Practical AI skills for people whose job isn't AI. Most posts end with a drill, because reading about a skill isn't having one.
OpenAI and Google shipped always-on agent platforms in the same week. Non-technical teams can now set up agents by describing workflows in plain English. The skill gap is no longer how to prompt — it's how to scope, delegate, and verify autonomous work.
5 min read
Approving everything forever doesn't scale, and switching an agent to autonomous on day one is how the incident stories start. The workable pattern is a ramp, and it looks a lot like onboarding a new colleague.
5 min read
There are now two populations in every organisation: people whose understanding of AI is current, and people whose mental model is 12–18 months out of date. They're making decisions together. Andrej Karpathy named the problem this week. Here's how to tell which side you're on — and what to do about it.
6 min read
Sullivan & Cromwell apologized to a federal judge after a court filing contained 42 AI-generated errors: fabricated citations, misquoted statutes, authorities that don't exist. The opposing firm caught them. Here's what that means for anyone using AI for research, reports, or client-facing work.
5 min read
When Anthropic updated Claude to Opus 4.7, real-world token usage jumped roughly 40% — with no pricing announcement. Here's what that means for any team running AI workflows at any scale.
5 min read
AI drafts fast and defaults to generic. For anyone whose job is being heard, that's a real risk. Here's how to use it for speed without your writing converging on everyone else's.
5 min read
Anthropic launched Claude Design this week — AI that makes prototypes, pitch decks, and marketing assets through conversation. Whether the output is useful depends entirely on the brief you write.
4 min read
Atlassian will start training AI on Jira and Confluence data in August 2026. Most plans are opted in by default. Here's what that means for your team and what to actually do about it.
4 min read
Stanford's 2026 AI Index found AI still fails roughly 40% of real workplace tasks. That number isn't a reason to use AI less — it's why the person who can catch those failures is worth more than the one who just generates output.
5 min read
Practical AI skills, sent when there's something genuinely useful to share. No filler, no hype.
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