AI Code Review

In February 2025, Andrej Karpathy posted a tweet that most engineers scrolled past: “There’s a new kind of coding I call ‘vibe coding’, where you fully give in to the vibes, embrace exponentials, and forget that the code even exists… I just see stuff, say stuff, run stuff, and copy-paste stuff.” Most senior engineers read it and moved on. “A prototyping trick. Nothing serious.” They were wrong. Fifteen months later, 63% of users of AI coding tools are non-technical. CEOs are building internal systems with Claude prompts. PMs are replacing Excel with automated dashboards. BAs are creating workflow automation without touching a codebase. And critically — they are shipping those things to production. ...

Series Orientation: This article is Part 3 of the AI Code Review & Vibe Coding series, examining the unique failure modes of AI-generated code. For the broader business context, see the Series Executive Summary. When engineers first review AI-generated code, they often encounter a counterintuitive phenomenon: the code looks right. It passes compilation. The tests are green. The function signatures are clean. The variable names are descriptive. And somewhere inside, there is a logic error that will silently corrupt your data, or a missing authorization check that will expose every user record to the first person who thinks to try a simple query manipulation. ...

Answer-first: Discover what vibe coding is, why AI prototypes hit a Production Wall, and why AI code review is a critical skill for modern software engineers. In February 2025, Andrej Karpathy, former Tesla AI Lead and OpenAI co-founder, tweeted a phrase that would define a new paradigm in software development: “There’s a new kind of coding I call ‘vibe coding’, where you fully give in to the vibes, embrace exponentials, and forget that the code even exists.” ...