Carbon Basics 1: What carbon is, and why it matters
What CO₂e means, how much CO₂ has built up in the air, how much of the 1.5 °C budget is left, and how big a tonne really is, shown in four 3D visuals instead of paragraphs.
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Analyzing DeepSeek Harness: How Do You Build an Agent Harness Where "Everything Is a Plugin"?
DeepSeek Harness (dsh) turns the model adapter, the tool registry, the session log, and even the agent loop into Cordis plugins, then assembles the product by stacking patch layers on top of an empty tree. Two weeks after release it passed 200k GitHub stars. This is a source-level analysis of its kernel (Cordis), profile and bundle composition, the rule that the session log is the source of truth, capability seams, self-modification tools, and the way it runs Claude Code and Codex as subagents.
Is Rails Slow? I Built the Same Blog API Eight Times to Price the Framework
"Rails is slow" is an unanswerable question, because a Rails app and a Go app are never doing the same work. So I narrowed it: inside one runtime, what do the framework and the ORM cost? Four runtimes, each built twice, all returning identical JSON from the identical four SQL statements, measured three times on Docker Linux with MySQL. The abstraction cost in CPU per request came out at ×7.67 for Ruby, ×6.14 for Python, ×2.62 for Node and ×2.51 for Go — and I counted, object by object, exactly what Active Record builds on every request.
Why I Made Markdown the Source of Truth — Building a Dashboard with an AI Agent
A retrospective on building a macOS desktop app (Tauri + Rust + React) with an AI agent. The decision to make markdown files — not the database — the source of truth, the research I did before writing any code, the features I chose not to build, and the macOS permission bug that took the longest to crack. A story about judgment more than code.
spec-kit vs superpowers: Two Ways to Give a Coding Agent a "Process"
GitHub's spec-kit and Anthropic's superpowers plugin both force a workflow onto coding agents so they never drift into vibe coding. But one is a spec-first file system that leaves the specification behind as an artifact in a .specify/ directory, while the other is a collection of discipline prompts lazily loaded through the Skill tool. We compare the two projects across distribution model, artifact philosophy, token cost, and extensibility.