Zero to One builder

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  Intro

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  User input form

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  Stage 1 - Clarify, AI asks some questions that can change the analysis

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  Stage 2 - Idea Analysis

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  Stage 3-I - Risk assessment

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  Stage 3-II - Overall confidence

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  Stage 3-III - Weighted evidence factors and Why confidence is limited and what are the limitations

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  Stage 4 - Multi-Perspective Debate Four viewpoints that don't have to agree with each other.

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  Stage 5-I - 3 Execution Paths & First experiment to do

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  Stage 5-II - Paths comparison

Inspiration

Most people with a good idea don't lack ambition — they lack structure. We kept seeing people spinning in circles: too vague to act, too early to hire a consultant. We wanted to build something that thinks with you, not for you.

What it does

Zero to One Builder is a guided 5-stage AI reasoning pipeline. You describe your idea, and the system walks you through:

1. Clarify — sharpens ambiguous ideas with targeted questions
2. Analysis — maps the problem, target user, value proposition, and resource gaps
3. Risk — surfaces the 4 key assumptions your idea depends on, with honest confidence scores
4. Perspectives — generates genuinely disagreeing viewpoints (Founder, Investor, Engineer, Customer)
5. Path — produces 3 execution paths with a weighted comparison and one first experiment to run

The user makes the final decision. The tool informs it.

How we built it

• React (Vite) for the frontend
• Groq API (llama-3.1-8b-instant) for fast structured reasoning
• All AI responses are structured JSON, validated and rendered as interactive UI components
• No backend database - stateless by design

Challenges we faced

Getting the model to produce genuinely specific outputs was the hardest part. Generic startup advice is easy; reasoning grounded in what the user actually typed is much harder. We spent significant effort on prompt engineering, especially the reasoning_steps field, which forces the model to explain why it landed on each score, not just what to do next. And one of the challenges we faced also, throughout the project is the UI, we had to make a lot of updates, change things so that every output is interpretable and can be easily understood by the user. We made sure everything is clear on what it means and what it does.

What we learned

That the UI is the product. The AI output is only as useful as the experience around it, the progressive disclosure, the honest framing, the explicit "this tool does not decide for you" language all matter as much as the model itself.

Built With

• css
• groq
• javascript
• llama-3.1-8b-instant
• react
• vite