Field notes.
Threads we're watching across AI, transformation and tech leadership — and the public signals we're reading. Less newsletter, more living notebook.
01Why we built this page
We read a lot about AI — more than is reasonable, honestly. Most of it doesn't hold up after one week of real work. This page is our attempt to hold on to the parts that do: the patterns, the moments of change, the things worth re-reading a month later.
What you'll find here are themes, not transcripts. Eight of them. Underneath, a living feed of the public links we've found most worth sharing onward. Everything is refreshed weekly.
For context on where we're writing from: our Raconteur coverage on Travelopia's AI experiment, and the post that kicked our internal momentum off.
02Eight themes we're tracking right now
Anthropic's release pace has become a strategic signal.
What stands out right now isn't any single Claude feature — it's the rhythm. New capabilities are landing almost every week: agent teams, design tooling, the rumoured one-prompt-to-app workflow, an agent view inside the coding tool itself. The tooling layer that start-ups raised hundreds of millions to build is being absorbed back into the model. If you're planning a twelve-month roadmap that assumes today's frontier capability, you're already behind.
Agent-oriented architecture is the next practitioner chapter.
Multi-agent marketplaces look exciting on slides but fall short in real use. The pattern that's actually working is smaller, well-bounded agents with clear responsibilities and interfaces — boring in theory, easier to manage in practice. Agent registries are starting to feel like a missing basic building block; the major cloud providers are racing to ship one. Discipline beats numbers.
LLM-curated knowledge bases are quietly building up.
One of the more interesting experiments we're watching: knowledge wikis maintained by an LLM, fed from a few hundred sources and refreshed continuously. The insight isn't the architecture — it's that LLMs are extremely good at the small upkeep that humans usually drop. Over time, company knowledge starts to build up rather than reset every time someone leaves. Expect more of this inside large companies within the year.
Sustained scepticism is forming around OpenAI's strategy.
Long-form journalism this spring — a New Yorker profile, a widely-read Daring Fireball critique, a serious book — is shifting the conversation among people who actually use these tools. Projected losses over the coming years look very large, the "super-app" direction is unpopular among architects, and the Microsoft partnership seems to be breaking apart. None of this is fatal. But it's no longer all-positive cheerleading either, and that change of mood matters when you're deciding budget.
Engineering work is reshaping this year, not next.
A few public data points are adding up. A major chip company reporting that effectively all of its software engineers now use AI coding tools daily. Notes from senior researchers warning that agent swarms still need close watching. Slide-deck workflows that used to take a day now come out of a single prompt with the right skill and a frontier model. The IDE is no longer the main place where work happens for more and more kinds of products.
Model collapse and agentic data risk are moving into the boardroom.
Two concerns are moving from blog post to the executive agenda. The first is the snake-eating-its-tail risk: frontier models trained on more and more AI-generated data, and the role of synthetic data in balancing it out. The second is agentic data risk — workflows where agents quietly change data at a speed and scale humans can't check in real time. Regulated industries are starting to ask what proof an executive team needs before they sign anything off. The honest answer right now is: we're still working it out.
Supply-chain attacks via AI tooling are the new normal.
The most-discussed incident of the spring wasn't a model jailbreak. It was a major platform broken into through a compromised third-party AI tool's OAuth integration. The lesson is old — wrongly set up third-party apps have been tripping up infrastructure teams for decades — but the attack surface is now ten times larger. Role-based access control, and giving every agent only the minimum access it needs, are no longer optional from day one.
Practitioner enthusiasm sits inside wider public mistrust.
A grounding note that's worth keeping close. Inside the bubble of people who use these tools every day, it's easy to forget that elsewhere AI is treated with deep suspicion. "Why did you use AI?" is a normal response in everyday life. The public conversation about AI in society — its benefits, its harms, its costs — is still very much in motion, and worth paying attention to even when the demos keep getting better every week.
03Signal feed — what we're reading
Public links we've found worth sharing onward. Newest first. Filter by keyword, date or source.