Agent Prompt Optimizer by Kayba – Auto-optimize agent prompts from real failures

Summary: Agent Prompt Optimizer autonomously improves prompts by analyzing agent failures and extracting reusable insights to prevent repeated errors. It integrates easily with existing agents or frameworks like LangChain, enabling agents to learn from mistakes without manual intervention or fine-tuning.

What it does

It monitors agent runs, identifies failures, and updates prompts based on what worked versus what failed. This process refines prompts automatically to reduce recurring errors.

Who it's for

Agent builders seeking to reduce manual prompt engineering and improve agent performance through automated feedback loops.

Why it matters

It eliminates repetitive manual prompt adjustments by enabling agents to learn from their own mistakes and improve over time.