AI was great until it was not

Commenters spent less time on the article’s prose than on a harder question: what disappears when an LLM becomes the default first stop for answers. Many worry that agents replace the messy exchanges through which coworkers, students, and researchers learn each other’s reasoning. The cost is not merely social nicety; it is weaker mentorship, fewer accidental insights during routine work, and graduates who can produce results without owning the underlying concepts. Several readers see academia as especially exposed, since students may bypass supervisors while supervisors themselves redirect questions to AI. Others reject the idea that human help was a golden age. They recall colleagues who resented interruptions and argue that an always-available tutor can unblock curious learners far faster than university or workplace hierarchies. Experienced users describe LLMs as a force multiplier: they can finally prototype ideas that formerly died for lack of time or programming capacity. The emerging compromise is that AI works best as a complement for people who retain agency and foundational knowledge, not as an autopilot for the work that teaches them. Skeptics doubt most people can reliably distinguish disposable drudgery from the supposedly trivial tasks that later trigger understanding. A smaller group dismissed the article itself as self-indulgent and short on practical conclusions.