> Maybe you mentioned it in your demo and I missed it, but how does this differ pasting the log messages to ChatGPT / Claude / another LLM? Is it mainly that yours can iterate over a large logfile without blowing up the context window?
We do quite a bit of aggregation over the log file, and generate summary stats and choose what bits to stuff in the LLM. Plan to support more platforms than just spark.
> Does it suffer from the same issue as other LLMs, where it will always identify potential optimizations or improvements even if none are truly needed?
Funnily enough, instructing sonnet-3.7 to not suggest unnecessary optimisations seems to have done the trick!
We do quite a bit of aggregation over the log file, and generate summary stats and choose what bits to stuff in the LLM. Plan to support more platforms than just spark.
> Does it suffer from the same issue as other LLMs, where it will always identify potential optimizations or improvements even if none are truly needed?
Funnily enough, instructing sonnet-3.7 to not suggest unnecessary optimisations seems to have done the trick!