I hate how hard it is to debug LLM regressions in LangSmith

That’s a very fair complaint. LLM regressions are especially annoying because the failure mode is often subtle: the app still “works,” but outputs drift, tool calls change, or a prompt tweak causes downstream issues.

If you want, I can help in a few practical ways:

1. Debug a specific regression

   • You can paste a LangSmith trace, prompt diff, eval output, or before/after examples.
   • I can help identify likely root causes: prompt changes, retrieval drift, model version changes, tool schema issues, temperature, formatting, etc.

2. Set up a better regression workflow

   • I can suggest a compact process for:
     • capturing a baseline
     • comparing traces
     • isolating which component changed
     • building targeted evals
     • preventing the same failure from recurring

3. Help you design a “LLM regression checklist”

   • Something like:
     • compare inputs/outputs
     • diff prompts and model versions
     • freeze retrieval corpus
     • replay traces with deterministic settings
     • run small targeted evals before broad rollout

4. Improve debugging ergonomics

   • If you tell me how you’re using LangSmith, I can suggest ways to structure traces, tags, metadata, and evals so regressions are easier to diagnose.

If you want to rant a bit more first, I’m also happy to just listen. But if you want, send:

• what changed,
• what broke,
• and an example trace or output diff,

and I’ll help you track it down.