6 posts
You have type checking, linting, and architecture rules. But your deterministic stack is blind to complexity, duplication, and naming disasters. Here's the $0 fix.
Let's be honest about what most AI code pipelines actually look like right now. You generate code with Cursor or Claude Code. You run because TypeScript strict…
Human review is inconsistent. AI review is worse. The only scalable defense for AI-generated codebases is deterministic enforcement: rules that fail the build, not suggestions that get ignored.
The standard advice for AI-generated code is "review it carefully." That advice is correct and useless at scale. A developer reviewing AI output catches…
The meme is funny because teams really do build against moving targets, fixed launch dates, and half-decided scope.
Call it Meteor development. If you first encountered the meme in Chinese or Japanese circles, that tracks: in Chinese writing it often appears as 陨石开发 / 隕石開發,…
A Stanford CS146S review and critique: the inaugural Fall 2025 course gets AI coding right, but the missing lesson is AI architecture and replaceability.
Stanford CS146S is CS146S: The Modern Software Developer, taught by Mihail Eric and launched as an inaugural Fall 2025 course. If you want the official…
AI can ship your React Native MVP fast, but without guardrails each small change can break unrelated flows.
The first stretch of vibe coding feels absurdly productive. Cursor and Claude Code can generate login, dashboard, settings, and push notifications fast enough…
LLM code review is non-deterministic, slow, and misses architectural violations. Here's the O(1) guard stack that actually keeps your code clean.
A developer in my network set up Claude Code as his CI code reviewer. "Just have Claude check the PR," he told me. "It catches things I'd miss." I asked him to…