If you are asking for human attention, demonstrate human effort
Points and comments are a snapshot, not live.
When sharing AI-generated work with teammates, label it clearly and add human commentary to show respect for their attention.
The author argues that as AI generates increasing amounts of code, documentation, and analysis, teams face a new etiquette question: when is it appropriate to send AI output to colleagues. The core principle offered is that requesting human attention demands demonstration of human effort. The author describes a past experience where a teammate sent AI-generated criticism without reading it themselves, then asks why the recipient should read something the sender deemed not worth their time. The recommendation is to clearly label AI-generated content, add personal commentary alongside it, and always review AI code before requesting review from others. This respects scarce attention and maintains humanity in collaborative work.
What commenters are saying
Commenters split on whether the issue is AI quality or human effort. Some argue AI often produces poor output and that labeling doesn't fix fundamental quality problems. Others contend the real problem is verbosity and lack of concision, noting that AI text tends to be lengthy and repetitive regardless of source, and that people should focus on brevity whether using AI or not. A strong thread argues that effort itself is not the measure of respect; usefulness to the recipient is what matters. Several commenters note that receiving unlabeled AI text is obvious anyway after reading it repeatedly. One comment flags that cheap models can hallucinate quotes and figures, requiring validation. There is broad agreement that the core issue is cognitive load and wasted time, not necessarily effort expended by the sender.