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Introducing self-improvement loops. The concept is simple: what if agents could improve Skills by reviewing past conversations? Here's the three step loop: - Score conversations from criteria you define - Isolate failures - Generate skill improvements

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Warp

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128,782 görüntüleme • 2 ay önce •via X (Twitter)

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Today, we're announcing content suggestions in Chatbase. Your agent can now self-improve by analyzing unresolved issues from past conversations, reviewing training data to surface conflicting information, then suggest improvements to fix any issues. Agents always fail in production unless they can learn from what went wrong. Missed answers, unresolved threads, and inconsistent knowledge. This is the missing layer that makes agents production-ready: continuous self-improvement.
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Today, we're announcing content suggestions in Chatbase. Your agent can now self-improve by analyzing unresolved issues from past conversations, reviewing training data to surface conflicting information, then suggest improvements to fix any issues. Agents always fail in production unless they can learn from what went wrong. Missed answers, unresolved threads, and inconsistent knowledge. This is the missing layer that makes agents production-ready: continuous self-improvement.

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3:28

Every skill file I write ends with a self-improvement loop. It sits at the bottom of the skill.md and runs before the skill finishes: - Did any step fail or need a workaround? - Did I correct or reject anything meaningful? - Did you discover something a future run might need? Most runs it comes back with one or two suggested edits. I say not needed, or I say run it, and it rewrites its own file. It never edits without asking first, so every change still goes through you. Put the loop at the bottom of the skills you already have and let them self-improve while you use them.

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