collect-user-feedbacklisted

# Collect user feedback Your users are running the best eval you have, for free, every day. Capturing their reactions and attaching them to the trace turns production into a continuous source of labeled data. Most teams either skip this or collect it and never use it. ## Capture both explicit and implicit signals **Explicit** (ask directly): - Thumbs up/down on a response (the simplest, highest-signal control). - A short reason on thumbs-down (dropdown: wrong / unhelpful / unsafe / other). - Accept / edit / reject on a suggested output (great for copilot-style apps). **Implicit** (infer from behavior, no extra UI): - Did the user retry, rephrase, or immediately give up? (dissatisfaction). - Did they copy/use the output, or continue the task? (satisfaction). - Did a downstream action succeed (the code ran, the ticket resolved)? Implicit signals are noisier but you get them on 100% of traffic instead of the small % who click thumbs. ## Wire it to the trace (this is the key step) Attach every feedback signal to the **trace/span it is about** (by trace ID), with the user, timestamp, and the reason. Most observability platforms (Langfuse, Phoenix, Opik, LangSmith) have a feedback/scores API for exactly this. Without the trace link, feedback is a number with no context; with it, a thumbs-down is a fully debuggable example. ## Use it (do not just collect it) 1. **Monitor** feedback rate + thumbs-down rate over time; alert on spikes (see `set-up-drift-alerts`). 2. **Triage**