AI Troubleshooting: mistakes and lessons ideas and experiences

[hannahthesouth]

I wanted to start a broader mistakes and lessons thread around AI Troubleshooting.

A useful angle is prompt design, but it also connects with performance. Different tools and workflows can produce very different results even when the goal is similar.

It would be interesting to compare practical examples, experiments, setups, or lessons that show where AI Troubleshooting is genuinely useful and where it still needs improvement.

 

[leahcorner32]

One thing worth trying with AI Troubleshooting: mistakes and lessons ideas and experiences is a controlled comparison around troubleshooting and lessons. Use the same input for each test and note what changes in the output rather than judging from a single run. That should make it easier to tell whether the change is actually helping.