Agent Factory: Autonomous System Builds AI Agents from Online Problem Discussions

Agent Factory is an autonomous system that builds AI agents by identifying real-world problems from online discussions. Inspired by Andrej Karpathy's autoresearch pattern, it applies the same "run experiments overnight, keep what works, throw away what doesn't" approach to idea generation rather than ML optimization.

How It Works

The system scrapes Reddit, Hacker News, GitHub, and Twitter for real problems people discuss online. It scores each potential idea on three criteria: demand, market gap, and feasibility. If an idea clears a quality threshold, the system automatically builds a standalone AI agent, validates it works, and commits it. The threshold ratchets up with each build, requiring progressively better ideas.

Practical Implementation

The project consists of three key files:

• program.md - Tells Claude Code where to research and what quality bar to hit
• seed/ - A minimal Next.js template with 7 tools
• run.sh - Launches Claude Code headless and auto-restarts on context limits

The system is built with TypeScript, uses MIT licensing, and runs on either OpenRouter or Ollama. It specifically avoids LangChain and CrewAI frameworks. Each generated agent is standalone and can be cloned and run independently.

Example Output

In its first session, the system generated 20 agents including:

• freelancer-deduction-finder - For freelancers asking about missed tax deductions
• wage-rights-advisor - For people confused about overtime exemptions
• data-broker-opt-out - For people overwhelmed by data broker opt-outs

Quality Verification

The system boots each agent, sends a test prompt, and checks if the output is useful. However, the creator acknowledges these are MVPs and some are rough. The primary purpose is idea generation - the creator reviews the shipped agents each morning and selects the most promising one for further development as a real project.