Evolve
Whether you're building a RAG chatbot that answers questions from your own data or a customer service agent that performs complex tasks, accuracy, reliability, and performance are critical. However, LLMs are inherently unpredictable, and as agents grow more complex with additional tools, context, and instructions, maintaining consistent behavior becomes increasingly challenging. Even a small change to a system prompt can introduce unexpected failures or affect previously working scenarios. Evolve is an AI-powered agent evaluation and optimization platform built with Symfony AI and MCP that addresses this challenge by letting AI coding agents like Claude Code and Codex autonomously test, evaluate, and improve other AI agents. Developers can create an agent or provide an existing system prompt, configure tools, supply dynamic context and test scenarios, and define both hard constraints (such as mandatory tool calls or execution order) and soft evaluation criteria, where an LLM judge assesses the complete execution path, decision quality, and outcome. Developers can set optimization goals for accuracy, performance, and cost, including model-specific success targets. Coding agents then iteratively refine system prompts, execute tests, analyze detailed traces, and use independent AI judges to score results and recommend improvements, while checking for regressions. A comprehensive dashboard provides visibility into execution traces, evaluation scores, token usage, costs, and prompt version history, making it easy to compare iterations and identify the most effective configuration. By automating evaluation, regression testing, and prompt optimization, Evolve transforms agent development from trial and error into a measurable, repeatable process where AI agents continuously help improve other AI agents.