I wanted to start a broader mistakes and lessons thread around Large Language Models.
A useful angle is creative uses, but it also connects with troubleshooting. 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 Large Language Models is genuinely useful and where it still needs improvement.
A useful angle is creative uses, but it also connects with troubleshooting. 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 Large Language Models is genuinely useful and where it still needs improvement.