Links

Kurt Mackey makes a compelling case that ephemeral sandboxes are fundamentally the wrong tool for running code with AI agents. His insight is that agents work better when they can maintain context across sessions, avoid redundant package installations, and leverage the full system lifecycle. This is an elegant solution to a common problem that I’m eager to try out.

The hardest working man in blogging, Simon Willison, rounds up the biggest LLM trends of 2025. From inference-scaled “reasoning” and tool-using agents to the breakout moment for coding agents like Claude Code, the amount of change has been truly colossal. It’s a dense, opinionated timeline that connects product releases to what actually changed for developers and day-to-day workflows.

A deep dive into how LLM prompt caching works under the hood, focusing on the transformer attention mechanism and the exact data providers reuse between requests. This is also one of the most accessible explanations of how LLMs work that I’ve encountered. The visuals are really clear, and the step by step walkthrough is incredibly clear. Via Simon Willison.

Via kottke.org, Robin Sloan describes himself as the programming equivalent of a home cook. I’ve been working in professional kitchens for a really long time, but lately I’ve rediscovered the joy of home cooking myself.

Simon Willison released a Python CLI tool that converts Claude Code sessions into shareable HTML pages with more detail than Claude Code itself provides, including hidden thinking traces.

A compelling reframing of Kubernetes as ‘a runtime for declarative infrastructure with a type system’ rather than just a container orchestrator.