mastering-ai-observability-workshop

Improve any Braintrust-instrumented agent by turning production traces into an offline eval loop: mine bad traces, build a failure taxonomy, capture cases in a remote Braintrust dataset, write scorers and an eval file, iterate on prompts/tools, and only then push online scorers. Use when the user wants to write evals for their agent, fix recurring production failures, or set up an auto-improvement loop for an LLM app.