Evaluating Agent Workflows with Traces, Feedback, Human Labels, and LLM Judges
A practical evaluation stack for agent systems: collect traces, use feedback to find pain points, add human labels, and apply LLM judges with calibration.
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A practical evaluation stack for agent systems: collect traces, use feedback to find pain points, add human labels, and apply LLM judges with calibration.
How to sandbox, gate, and instrument AI coding agents before giving them repo write access or a shell.
Production MCP needs more than protocol support: contract tests, capability policy, trust scoring, and hardened auth and session handling.
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