feat: update interview and tiers
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- 60%+ interviews say "I would use this" (6 out of 10)
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- 40%+ willing to pay $20+ (4 out of 10)
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- 30%+ want early access (3 out of 10)
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- Consistent pain point validated (not scattered)
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- **KILLER USE CASE identified:** ONE specific, frequent, expensive pain mentioned by 60%+ respondents (not scattered generic needs)
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- Budget confirmed (they pay for other tools)
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**Possible outcomes:**
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@ -196,18 +196,25 @@ Thanks for agreeing to chat! Here are the questions:
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6. Have you tried to automate this? What did you try? What worked/didn't work?
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7. **NEW:** Have you tried AI image APIs (fal.ai, Replicate, Together.ai, Gemini direct)?
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7. **Killer Use Case Discovery:**
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- When was the LAST TIME you spent more than 30 minutes on finding/generating/preparing images for a project?
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- Tell me about it in detail: What project? What image? Why did it take so long?
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- How often does this happen? (daily/weekly/monthly/rarely)
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- Roughly, what's your time worth per hour? (annual salary / 2000)
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- If this process took 5 minutes instead of 30+ - how much would you save per month?
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8. **NEW:** Have you tried AI image APIs (fal.ai, Replicate, Together.ai, Gemini direct)?
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- If yes: What was your experience? What did you like/dislike?
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- If no: Why not?
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8. If there was a tool that integrated image generation into your agentic workflow, which integration would you prefer:
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9. If there was a tool that integrated image generation into your agentic workflow, which integration would you prefer:
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- MCP (for Claude Code/Cursor)
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- CLI tool (terminal-based)
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- REST API (programmatic)
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- Prompt URLs (GET-based generation)
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- Other?
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9. What would you pay for a production-ready solution like that?
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10. What would you pay for a production-ready solution like that?
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- Options: $0 (only free tier), $10-20/month, $20-50/month, $50+/month
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- OR: One-time credit packs (e.g., $20 for 200 images, valid 90 days)?
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@ -596,6 +596,30 @@ Metadata: { included_credits: 500, overage_rate: 0.10 }
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---
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---
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## Alternative Approach: Single Tier Launch (For Consideration)
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Before launch, it's worth considering an alternative strategy: start with **one paid tier only** instead of three (Free, Credits, Pro).
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**Rationale for Banatie:**
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1. **Faster willingness-to-pay validation:** With a single paid tier ($49/mo for 500 generations), we immediately learn whether people are willing to pay for the solution. A Free tier can create an illusion of demand from users who will never convert.
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2. **Lower complexity in MVP:** One pricing tier means less code (no tier logic, no credit system, no watermark implementation), which is critical with limited time availability (15-20 hours per week).
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3. **Focus on the right customers:** A $49/month price point automatically filters out freebie seekers and attracts those who genuinely value solving their problem. These are exactly the customers whose feedback matters most for PMF.
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4. **Flexibility for evolution:** After 10-20 paying customers, we'll hear their real requests: "I need it cheaper" → add Credits tier, "I need more volume" → add Pro+ tier, "let me try for free" → add Free tier. Building based on actual demand is more reliable than building on hypotheses.
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5. **Reduced operational risk:** With a constrained budget ($6K/month sole income), every free user = Gemini API cost with no return. A single paid plan minimizes losses during the validation phase.
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**When to expand tiers:** After observing patterns in requests from the first 10-20 customers. If they ask for "cheaper for one-off projects" → add Credits. If they ask for "trial without commitment" → add Free tier. This is a data-driven approach instead of guesswork.
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**Decision:** Discuss after ICP validation completion. If the killer use case turns out to be "professional assets for client projects" → single paid tier is optimal. If the killer use case is "quick experiments for A/B testing" → Free tier might be justified for virality.
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---
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**Document owner:** @men (based on Oleg's feedback)
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**Next review:** After beta testing (Month 2-3)
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**Related docs:** `strategy/07-validated-icp-ai-developers.md`, `execution/09-mvp-scope.md`
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