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If you are good at code review, you will be good at using AI agents

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Using AI agents correctly is a process of reviewing code. If you’re good at reviewing code, you’ll be good at using tools like Claude Code, Codex, or the Copilot coding agent. Why is that? Large language models are good at producing a lot of code, but they don’t yet have the depth of judgement of a competent software engineer. Left unsupervised, they will spend a lot of time committing to bad design decisions. Last week I built VicFlora Offline: an offline-friendly PWA that hosts some of the VicFlora data for keying out plants, so you can still use the keys if you’re in the field somewhere with bad internet reception. Codex spent a lot of effort trying to reverse-engineer the VicFlora frontend code for the dichotomous key. It was honestly pretty impressive to watch! But I figured there had to be some easier way to access the raw data, and I was right. This happens over and over again when I use AI coding agents: about once an hour I notice that the agent is doing something that looks s

Using AI agents correctly is a process of reviewing code . If you’re good at reviewing code, you’ll be good at using tools like Claude Code, Codex, or the Copilot coding agent. Why is that? Large language models are good at producing a lot of code, but they don’t yet have the depth of judgement of a competent software engineer. Left unsupervised, they will spend a lot of time committing to bad design decisions. AI agents and bad design Last week I built VicFlora Offline : an offline-friendly PWA that hosts some of the VicFlora data for keying out plants, so you can still use the keys if you’re

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