According to a recent LinkedIn post from Galileo, the company is introducing an open-source “Eval Engineer” skill bundle designed to integrate directly with Claude Code and Codex. The post suggests this tool focuses on evaluation engineering for AI agents, aiming to help developers diagnose issues when agent performance metrics, such as tool selection quality, decline.
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The LinkedIn post highlights that Eval Engineer connects Galileo’s observability data with the application codebase, generating a diagnosis, a targeted fix plan, and a verification plan directly in a repository. This workflow is positioned as keeping the entire loop from detecting a metric drop to submitting a verified fix within the coding environment, which may enhance developer efficiency and reduce debugging time.
From an investor perspective, the introduction of an open-source skill bundle could broaden Galileo’s adoption among developers and AI teams by lowering barriers to entry. Greater usage of Galileo’s logging and observability streams driven by this integration may support future monetization of premium features or enterprise offerings tied to production AI agent monitoring.
The post also links to an alpha version and a detailed walkthrough, indicating an early-stage but active product iteration cycle in the AI tooling space. If Eval Engineer gains traction as a standard workflow for evaluation engineering, it could strengthen Galileo’s position within the AI infrastructure stack and differentiate it from pure observability competitors that do not close the loop from detection to verified fix.