Stop Telling Me to Ask an LLM

Original Article ↗ Hacker News Discussion ↗

“Ask an LLM” as the new “Google it” / LMGTFY

  • Many see “ask Claude/ChatGPT” as the modern “Google it” or LMGTFY.
  • Often interpreted as a brush‑off, a polite “go away” or “not my problem,” especially when the asker has already done research.
  • Others argue it can simply mean “I’d have to look it up too, and an LLM is the same tool I’d use.”

Question quality and “proof of work”

  • Strong theme: you’re more likely to get real help if you show what you’ve already tried (options considered, docs read, LLM output evaluated).
  • Referring people to “ask an LLM” for very low‑effort questions is seen by some as entirely appropriate.
  • Several note that explicitly including “here’s what AI said and why I doubt it” is helpful context.

Human expertise vs AI‑mediated answers

  • Many askers want human judgment, not a second LLM pass over the same problem.
  • Frustration when coworkers just paste LLM responses into chats or PRs, with no sign of understanding.
  • Some reviewers feel reduced to “LLM rubber stamps,” reviewing code and comments largely generated by agents.

Workplace dynamics and mentoring

  • Seniors complain of constant interruptions and unrealistic expectations to mentor while still delivering their own work.
  • “Ask an LLM” is sometimes used as a boundary to protect focus time.
  • Others argue that if mentoring is expected, it should be explicit and compensated, not quietly offloaded to AI.

Reliability, misuse, and cost of correction

  • LLM hallucinations create “misinformation on the clock”; debunking them can be more expensive than answering a clean question.
  • Example: a PM shipping a metrics framework based on made‑up LLM code, forcing others to unwind the mess.
  • Concern that some users lack the expertise to distinguish good from bad AI answers.

Emotional and cultural impact

  • Being told “ask an LLM” can feel insulting: implies laziness, ignorance, or that human experience no longer matters.
  • Some see it as admitting one’s own replaceability or loss of confidence.
  • Others emphasize broader fatigue: layoffs, pressure, and burnout make deep, exploratory conversations feel like a luxury.

Knowledge ecosystem concerns

  • Fear that over‑reliance on LLMs plus layoffs of experts will erode real subject‑matter knowledge.
  • Worry that AI‑generated content and agentic workflows flood channels with low‑value material, while genuine expertise becomes rarer and harder to access.