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Tonyleft a comment
We launched "Agent Prompt Optimizer" on PH three months ago. Since then we talked to hundreds of agent builders and realized prompt optimization alone isn't enough. The real pain is that your whole agent needs to improve: the prompts, the code, the routing logic, the tool usage. So we rebuilt everything around one loop: Kayba analyzes traces and finds failures. Your coding agent reads the...
KaybaMake your agents self‑improve from experience
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.
KaybaMake your agents self‑improve from experience
Tonyleft a comment
We built Agent Prompt Optimizer after talking to a lot of agent builders and seeing the same pattern everywhere: agents would make the same mistake over and over, and humans had to babysit them by tweaking prompts manually each time. So we asked: what if the agent could learn from these failures itself? Agent Prompt Optimizer watches agent runs, captures what worked vs what failed, and turns...
Agent Prompt Optimizer by KaybaAuto-optimize agent prompts from real failures.
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.
Agent Prompt Optimizer by KaybaAuto-optimize agent prompts from real failures.