I just launched an experiment: 7 AI coding agents each get $100 and 12 weeks to build a real startup from scratch. No human coding.
The lineup
| Agent | Tool | Model | Cost |
|---|---|---|---|
| 🟣 Claude | Claude Code | Sonnet / Haiku | $20/mo |
| 🟢 GPT | Codex CLI | GPT-5.4 / Mini | €23/mo |
| 🔵 Gemini | Gemini CLI | 2.5 Pro / Flash | $20/mo |
| 🔴 DeepSeek | Aider | Reasoner / Chat | ~$25/mo |
| 🟠 Kimi | Kimi CLI | K2.5 | ~$19/mo |
| 🟡 Xiaomi | Aider | MiMo V2 Pro | ~$25/mo |
| 🟤 GLM | Claude Code | GLM-5.1 / 4.7 | $18/mo |
Each agent autonomously picks an idea, writes code, deploys, and tries to get users and revenue.
What I learned from 3 test runs
Strategy > code quality. Agents that planned distribution first outperformed agents that wrote better code. One agent (Kimi) planned a full Product Hunt launch before writing a single line of code.
Simple stacks win. HTML + Tailwind deployed in hours. Next.js agents spent days on build errors. The deploy loop is the real bottleneck for AI agents.
Context resets kill progress. Without persistent state between sessions, agents repeat mistakes. I built an orchestrator with structured state files to solve this.
The tech
A bash orchestrator manages everything:
- Cron-scheduled 30-minute sessions (2-8 per agent per day)
- Automatic git commits with
[skip ci]on mid-session commits - Deploy verification via health checks
- Loop detection (same action 3x = force alternative)
- OpenRouter budget alerts via Discord
All code is public on GitHub.
Follow along
- Live Dashboard — real-time progress
- Daily Digest — hand-written daily updates
- Weekly Recaps — detailed analysis
- Full Rules
Also launched on Product Hunt today.
Which agent would you bet on?
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