AI;DR (AI; Didn't Read)

That framing landed because many people are already dealing with it at work. The strongest pattern was engineers describing PRs, Jira tickets, Slack replies, release notes, and internal docs bloated with AI commentary that nobody actually reads. Features still ship, which is why this is spreading, but readability and accountability are collapsing. Several people described a new failure mode where coworkers cannot explain what they “wrote” without consulting ChatGPT in real time. The complaint was less “AI is fake” than “I am being forced to do first-pass validation on text the sender did not understand.” That is why the discussion kept circling back to ownership. Readers will tolerate AI help if a human clearly reviewed, compressed, and stands behind the result. A second theme was that AI writing has become recognizable not just because of stock phrases, but because it behaves like an expansion engine. It inflates a small idea into a large, plausible document with low information density. That makes it especially toxic in software teams, where generated comments and docs multiply faster than anyone can review them and then mislead later humans and agents reading the codebase. A few commenters are already responding with hard process limits like short comment caps, PR formatting rules, and automatic rejection of overly long AI-flavored text. The underlying lesson was blunt. Writing is now cheaper than reading, so any team that does not actively defend concision will drown in machine-made surplus prose. There was credible pushback, but it mostly narrowed the claim rather than overturning it. Some argued that obvious AI style is not the core issue. Bad human writing, ghostwriting, copywriting, templated influencer prose, and “link as argument” all predate LLMs. Others said the only real bar should be usefulness. If an AI-assisted tutorial or message is concise, accurate, and accountable, they do not care how it was produced. A few also warned that “AI;DR” is becoming a lazy accusation people throw at anything they dislike, and that false positives are rising as people start treating normal punctuation, polish, or structure as “AI tells.” Even so, the center of gravity stayed clear. Raw or lightly edited AI output is being treated as a tax on everyone else’s attention, and workplaces that do not draw boundaries are creating exactly the kind of low-trust communication systems people will stop reading.