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We built meta-agent: an open-source library that automatically and continuously improves agent harnesses from production traces.Point it at an existing agent, a stream of unlabeled production traces, and a small labeled holdout set.An LLM judge scores unlabeled production traces as they stream.A proposer reads failed traces and writes one targeted harness update at a time, such as changes to prompts, hooks, tools, or subagents.
The update is kept only if it improves holdout accuracy.On tau-bench v3 airline, meta-agent improved holdout accuracy from 67% to 87%.We open-sourced meta-agent. It currently supports Claude Agent SDK, with more frameworks coming soon.Try it here: https://github.com/canvas-org/meta-agent
Show HN: Meta-agent: self-improving agent harnesses from live traces
An open-source library that 'automatically and continuously improves agent harnesses from production traces,' using an LLM judge and a proposer to iteratively refine prompts, hooks, tools, or subagents based on performance.
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An open-source library that 'automatically and continuously improves agent harnesses from production traces,' using an LLM judge and a proposer to iteratively refine prompts, hooks, tools, or subagents based on performance.
Meta-agent addresses a critical challenge in AI development: the continuous improvement and maintenance of agent performance in production. By automating the iterative refinement of 'agent harnesses' (prompts, hooks, tools) based on live 'production traces' and an 'LLM judge,' it significantly reduces the manual effort and expertise required for agent optimization. The demonstrated improvement in 'holdout accuracy' from 67% to 87% validates its effectiveness. This open-source library, supporting 'Claude Agent SDK,' positions itself as an essential tool for enterprises deploying and scaling AI agents, directly impacting operational efficiency and the reliability of AI-driven applications. It represents a key trend in MLOps for autonomous system improvement.
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What is Meta-agent: self-improving agent harnesses from live traces?
Meta-agent: self-improving agent harnesses from live traces is analyzed by our AI as: An open-source library that 'automatically and continuously improves agent harnesses from production traces,' using an LLM judge and a proposer to iteratively refine prompts, hooks, tools, or subagents based on performance.. It focuses on Meta-agent addresses a critical challenge in AI development: the continuous improvement and maintenance of agent performance in production. By auto...
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The initial public indexing or launch date for Meta-agent: self-improving agent harnesses from live traces within our tracked developer communities was recorded on April 7, 2026.
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Which technical categories define Meta-agent: self-improving agent harnesses from live traces?
Based on metadata extraction, Meta-agent: self-improving agent harnesses from live traces is categorized under topics such as: open-source library, self-improving agent harnesses, production traces, unlabeled production traces.
How does the creator describe Meta-agent: self-improving agent harnesses from live traces?
The original author or development team describes the product as follows: "We built meta-agent: an open-source library that automatically and continuously improves agent harnesses from production traces.Point it at an existing agent, a stream of unlabeled production trace..."
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