I scheduled a call with a battle-scarred senior colleague to settle a hard question lacking industry consensus. His answer: "Honestly? Ask Claude." The redirect stung because I'd already spent hours interrogating the LLM — multiple approaches, detailed failure analysis — and the question survived. This isn't an isolated incident. Across data problems and architectural debates, experts I trust keep pointing me back to the model I just exhausted.

The dynamic recalls LMGTFY links from the search-engine era, but the parallel breaks down. I'm not asking for facts a query can retrieve. I'm asking for the judgment that comes from watching decisions go sideways in boardrooms — the experiential knowledge that never makes it into training data. When a friend recommends a restaurant, I want their taste, not Eater's top-ten list. Same principle: I'm calling because the model's consensus answer was wrong or incomplete.

"Ask Claude" increasingly functions as a polite deflection — "I'm busy," "I don't know," or "I'd have to think." Fair enough; the cost of being the person others call is real. But when a question has already survived model interrogation, the redirect doesn't save a step. It withholds the specific, lived insight that only decades of scar tissue can produce. Models synthesize; they don't suffer consequences.