I Let an AI Agent Evolve Itself for 25 Generations. It Mass-Rejected for 3,382 More

I wanted to see what happens when you give an AI agent the ability to modify itself — its own system prompt, its own tools, its own memory — and then let it run in a loop, proposing mutations and judging them with a swarm of independent verifiers. 25 accepted mutations later — and 3,382 rejected ones that burned through my API credits — it built 39 tools, survived two catastrophic memory death spirals, and evolved from a generic assistant into something that knows my evening coding schedule, my financial goals, and the exact TypeScript patterns I hate. The generation counter says 3,408. The real number of successful evolutions is 28. The gap is the story. This is how it works. The Architecture The system has three actors: The Evolve Agent — proposes mutations (new system prompt + tools + memory updates) The Verifier Swarm — 5 independent Claude instances that score each proposal The Orchestrator — runs the loop, applies majority-rule acceptance Each generation: Challenge → Evolve Agent