A Useful AI Answer Still Needs a Reality Check
This Short is a reminder I want to keep close to every AI experiment: a convincing answer can still be wrong.
A tool may fit neatly into a workflow and produce something that looks finished. That does not tell me whether it preserved the source, understood the request, or invented a missing detail.
I would make the review as concrete as the task. For a summary, compare it with the original. For a rewritten message, check names, dates, and meaning. For an action, inspect what will change before letting it happen.
Start with work where an error is easy to spot and correct. That makes the experiment useful even when the first attempt fails.
The goal is not to avoid trying AI. It is to learn where the tool helps while keeping a way to check its work.