The Instrument and the Ledger
In June I itemized the AI subsidy by hand. This month I built the instrument that does it for me. It took an afternoon, and it was built by the very thing it measures.
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All essays tagged claude-code.
In June I itemized the AI subsidy by hand. This month I built the instrument that does it for me. It took an afternoon, and it was built by the very thing it measures.
★Twenty-six days of Claude Code showed $2,556 of API-priced work against a $200 subscription. The lesson was not the total. It was cache behavior, model routing, and a government kill switch that landed in my usage chart. Value lives in verified outcomes, not tokens, and the work has to survive the stop.
★Claude Code agent teams are powerful, but they are not faster subagents. They earn their cost only when the work needs real peer challenge, not polite parallel execution.
A weekend home-networking project became a practical lesson in AI-assisted reasoning, documentation, guardrails, and engineering judgment.
The strategy posts say AI software development is a system. Here is the working loop I run inside that system: a refined specification, a layer of standards, and a coordinated set of specialists doing the work.
★After thirteen months of daily Claude Code use, I stopped treating AI coding as a prompt discipline problem and started treating it like an engineering system: configurable, layered, observable, and built to learn.
A decade-old side project, six major features, one week. How spec-driven AI-assisted development compressed months of work into a focused sprint on a real codebase with real constraints — and where the AI got it wrong.
After thousands of sessions with Claude Code, Codex, Kiro, and every other LLM-based CLI and IDE, I distilled what I learned into a reusable Claude Skill. Here's how those lessons became the guardrails that let me move faster and actually trust the output.
I took a production iOS app, pointed Claude Code at it, and had a fully functional Android app in eight hours over a weekend. Here's exactly how it worked.
From 'users want commute alerts' to 1,800 lines of shipped, App Store-ready code in a single coding session. A deep dive into architecture, edge cases, and what AI-assisted iOS development actually looks like.
Using Claude Code and Opus 4.5 as thinking partners helped me rebuild confidence, clarity, and quality in a growing macOS codebase.
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