Drive Scale And Speed With The Platform Org Model - 59% of respondents have using a platform instead of whole bunch of different platforms as a priority. // Enterprise want the benefits of centralized, standardized IT stacks. Always. DIY platforms and shadow platforms (sprawl od accidental platforms) is often a bad idea. Your platform needs aren’t special, your app needs are. If you focus on platforms, you’ll steal mojo and budget away from those app needs.

Issues for His Prose Style - Picking the right noun as a deep cut mechanic, to show authenticity, and build up a mythos of yourself, and for yourself. // Hemingway’s letters.

The big idea: what do we really mean by free speech? - What “freedom of speech” means to the asshats: “what they actually want is freedom from the consequences of broadcasting their views."

Paul Millerd on AI and writing - This is the response a very pragmatic writer had to AI.

Dutch people concerned with U.S., Russia, Ukraine developments; More support EU army -

5 Questions to Help Your Team Make Better Decisions - (1) What Would Happen if We Did Nothing? (2) What Could Make Us Regret This Decision? (3) What Alternatives Did We Overlook? (4) How Will We Know If This Was the Right Decision? (5) Is This Decision Reversible?

AI Essentials for Tech Executives – O’Reilly - Good tables translating AI-tech-speak to business outcomes.

Are AI Development Frameworks The Foundation Of The Agentic World? - This is a really good overview AI middleware, all the stuff you need to surround model access to. As you see, it is A LOT. And still, it doesn’t include the runtime and operations stuff - day two. // Side-note: when you hear the phrase “agentic AI,” just think “using AI in apps."

Software Sourcing in the Age of AI - More B2B slop. // “The average software sourcing process involves 28 stakeholders and takes six months. That’s six months of manual research, vendor meetings, demos, internal debates, and ultimately, a decision that still may not be fully informed."

Lack of AI-Ready Data Puts AI Projects at Risk - If you’ve let your data lakes turn into data swamps your AI projects are going to go poorly. // “Gartner predicts that through 2026, organizations will abandon 60% of AI projects unsupported by AI-ready data."