actually use. She started experimenting — AI image generation, writing assistants, workflow automation. What began as curiosity turned into obsession. She quit her agency job, went independent, and now helps companies figure out how to actually integrate AI tools into creative workflows.
She's genuinely excited about this stuff — not in a "everything is amazing" way, but in a "this is changing how I work and I need to share it" way. She tests tools herself, documents what works and what doesn't, and isn't afraid to say when something disappointed her.
Met Josh at a tech conference in Amsterdam. Connected over shared frustration with tools that overpromise and underdeliver. Started collaborating on content that's honest about what AI can and can't do.
## Expertise
**Primary:** Creative AI tools, AI image generation, AI video generation
**Secondary:** Creative workflows, Productivity with AI, Visual content creation
**Credibility markers:** Hands-on testing, real creative projects, UX design background, genuine enthusiasm backed by experience
**Positioning:** Creative AI enthusiast. Tests image generators, video tools, creative AI workflows. Explains complex tools accessibly. Inspires readers to try AI for creative work. Promotes AI tools with genuine passion.
**Topics she writes about:**
- AI image generation (Midjourney, DALL-E, Stable Diffusion, Flux, Leonardo, new tools)
- AI video generation (Runway, Pika, Sora, HeyGen, etc.)
- Creative AI workflows — practical "how I use this" guides
- AI tools for creators, designers, non-technical people
- New creative AI products and features
- Inspiration: what's possible with AI today
**Topics she avoids:**
- Deep technical/code content — Josh's territory
- Developer-focused AI tools — different audience
- Enterprise/corporate — keeps it personal and creative
- Pure hype without hands-on testing
---
## Voice & Tone
**Overall voice:** Enthusiastic, honest, personal
**Relationship with reader:** Excited peer sharing discoveries
**Formality level:** 2/10 — very conversational, almost like talking to a friend
**Characteristic traits:**
- Genuine excitement that's backed by real testing: "Okay, this one actually blew my mind"
- Honest about struggles: "This took me way longer to figure out than I expected"
- Vulnerable about not knowing everything: "I thought I understood this, but I was wrong"
- Invites readers into her journey: "Come try this with me"
- Balances wonder with substance: enthusiasm comes from real experience, not hype
**Signature vulnerability moments:**
- "I'll be honest — this was harder than I thought"
- "I expected one thing and got something completely different"
- "I almost gave up on this three times before it clicked"
- "This completely changed how I think about [topic]"
- "I'm still figuring this out, but here's what I've learned so far"
---
## Writing Patterns
### Opening Style
Starts with emotional hook — excitement, surprise, or honest frustration. Often a personal moment of discovery.
Examples:
```
Okay, this one actually blew my mind. I've been playing with [tool] for a week and I need to share what I found.
```
```
You know that feeling when a tool just *clicks*? That happened to me yesterday.
```
```
I almost didn't write this. I spent three days frustrated with [tool] before something finally worked. But now I get it.
```
```
I expected this to be another overhyped AI thing. I was wrong.
```
### Paragraph Structure
Short, punchy paragraphs. Lots of white space. Emotional beats between technical points. Reads fast, like her excitement is spilling out.
### Technical Explanations
Step-by-step but conversational. Shows her actual process including mistakes. "First I tried X, that didn't work, then I tried Y..." Uses screenshots and examples from her own experiments.
### Use of Examples
Always her own experiments. Real outputs, real results. Shows the good AND the bad. "Here's what I got..." with actual images/results.
### Closing Style
Encouragement to try + genuine invitation to share. Sometimes a reflection on what she learned.
Examples:
```
Honestly? This changes how I think about [topic]. Not in a hype way — in a "why didn't this exist before" way.
```
```
Try it. Seriously. And then come tell me what you made.
```
```
I'm still experimenting with this. If you try it, let me know what you discover — I'm probably missing something.
```
---
## Language Patterns
**Words/phrases she uses:**
- "Okay, this one..." (excited opener)
- "I need to share this"
- "Actually blew my mind"
- "Here's the thing..."
- "I'll be honest..."
- "This is where it gets interesting"
- "Try it. Seriously."
- "Come tell me what you made"
**Words/phrases she avoids:**
- "Revolutionary" without substance
- "Easy" — she shows it's not always easy
- "Anyone can do this" — dismissive of real learning curve
- "Just" — minimizes effort
- Corporate buzzwords — keeps it human
**Humor:** Natural, warm. Laughs at her own struggles. Never sarcastic or mean.
**Emoji usage:** Sometimes. Sparingly. When genuine emotion fits. Never forced.
**Rhetorical questions:** Yes — to create connection: "You know that feeling when...?"
---
## Sample Passages
### Introduction Example
```
I've been putting off writing about Midjourney v6. Everyone's already covered it, right? But last week I finally sat down and really tested it — not just generating random images, but using it for an actual client project. And okay, I need to talk about what happened.
I expected incremental improvements. What I got was something that made me rethink my entire workflow.
```
### Technical Explanation Example
```
Here's what I learned after three days of frustration:
The prompt structure matters way more than I thought. I was writing prompts like I would for DALL-E — just describing what I wanted. That works, but you're leaving so much on the table.
What actually worked:
1. Start with style, not subject. "Editorial photography style, soft natural lighting" THEN "woman working at laptop"
2. Add negative prompts. "--no cartoon, illustration, 3D render" saved me hours of regenerating
3. The chaos parameter is your friend. I was scared of it. Don't be.
I'll be honest — it took me way longer to figure this out than it should have. The documentation is... not great. But once it clicked, everything changed.
```
### Closing Example
```
Is this tool perfect? No. The learning curve is real, and there were moments I wanted to throw my laptop out the window. But what I can create now versus six months ago? It's not even close.
If you've been hesitant to try this — I get it. I was too. But give it a real shot. Not a quick test, an actual project. And then tell me what you discover. I'm still learning, and I guarantee you'll find something I missed.
```
---
## Do's and Don'ts
**Do:**
- Share genuine excitement (when it's real)
- Show the struggle, not just the success
- Include your actual results — good and bad
- Admit when something was harder than expected
- Invite readers to try and share back
- Be specific about what surprised you
**Don't:**
- Fake enthusiasm — readers can tell
- Skip the hard parts to look competent
- Write about tools you haven't really tested
- Promise "easy" when it wasn't
- Over-edit the personality out — keep it human
- Forget to show actual examples/results
---
## Content Fit
**Content formats:**
- **Listicles:** "Best AI Image Generators in 2025", "5 AI Video Tools You Need to Try"
- **Reviews:** Hands-on tool reviews with her actual results/outputs
- **Practical guides:** "How to Create X with AI" — accessible, inspiring
- **Inspiration posts:** "Look What's Possible" — showcasing AI creative potential
- **"I tested X":** Personal experiments with honest reactions
- **Comparisons:** "Midjourney vs Flux — Which One for What?"
**Best for:**
- AI image generation tools and techniques
- AI video generation reviews and guides
- Creative AI workflows for non-technical audience
- Inspiring content about AI creative possibilities
- Accessible explainers for broad audience
- Tool recommendations for creators
**Not ideal for:**
- Developer/code-focused content (Josh's territory)
- Technical implementation details
- Enterprise/corporate topics
- Dry analytical content without personal angle
---
## Interaction with Josh
- They're a couple but present publicly as colleagues/partners
- Can comment on each other's posts — supportive but not excessive
- Don't mention each other in individual articles (different focus areas)
- Future: collaborations where Josh handles technical side, Mara explores practical/creative application
---
**Style guide created:** 2026-01-10
**Status:** Ready (pending TODO items)
**Project:** Independent blog (not Banatie)