AI-adopting firms are growing headcount, not cutting it: A Goldman Sachs analysis circulating this week, charted by Callum Williams of The Economist, shows US firms that have adopted AI report net positive employment growth across the past six months. Finance, insurance, arts and entertainment sit at the positive end; transportation and food service show modest decreases; the all-industries balance is positive. Self-reported and narrow-window, but the direction matters. David reads it as Jevons playing out: AI-adopting firms grow because productivity gains expand what their people can do faster than they replace them. The risk is falling behind the firms whose people are using AI to scale.Five percent, not fifty: the candid private-equity number: Pete Stavros, co-head of global private equity at KKR, told the Milken Institute conference last week that AI is improving portfolio company earnings by about 5%, not the 50% that a revolutionary technology should offer. Five percent across a portfolio of billions is real money. It is also a long way from the scale of growth many hope for. The gap between what feels possible and what the spreadsheets show says something about where the bottleneck actually sits, and these days it isn't the AI. Sets up the essay's punchline that choosing well, not building harder, is what's left.Both AI labs went into private equity the same day: On Monday, Anthropic announced a $1.5 billion vehicle with Blackstone, Goldman Sachs and Hellman & Friedman. Engineers from Anthropic will embed inside the consortium's mid-market portfolio companies and build custom Claude workflows. The same day, OpenAI finalised a $10 billion joint venture; Google is reportedly in talks to do the same. What was reported as "AI labs raise more money" is actually a category change: the AI labs are turning into distribution-led services firms with a model attached, lifting the forward-deployed engineer pattern from Palantir. David's worry: PE has run the same cut-first playbook for forty years; the bigger unlock from AI is the opposite move, people making sharper decisions with a tool thinking alongside them. That value compounds; what a forward-deployed engineer hard-codes into a workflow does not.Push it harder, then skillify, then iterate: The simplest workflow upgrade David has coached this year, and it stacks. Push it harder: when the model gives you a perfectly reasonable answer, tell it to do more searches and use credible primary sources, government statistics, peer-reviewed papers. Three extra words, often. The next round does real research and surfaces what the first pass skipped. Skillify it: when a session produces something useful, ask the AI to turn the exchange into a reusable skill, a folder with a description and a prompt any future session can pick up; encode the mistakes as guardrails. Iterate: when the skill misbehaves, just say "change yourself so X" and it rewrites itself in place. Skills become living artefacts, not fixed ones. Works particularly well in Claude where skills are first-class.Shadow your most AI-pilled employee for two days: Matt Stockton, an operator and investor, made the case this week. Find the rabbit-holed colleague (not the keenest, not the head of digital transformation, the one who already knows what they're doing) and watch how they actually work for two days, then do the same work yourself for a week. "AI lives on command lines right now, it does not live in PowerPoint jargon slides." Most senior leaders consume AI through polished demos and vendor decks, then make strategy decisions with no felt sense of the technology's real constraints. Cheapest fix going. Questions to ask while shadowing: which tools and settings are you using, show me the actual prompt you typed, what did the model get wrong, what did you stop doing manually three months ago that's still in my diary.Ask AI to build you an HTML slide deck instead of PowerPoint: Just ask. "Build me a slide deck on [topic] in a single HTML file." Most chat tools can do this now. Why bother? PowerPoint output from AI is uneven, with broken chevrons, mis-rendered shapes, and two hours of touch-up. HTML slides come back closer to ready, are infinitely easier to edit (you talk to the file rather than wrestle with a template), and unlock things PowerPoint can't do: an inline edit-mode toggle that turns text into contenteditable, a speaker-view page with notes and a timer, narrate buttons that read slide notes aloud, a Q&A page that answers from the deck content only. Single-file decks travel better than multi-file projects: you can email it, host it on any static page, screen-share it without screen-sharing software.Read the full edition with all links and sources
