•1 min read•from Machine Learning
when a run is wrong but nothing actually failed, where do you start? [D] [R]
this is the kinda debugging case i find rlly annoying/
everything says success.
no exceptions no failed tool calls. no obvious timeout the workflow completes but the final result is still wrong
when that happens, what’s your first move?
do you guys usually:
- start from the final output and work backward
- compare against a previous good run
- inspect state transitions
- check retrieval/tool behavior
- look at model inputs
- replay it
- check business state outside the trace
- just read the whole thing until something looks off
interested in what people actually do in production not the idealized version but thats fine too. and if you have anything you've built to help with this process I'd love to see it :)
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