David's Saturday AI Thoughts

A story arrived nearly whole on a hot, sleepless London night, so David got up and wrote it: Sarah resigns on a Tuesday, and her firm keeps her anyway, rebuilt from three years of her emails, transcripts and Slack, because the archive holds what her handover never could. Every step is possible with tools firms already own. The reader comments chilled him more than the writing did, and they shifted...

Two photographs of the same Wimbledon court forty-two years apart tell the whole story: in 1982 the grass is worn where players served and rushed the net, and by 2024 the bare patch has moved to the baseline because the game became a rally. David uses that shift to argue knowledge work has made the same move, only in four years instead of forty-two. Producing got cheap, so the effort moved to fram...

David sent an important email last week that a machine wrote, read it, changed nothing, and sent it — one of three handovers that look, on their face, like exactly the surrenders the worriers warn about. None of them were. Taking Rahim Hirji's new book SuperSkills as a generous foil, he argues most AI handovers are good bargains, not a thousand small surrenders dressed as convenience: the machine...

Almost nobody who sets up their AI ever tells it who they are. Not just the job title, but how they think, what they notice, how they decide. David Boyle argues that the empty personalisation box is the most useful question the whole product asks, because if you don't tell the model what makes your judgement specific, it has one assumption left: you're average. He builds the case on fresh research...

Anthropic's newest model costs exactly double its predecessor, one GitHub Copilot bill jumped from a flat $50 a month towards $3,000, and suddenly the invoice, not the model, is the story. David argues most organisations manage these bills exactly backwards: they celebrate the biggest token burners or cap everyone, and both approaches manage the number instead of the judgement. His maths says the...

David finally does the thing he has spent years telling other people to do: he hires a graduate. Ethan joins for a placement year, taken on as an experiment, because the awkward truth is that a graduate today is more capable than ever and less needed than ever. David sets out four hypotheses for why a young person is still worth it: someone has to check and own what the machine makes, managing a m...

David walks through how AI got practically useful, grounded in Dwarkesh Patel and Gavin Leech's The Scaling Era. The through-line: the future of AI has shown up long before it shipped, every single time. Seeing wasn't the hard part; believing it enough to bet on it was. He revisits the early scaling-law moments that should have been obvious to outsiders, asks why they weren't, and what today's peo...

What happened this week: * AI displacement now shows up in the US government data at both ends of the career ladder: A Bloomberg analysis of new BLS figures finds every one of the eighteen occupations the BLS classifies as A... * The UK's data regulator has put AI hiring tools on formal notice. Sixteen organisations have already had a letter: The Information Commissioner's Office issued formal gui...

What happened this week: * The METR capability curve just went from one hour to one day. The unit of AI autonomy is now measured in human work-days, and the doubling holds on a log scale: METR, an AI evaluation lab, measures... * Half of organisations have already redesigned core workflows around AI, and a fifth have built new business models. The gap framing misses the story: BCG's AI at Work 202...

What happened this week: * 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 ... * 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 i...

David builds the case that flat-rate AI pricing is dying and that the buyer's question is no longer 'how much will this cost' but 'where does the spending compound'. He opens at a Las Vegas buffet that closed on 31st May, then moves to the supplier-side news: three of the four biggest AI vendors switched pricing in the last few weeks (Anthropic stripped bundled tokens out of Enterprise seats in mi...

AI-native teams need three roles: Director, Builder, Auditor. Execution is cheap, verification is expensive. Most organisations have zero Auditors and are shipping nothing because nobody is named to check. What happened this week: *

AI broke the old proxy (good writing = good thinking) but the new proxy ('sounds like AI' = no thinking) is equally unreliable. A friend's challenge prompted a deeper question: evaluate thinking, not wording. Two tests proposed: Quality (does the argument hold under pressure?) and Ownership (CEO principle). Fine-tuned models now preferred over human writing 62% of the time. What happened this week...

Team-level AI infrastructure can precede and contain individual training. The cost of encoding how a team works into shared reusable tools just dropped from hours to minutes with Gen 2 tools (Claude Code + transcripts). A small jewellery company built thirteen shared skills in a day. Step two doesn't just follow step one, it can contain it. What happened this week: * Claude Code now writes 4% of a...

Organisations say they're production systems but behave like human systems. The revealed preference is togetherness, not efficiency. AI adoption reverts because training optimises for individual productivity while the real binding force is human collaboration. What happened this week: * Dorsey wants to replace org charts with AI world models (Block restructuring) * Mollick says de-weirding AI is a...

A Wharton study of 1,372 people identified 'cognitive surrender': when AI produces an answer, people stop questioning it while recoding it as their own judgment. Accuracy drops from 45.8% alone to 31.5% with incorrect AI. The better the system gets, the harder it becomes to stay vigilant inside it. What happened this week: * Three CEOs (Coca-Cola Quincey, Walmart McMillon, Adobe Narayen) stepped d...

The gap between AI wonder and behaviour change. PwC's CEO says get with it or get out, but the real question is get with what. Jeremy Howard's slope-over-intercept frame: capability growth matters more than current output. Anthropic's research shows most coding tool users enter autopilot. Not all inefficiency is waste: some friction is load-bearing. What happened this week: * Centaur chess inverte...

The dual experience of AI acceleration: excitement and terror, said in that order. Top builders 3-5x more productive, median only 10-20%. The gap widens. Amazon outages show what happens when power outpaces care. Skill requirements dropping in AI-exposed jobs. The organisations that will matter are those building in care alongside speed. What happened this week: * Shopify CEO ran AI optimisation a...

Leaders deploying AI face a binary choice: extraction (cut costs from existing operations) or expansion (grow what the organisation is capable of). The apprenticeship pipeline paradox: if juniors never do the grunt work AI now handles, how do they develop the judgment that makes seniors valuable? Hiring as deliberate investment, not necessity. What happened this week: * Software stocks down ~30% s...

AI value sits not in dramatic one-off wins but in a hundred small daily elevations (better meeting prep, cleaner drafts, faster document scanning) that compound into transformation. Firms can't see it because they track big projects, not distributed micro-gains. The Japanese senryu poetry cancellation illustrates the risk: AI alone produces sameness, AI plus human steering produces something bette...

The tension between individual excitement about AI (senior leaders working weekends, doing a week's work in ten minutes) and organisational inertia (unchanged meeting cadences, team structures, adoption rates). 84% of the world has never used AI. What happened this week: * Technical barrier gone, domain expertise matters now: Wharton MBA students built companies in four days with AI tools, non-tec...