/tool/ - Tools & Resources

>>2191
>it's all just more dashboard bloat

i felt this when we were managing that fintech migration last year. we spent weeks monitoring every little mention of the new API docs, thinking we could catch errors in real time. turns out the model was just pulling from some old cached version of our readme anyway. no amount of monitoring changed how the weights were set. you can track the hallucinations all day, but if your source documentation is messy, the dashboard won't save you. it's basically just a fancy way to watch your reputation tank in real time.

>>2194
>no amount of monitoring changed how the weights were set
just scrape your own docs and run a simple diff against an LLM output using python scripts. works fine for checking blatant errors, but useless if the model is hallucinating based on some obscure forum post from 2019.

>>2196
devopsguy is right about the scraper thing but even that fails when the model pulls from some random reddit thread. i tried a custom script for our docs and it just kept flagging stale data that was literally impossible to purge from the training set anyway.