ShipFit
- Built to disagree. 24% of ideas get a Kill verdict against live data thresholds, not vibes
- Forced 9-stage sequential decision sequence. Each stage depends on the last
- Live competitor data with real URLs and prices sourced via search APIs at run time
- Customer signal pulled from G2 / Trustpilot / Reddit / App Store reviews, not generated by chat
- Named buyer personas with willingness-to-pay $ amounts, CAC and decision timeline
- Pricing architecture with Van Westendorp methodology, MVP scope with Lean / Balanced / Full packages
- Channel-specific launch playbook with conversion tracking, not a generic launch roadmap
- Exports to Cursor, Claude Code, Lovable, Replit, Windsurf, v0 and Gemini with tool-optimised prompts
- 55 named frameworks (Mom Test, Van Westendorp, Jobs-to-be-Done, 7 Powers, Blue Ocean) applied with scoring rubrics
- Not a chatbot. ShipFit is a structured 9-stage process, not a back-and-forth conversation
ValidatorAI
- Friendly chat interface and big community. 300,000+ founders have used Val, low barrier to start
- Bundles AI-generated landing page and a 14-step launch roadmap with the idea check
- Trained to be helpful. Default tone is encouraging. Rarely returns a 'stop building this' verdict
- No forced sequential decision process. Chat plus a roadmap, not nine decisions that depend on each other
- Frameworks referenced in chat, not applied systematically with scoring rubrics. No Mom Test / Van Westendorp / JTBD by name
- No buyer personas with explicit willingness-to-pay $ amounts or CAC numbers
- No MVP scope with Lean / Balanced / Full packaging or feature prioritisation
- No pricing architecture. Van Westendorp methodology and competitive pricing positioning not applied
- No exports to coding tools (Cursor, Claude Code, Lovable, Replit, Windsurf, v0, Gemini)
Val says yes. ShipFit says prove it.
Open ValidatorAI. Type an idea. Val will be friendly, helpful and almost certainly positive. Try this experiment: type a deliberately weak idea and see if it kills it. It won’t. It will find reasons to be encouraging.
That isn’t a bug. Val is a chat experience layered on a large language model with a startup-flavoured system prompt. Chat experiences are tuned for helpfulness, not honesty. The default behaviour of every LLM-based chatbot is to find the most agreeable version of an answer.
ShipFit is built the other way. The job is to disagree with you when the data says no. 24% of ideas that go through the full 9-stage sequence get a Kill verdict against live market data. Not vibes. Real competitor pricing, real complaint patterns, real opportunity scores.
9 decisions ValidatorAI doesn’t force
Val gives you a chat, a 0-100 score and a 14-step launch roadmap. ShipFit gives you 9 forced sequential decisions in a fixed order because 25 years of launching products taught the founder which decisions actually matter and in which order.
- Worth Building? Market verdict with real competitor URLs and prices
- Who Pays? Named buyer personas with willingness-to-pay $ amounts
- What Hurts? Pain points ranked by severity from real G2 / Trustpilot / Reddit data
- How to Win? Competitive positioning against real competitors
- What’s V1? MVP scope with Lean / Balanced / Full packages
- How to Charge? Pricing architecture with Van Westendorp methodology
- Will They Pay? Behavioural validation with landing page copy and traffic templates
- How to Launch? Channel-specific playbook with conversion metrics
- What to Export? Tool-optimised prompts for Cursor, Claude Code, Lovable, Replit, Windsurf, v0, Gemini
You can’t price before you’ve defined the buyer. You can’t scope the MVP before you’ve ranked the pain. That ordering is the product.
What you get. ShipFit vs ValidatorAI
| Capability | ShipFit | ValidatorAI |
|---|---|---|
| Forced 9-stage sequential decision process | ✅ | ❌ |
| Ship / Pivot / Kill verdict when the data says no | ✅ | ❌ |
| Live competitor URLs from search APIs at run time | ✅ | ❌ |
| Customer signal mined from G2 / Trustpilot / Reddit / App Store | ✅ | ❌ |
| Named buyer personas with willingness-to-pay $ amounts | ✅ | ❌ |
| Pain points ranked by severity and frequency from real reviews | ✅ | ❌ |
| Pricing architecture with Van Westendorp methodology | ✅ | ❌ |
| MVP scope with Lean / Balanced / Full packages | ✅ | ❌ |
| Channel-specific launch playbook with conversion metrics | ✅ | ❌ |
| Exports to Cursor, Claude Code, Lovable, Replit, Windsurf, v0, Gemini | ✅ | ❌ |
| 55 frameworks attributed by author with scoring rubrics | ✅ | ❌ |
| 24% Kill rate against live data | ✅ | ❌ |
| Source link on every claim | ✅ | ❌ |
| Reproducible: same idea, same data, same verdict | ✅ | ❌ |
The bottom line
Val is a friendly chat with a launch roadmap and a generated landing page. ShipFit is a forcing function with live data, Van Westendorp pricing, MVP packaging and a coding-tool export.
Most founders comparing the two have been “validating” with Val for weeks. The conversation feels productive. They still don’t have a buyer with a price, an MVP scope or a coding-tool prompt. That’s the pattern Val produces by design.
Spend $5 on ShipFit’s Quick Take. 2 minutes. Live data. Real verdict.
Frequently asked questions
Is ShipFit better than ValidatorAI?
Isn't ShipFit just a ChatGPT wrapper too?
What does ShipFit do that ValidatorAI doesn't?
Can I use ShipFit instead of ValidatorAI?
Keep exploring
The 9-step playbook from market verdict to ship-ready spec.
MoSCoW sorts features into Must, Should, Could and Won't against a fixed date. The 60% capacity rule is the part most teams drop, and dropping it breaks it.
Adele Revella's Five Rings of Buying Insight, the questions that produce each one, and why a persona built without buyer interviews informs no decision.
Most founders ship an MVP that's actually V1.3 with bugs. Real MVP scoping cuts ruthlessly until you can name the one hypothesis V1 proves, and ships a product that tests it.
Most early-stage competitive analysis is a 2x2 with your product in the top-right quadrant. The real version is harder, more boring, and tells you whether you can actually win.
Van Westendorp in 4 numbers. Skip the survey-platform fees.
Use the Jobs-to-be-Done switch format: 'When [situation], I want to [motivation], so I can [outcome].' Drawn from real buyer interviews, not your hypotheses. The statement should make a specific person feel a specific moment. Pass four tests: it names a real situation, the buyer can identify the moment, the outcome is measurable, and at least 3 unrelated buyers describe the same problem in similar words.
AI startup idea validation that tests for a real buyer and a moat, not a cool demo. ShipFit forces 9 decisions and flags thin-wrapper risk. Start free.
Claude Code is a brilliant coding tool that will say yes to almost any idea. ShipFit is a decision engine built to disagree with you when the data says no. Use ShipFit to decide what to build. Use Claude Code to build it.
Ready to make your next product a success?
9 decisions between your idea and a product worth building.