Coté

AI companies are building platforms for running agentic applications. Right now, those applications are primarily for software development, with a little bit of knowledge worker stuff. In each case, you get a “harness," an application that wraps all sorts of functionality around a model. This harness app is way beyond the chat-based apps we grew up with over the past few years. They use the model to figure out multi-step processes and get access to data and other apps - accessing files, working with your email, PowerPoint, etc.

Summarized by AI. 2026-04-12 09:40 Bernie vs. Claude Senator Bernie Sanders questions Claude directly about how AI intersects with privacy, profit, and democratic erosion, framing data collection as the hidden engine behind most consumer-facing AI. Claude concedes that companies harvest browsing history, location, purchases, search activity, even pause time on a page, then feed it into AI that assembles granular personal profiles users never meaningfully consented to. Those profiles drive targeted ads, differential pricing, and feed ranking, all invisibly and largely unregulated.

Summarized by AI on 2026-04-14. A Berkman Klein Center public conversation between Tyler Cowen (George Mason, Mercatus Center) and Jonathan Zittrain (Harvard), framed around hypothetical Anthropic and OpenAI releases Mythos and SPUD, each powerful enough to be withheld on safety grounds. Cowen opens by saying he believes the safety claims, adding that the real question is not whether these frontier models are dangerous but how long until an acceptable open-source equivalent arrives.

Also: Anthropic devouring IT services, Spring Boot 4, Fanta lore, and outsourcing D&D Related to your interests The Modern Spring Workflow Is Enterprise-Ready and AI-Boosted The Spring Team on Spring Framework 7 and Spring Boot 4 On Anthropic’s Mythos Preview and Project Glasswing - Yes: “This is very much a PR play by Anthropic–and it worked.” But: “Everyone who is panicking about the ramifications of this is correct about the problem, even if we can’t predict the exact timeline.

I wake up at six every morning to have coffee, read The Economist briefing, and read my “RSS feeds.” Everyone else is asleep, and it is quiet and dark. This is when I find things to bookmark and share, or just read and inform myself. Sometimes I start projects. Recently, getting all my janky AI harness stuff right. This is a mistake. About 90 minutes later, I need to make sure everyone is awake (four people ranging from six years old to 50) and moving towards the goal of getting to school on time.

Also: Managed Agents, password manager angst, and vibe-coded home dashboards NASA's "A Crater of Remembrance," from Artemis II. Full set here. Related to your interests Suits won’t quit AI spending, even if they can’t prove ROI - “[I]n a survey of 2,110 business leaders globally, the consultancy found 70 percent of UK business leaders think AI will remain high on their spending agendas even in the face of an economic downturn.

When I see a platform engineering conference talk about building an internal developer platform on Kubernetes, I think about cf push. Cloud Foundry has been doing this - the actual thing, the single command that takes you from source code to running app - for more than a decade. People keep rebuilding it on top of Kubernetes with Backstage plus a pile of CRDs and a bespoke yaml, and that’s.

If you’ve spent any real time with Claude Code or Cursor, you know the feeling. The thing you told the agent five minutes ago is now optional as far as it’s concerned. The fix isn’t a smarter model. It’s architecture. This week David Zendzian and I dig into memory for AI agents - what it actually means, why one giant context window isn’t it, and what a real structure for long-running agent work looks like.