A new Anthropic research paper on AI and employment is getting a lot of attention. At face value, it suggests that the sectors most vulnerable to disruption from AI are white-collar, analytical professions: law, finance, management, media and arts, many academic disciplines. The headline finding and a radar chart of affected areas have been repeated ad nauseam in my LinkedIn feed. But a careful reading of what is a genuinely interesting paper explains why I find it less alarming than first appearance might suggest, despite it affecting the fields closest to my own work.

It has been a week in which AI moved decisively out of product demos and into politics, newsrooms, courts, and war. Across very different domains, the same underlying tensions keep surfacing: control, accountability, and whether speed is crowding out judgement.

Earlier this week, John Willshire posted on LinkedIn about Claude Code and the sudden proliferation of niche tools people are building with it. He wondered whether this “personal software”—quick, bespoke tools built to solve a very specific problem for a single person or team—might eventually develop into something scalable. Someone else replied that perhaps scaling isn’t the point. If the cost of building software has collapsed, tools no longer need to justify themselves as products. They can exist just because someone finds them useful, interesting, or entertaining to make.

A slightly shorter—and later—newsletter than normal, as I’ve been on the road this week (six webinars and courses in four days—welcome to new subscribers from those events). I started the week needing a productivity boost, and Google provided one…

Everything is now a data business, especially media companies. My friend Alex Boden’s analysis of the Washington Post’s pivot to WP Intelligence is characteristically sharp: editorial expertise converted into structured intelligence products, sold to professional audiences on enterprise contracts. The playbook works for a news publisher. The question for trade book publishers is what version of that pivot is available to them.

In recent months there has been a discernible shift in AI—and the pieces I feature—away from simple chatbots to agentic tools like OpenAI’s Codex and Claude Code. My smartest friends have moved from using AI for five or ten-minute microefficiencies to delegating complex coding or research tasks measured in hours. Chatbots will still have their place, but the rise of AI agents and big themes around trust dominate my thinking this week.

Thanks to Luis González, Javier Celaya, Christopher Kenneally and their colleagues for inviting me to give a keynote address on the impact of AI on audiobook publishing this morning at Parix Audio Day 2026 in Madrid. It’s one of the best conferences in the publishing calendar, and hands down the best venue.

I’ve been trying to write something here roughly once a week, largely but not exclusively about my experience working with AI in publishing. I hadn’t planned to post anything else this week, but John Willshire linked to a post from Rachel Andrew on managing publishing operations in the context of generative AI and I wanted to respond to it with some thoughts about how the issues it raises affect book publishing.