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evolving-ai-agents

Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation loops.

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# Evolving AI Agents with A-Evolve

## Overview

A-Evolve is universal infrastructure for evolving any AI agent across any domain using any evolution algorithm with zero manual engineering. It represents all evolvable agent state as files (prompts, skills, memory, tools), runs iterative solve-observe-evolve cycles against benchmarks, and uses LLM-driven mutation to improve agent performance automatically.

**Benchmark results** (Claude Opus 4.6):
- MCP-Atlas: 79.4% (#1)
- SWE-bench Verified: 76.8% (~#5)
- Terminal-Bench 2.0: 76.5% (~#7)
- SkillsBench: 34.9% (#2)

## When to Use A-Evolve