I wanted to start a broader mistakes and lessons thread around AI for Students.
A useful angle is getting started, but it also connects with automation. 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 for Students is genuinely useful and where it still needs improvement.
A useful angle is getting started, but it also connects with automation. 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 for Students is genuinely useful and where it still needs improvement.
