FounderOS

Pitch agent giving out Pitch ideas for our startup
Idea agent grades our idea based on 4 factors - market, differentiation, revenue, and execution feasibility
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Inspiration

Everyone has startup ideas, but almost no one executes. The gap between an idea and a real product is massive. You need research, product design, pricing, branding, and a team before you can even begin. We built FounderOS to collapse that gap so one prompt can turn into a real, running startup.

What it does

FounderOS is a multi-agent AI system that takes a startup idea and produces a full venture plan across product, market, business, brand, and pitch, along with an honest idea score backed by a weighted formula. It generates a tailored founding team with assignable roles, produces real Week 1 deliverables such as code, copy, and specs, and ultimately builds a live, runnable MVP in the browser. Every step is human-in-the-loop, allowing users to approve, redirect, or modify outputs before moving forward.

How we built it

We built the system with a Node.js and Express backend that orchestrates multiple specialized agents through OpenClaw running in Docker. Each agent is defined with structured prompts and communicates through a unified API powered by Google Gemini 2.5 Pro. Results are streamed to a React frontend using Server-Sent Events so users can see outputs in real time. The final build phase synthesizes all agent outputs into a single self-contained web app served instantly in the browser.

Challenges we ran into

Getting agents to produce real work instead of describing work was a major challenge. We had to enforce strict prompt constraints to ensure outputs were actual code, copy, or deliverables. Keeping outputs realistic was also difficult, as models tend to exaggerate market sizes and funding. We introduced grounding rules and deterministic scoring to fix this. We also had to prevent impossible tasks and ensure all outputs could be created pre-launch. Finally, building a reliable streaming architecture across multiple long-running agent calls required careful backend and frontend coordination.

Accomplishments that we're proud of

We built a true end-to-end system that goes from a single idea to a working MVP. The system does not stop at planning but executes and produces real outputs. We created a structured multi-agent workflow that stays consistent across layers, and a scoring system that evaluates ideas honestly instead of overhyping them. Most importantly, we demonstrated that one prompt can become a real startup pipeline.

What we learned

Prompt engineering at both the system and call level is critical
Multi-agent systems are fragile at handoffs and require strong structure
Scores must be computed deterministically to be trustworthy
Execution is far more valuable than idea generation alone
Realism and constraints make AI outputs significantly more useful

What's next for FounderOS

We plan to deploy FounderOS to the cloud so users can access it without local setup. We want to improve the MVP builder to support more complex applications and real integrations. We also plan to add iterative feedback loops so users can continuously refine and evolve their startups. Long term, we aim to turn FounderOS into a platform where anyone can go from idea to company without needing a traditional founding team.