AI & Machine Learning
Editorial coverage of artificial intelligence — the models, the infrastructure, the businesses being built on top of them.
Our AI coverage is grounded reporting on the systems, businesses, and second-order effects that actually matter. We audit predictions against outcomes, map production patterns as they emerge, and separate the frontier story from the small-model story. Every piece is reviewed by a human editor with a working understanding of the underlying research.
Editor's Picks
The Real State of MCP: 18 Months in Production
Eighteen months after Anthropic open-sourced the Model Context Protocol, MCP has quietly become the default plug for AI agents. We surveyed the public registry and production deployments to map what works, what breaks, and where the next gap is.
The Small Model Renaissance: When Big AI Doesn't Win
The narrative that big always wins is a partial narrative. We map the class of small, task-focused models that quietly took a growing share of production AI work — where they win, where they still lose, and what changed.
The Five-Layer Cake of Modern AI Infrastructure
The AI infrastructure conversation is bad because the layers blur. Most arguments about 'the AI stack' confuse five separate markets with five separate competitive dynamics. Here is the framework we use to keep them apart.
We're still writing on this topic.
Subscribe to our weekly newsletter to catch the next AI & Machine Learning piece.