I wanted to start a broader ideas worth trying thread around Large Language Models.
A useful angle is integration, but it also connects with setup choices. 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 integration, but it also connects with setup choices. 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.