The problem
What was broken before AI
AI coding tools can create working-looking software quickly, but the first version is often uneven. It may pass a simple demo while missing edge cases, producing brittle code, or misunderstanding a requirement. A human can review the work, but when the builder is moving fast or working outside their strongest area, it is easy to miss issues that another reviewer would catch.
What changed
What the use case made possible
CJ’s workflow separates the roles. The first model acts as the builder and focuses on creating the implementation. The second model acts as a reviewer and focuses on finding problems. The reviewer’s output becomes the next input for the builder, but the human stays in charge of deciding which critiques are valid. That separation makes the workflow feel closer to a lightweight engineering team than a single chat session.
Why this matters
Why this use case is worth studying
This use case is valuable because it brings a familiar engineering habit into AI-assisted coding: do not let the author be the only reviewer. The second model is not a perfect senior engineer, but it can create friction at the right moment. It forces the work to survive another perspective before the human accepts it.
Use this when
When this pattern applies
Use this pattern when AI-generated code looks promising but you do not fully trust the first version. It works especially well for small features, prototypes, internal tools, or unfamiliar code where a second perspective could catch issues before you keep building.
