Observability, Evaluation, and User Feedback Systems
~40 min read
How to make an AI system observable and improvable: structured traces, async evaluation, and extracting quality signals from explicit and implicit user feedback.
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Key points
- •A structured trace on every request is the foundation of observability — without it, you're flying blind when something breaks
- •Run evaluations asynchronously so they don't add latency to the response path
- •Implicit feedback (re-ask, copy-paste, session abandonment) gives higher volume than explicit ratings but is noisier — aggregate both and validate with human review