Writing tutorials for a living means I spend a lot of time thinking about clarity and what actually helps someone understand a concept versus what just sounds helpful. Lately I keep running into this weird tension with AI tools.
On one hand, they speed up the grunt work. Boilerplate explanations, first drafts, restructuring a wall of text. Fine. But when I lean on them too much, the output has this flattened quality, like everything is technically correct but nobody is home. Readers notice. The comments section notices.
The bigger issue is that beginners are now using AI to learn from AIgenerated docs, and there's no human in that loop catching the subtle wrong turns. I've seen tutorials spreading an outdated pattern because some model confidently reproduced it from old training data, and new developers are just running with it.
What I keep wondering is whether the people building these models think about documentation quality as a real problem or just a content volume problem. Because those are completely different things and the solutions look nothing alike
Curious if anyone else writing technical content, or even just consuming it, has noticed the quality bar shifting in a weird direction lately. Not worse across the board, just... stranger
[link] [comments]