What Do You Do While AI Codes?

AI coding assistants have fundamentally changed the rhythm of software development. While an AI generates code, you might have five minutes here, twenty there. These gaps add up throughout the day, and how you spend them determines whether AI makes you more productive or simply gives you more time to procrastinate.

Five ways to make those minutes count

First, review what the AI wrote immediately. This sounds obvious, but many developers let AI output pile up without checking it. The longer you wait, the more context you lose. A quick scan while the AI is working helps you catch obvious issues before they become debugging sessions.

Second, write tests. AI generates function signatures and implementations fast, but tests require understanding the business logic that AI cannot infer. Use those gaps to think through edge cases and write assertions. When the AI finishes generating a function, your tests are ready.

Third, plan the next step. AI works best when given clear direction. Use coding gaps to think ahead: What should this module do next? What are the dependencies? Sketch out the architecture on paper or in comments. When you return to the AI prompt, you'll have sharper requirements ready.

Fourth, update documentation. Many developers treat docs as an afterthought, but brief comments explaining why code does something (not just what it does) prevent future confusion. The AI is generating the "what" — fill in the "why" during your gaps.

Fifth, communicate with your team. Those five-minute windows are perfect for Slack messages, code review comments, or syncing with teammates. Staying connected prevents the isolation that remote work can create and keeps everyone aligned.

The habit that makes you the bottleneck

Here is the trap: treating AI output as final. When you trust AI suggestions without scrutiny, you become the bottleneck because you eventually need to fix the bugs, explain the unclear code, and handle the edge cases that AI missed. Worse, you stop improving because you're not engaging deeply with the code.

The "quick" habit that backfires is glancing at AI output and moving on. It feels efficient in the moment, but deferred review compounds into technical debt. You spent the time you saved creating problems you'll solve later under pressure.

Instead, treat AI output as a first draft from a junior developer — useful, but requiring your expertise to refine. This keeps you engaged, catches issues early, and makes you genuinely faster, not just busier.

The developers who thrive with AI aren't the ones who type less. They're the ones who think more while the AI types.

Further reading: https://dev.to/anchildress1/what-do-you-do-while-ai-codes-k8k