common-session-retrospective

To analyze conversation corrections for AI agent skill gaps, you run a session retrospective on recent session data to detect correction loops and identify specific areas where the agent requires improvement.

Yes, you can automatically improve the skills library by applying session review analysis, which detects skill gaps from conversation corrections and suggests targeted enhancements to update the AI agent's capabilities.

Session retrospective in AI agent training is the process of reviewing conversation corrections to detect skill gaps, identifying correction loops, and suggesting improvements to enhance the overall skills library.

Yes, you need access to session data and the ability to modify the skills library to run a session retrospective, as the analysis relies on reviewing conversation corrections to detect and resolve skill gaps.

You should run a session review to detect AI agent skill gaps after a conversation session that involves user corrections or requests for rework, allowing you to identify correction loops and suggest library improvements.