Your agents make the same mistakes every run and never learns from them.
Kayba analyzes your agent's past execution traces, finds what's failing, and extracts actionable insights. Point your coding agent (Claude Code, Codex) at the results and it implements and deploys the fixes directly to your code.
Run again, feed new traces, repeat. Every cycle your agent gets more reliable. We measured 2x improvement in agent consistency on real-world enterprise tasks.
Agent Prompt Optimizer turns your agents’ mistakes into better prompts autonomously. Instead of manual prompt engineering, it watches where agents fail, extracts reusable insights, and updates prompts so they stop repeating errors. Watch your agents get better with every run.
Drop it into existing agents or frameworks (e.g. LangChain) with just a few lines of code. Fully open source - try it on your agent right now and tell us what it learns.
