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Build auditable self-evolving workflows and iteration systems for AI agents.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "evolver" yet — see the docs or source repo.
Help me design a self-evolving workflow for a customer support AI agent using Genes, Capsules, and Events, including versioning, evaluation metrics, rollback strategy, and audit log structure.
A structured agent evolution plan covering core components, execution steps, evaluation methods, and audit mechanisms.
Write an evolution experiment specification for my coding assistant agent to improve bug-fix success rate. Define the hypothesis, event tracking fields, gene mutation strategy, control group setup, and success criteria.
An actionable experiment specification document ready for agent iteration testing and result comparison.
Create an auditable rollback strategy for an AI agent in production. When a new evolution cycle degrades performance, explain how to trace issues through events, revert Capsule versions, and preserve the full audit trail.
A clear rollback and audit plan covering triggers, investigation steps, recovery flow, and logging requirements.
Turn your codebase into an automated research loop for benchmark-driven optimization.
Optimize content for visibility across ChatGPT, Perplexity, Claude, and Gemini.
Keep AI coding agents architecture-aware, verified, drift-checked, and safer over long tasks.
Govern enterprise agent runtimes, skill assets, observability, and private distribution.
Enable AI agents to read, write, and evolve memory across apps.
Build a self-evolving memory graph for coding agents with semantic search.