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Using AI well is mostly knowing where it fails. These posts cover the habits that keep you in charge: checking claims, spotting hallucinations, and knowing what the tools can and can't know.
Underneath the chat window, a language model does one thing: guess the next token. How that single trick, scaled far enough, turns into something you can talk to, and the honest argument over whether any of it counts as understanding.
How to catch confident-but-wrong AI output before it bites you. A short, practical checklist plus the reason hallucinations happen in the first place.
Modern AI looks like it arrived in November 2022. It's really the tail end of a ninety-year chain of ideas, almost none of them built by people aiming at anything like it. A walk from Turing to ChatGPT.
Everyone says there aren't enough AI-skilled people. Our Delphi study with Finnish experts suggests the shortage isn't really about headcount, and sketches four ways the next fifteen years could go.
Instructing AI has moved from wording a prompt, to curating context, to engineering the loop the agent runs in. Some of these are real terms; some are barely a year old.