A slightly shorter email than usual today, as it’s been a very busy week of travel. I had conversations about AI in some interesting places: a publishing conference, an Oxford college and the House of Lords. The latter two particularly felt a long way from Silicon Valley, but the discussions underlined how much the technology is permeating every aspect of our lives. ​ International readers may have missed President Trump’s state visit to the UK this week, but domestically it’s been hard to ignore. There was a slew of major AI investments being announced, but for publishers the most consequential aspect of the week was confirmation from new Technology Secretary Liz Kendall that no commitments had been made to AI companies on UK copyright and AI training. ​ A couple of major updates on AI and ecommerce. Amazon announced an upgrade to its Seller Assistant, which now includes AI agents for tasks like inventory management. Publishers or retailers using FBA can use the AI to review stock levels, minimise charges, identify product opportunities and plan marketing campaigns. This goes beyond basic automation into generating proactive insights. This is interesting in its own right, but also speaks to Amazon’s bullish strategy on AI: this tooling is for FBA today, but it shows the direction of travel for Vendor Central and other systems. ​ Secondly, on the customer side of the transaction, Google launched Agents Payment Protocol (AP2), a standard way for AI agents to be authorised to make purchases on behalf of consumers. More than a third of UK consumers (more than half in the US) are already using generative AI for research and product discovery. Whether purchasers will be happy with the idea of an AI personal shopper is a big question. ​ I was at the Independent Publishers Guild Autumn Conference on Tuesday, and had the pleasure of chairing a panel with Isaac Jones of the BMJ and Lauren Ingram of Next Big Thing, discussing the impact of AI on websites, and how to optimise website content for AI models. Publishers need to strike a balance between controlling how the content on their website is used by AI models, preserving traffic, and being visible and hyperlinked in AI outputs—or, as I thought about it afterwards, having your click and feeding it. This is a fundamental question given that point above on the importance of AI for product discovery. This is a complex and nuanced topic, but as a start on a checklist for publishers, my takeaways from the session were: there will be a range of perspectives even within a publisher—editorial, marketing and technical stakeholders look at this through their own lens, so coordination is essential; quality of content (including specificity, uniqueness and credibility) is fundamental, which should play into publishers’ strengths; and experimentation is key, including putting yourself in your audience’s shoes and using the platforms they do. Do get in touch if you’d like to discuss what this means for your business. ​ Some highlights from OpenAI’s new research paper on how people are actually using ChatGPT: around 10% of the world’s adult population has used ChatGPT; 18 billion prompts are being sent each week; and non-work use cases (advice, shopping) account for 70% of usage, up from about half a year ago. ​ There’s a sobering report here on librarians’ experience of AI: patrons showing reduced critical thinking, and requesting hallucinated books. ​ Thanks to Thad McIlroy for highlighting an essay on AI in the workplace that argues most organisations are essentially in the business of converting work from one format to another. As it points out, there’s a natural role for AI in this, and the implications it identifies for organisations echo the HBR piece I shared last week on consulting firms. Broadly it rings true. But two nuances strike me. First, AI is very good at summarising—many of the examples in the essay are essentially reductive—but often less capable when the task is to expand short form into long form. Second, what AI produces often loses individuality. In Oxford this week, I spoke with a Mandarin translator about how AI translation can be powerful but flattens linguistic nuance. For some tasks in business and publishing, the output may be good enough. But publishing is a business of meaning-making as well as information—and that’s where the human voice remains indispensable.

This week’s stories point to deeper layers of the AI stack: standards, infrastructure and how organisations are evolving. From licensing to litigation to content production, there are clear signs of where publishing may be heading.

This week’s practical insight focuses on two linked topics: onboarding and oversight of AI models. But there are also more philosophical questions from news publishing and Seth Godin, and details of the most open LLM to date. Have a great weekend. ​ Sometimes it’s the simplest insights that stick. In a recent webinar with Rich Ziade and Paul Ford of AI developer Aboard, Rich said something that stopped me in my tracks: “AI is a new hire.” When you onboard a new team member, you think carefully about their role—who they’ll work with, what systems they’ll need access to, how they’ll get up to speed. In a hybrid workplace, we’ve learned that structure and documentation matter more than ever. But with AI, I’ve seen people open up a general LLM with no context or preparation, and then feel disappointed by the results. It’s the equivalent of throwing a new hire in at the deep end and hoping for the best. ​ Here’s my start on a checklist to avoid that. Have you done each of these things for your AI projects? And let me know if there’s anything you’d add to the list.

The AI and content ecosystem is maturing fast. The big news this week is a settlement in Bartz v. Anthropic with implications for other litigation. But besides the big picture, the newsletter highlights new tools and practical things you can try. Have a good weekend.

AI is changing how people produce, discover and evaluate content. This week’s stories show how fast those shifts are happening. From Amazon’s AI shopping assistant to Grammarly’s reimagining of student writer, publishers face questions about visibility, value and voice.

This edition covers OpenAI’s response to GPT-5 feedback with a partial model selector and a 140,000-word context window, Drew Breunig on how long contexts fail and how to fix them, John Willshire’s seven key questions for working with AI, MIT Press’s survey of 6,000 authors on LLM training, Reddit blocking the Internet Archive’s Wayback Machine, Neil Perkin on using AI for scenario planning, and a personal case study on using AI to size and map the UK publishing industry.

Recently I’ve been doing some research on the size and scope of the UK book and journal publishing industry, based on data from Companies House. This research is a preparatory step towards building a database of companies, highly relevant for my work as an independent consultant and as policy advisor for the Independent Publishers Guild, which represents over 600 book and journal publishers of all sizes. The other trade body, the Publishers Association lists 168 members at the time of writing, particularly larger, corporate publishers—though there is some overlap between the two organisations’ memberships. The UK publishing sector is world leading, representing over £7 billion of revenue, and it represents the bulk of my client base. So it’s worth understanding.

As AI capabilities expand, so does the gap between what’s technically possible and what’s useful and meaningful. Many of the links this week address the same question: where does human perspective add value?