AI coding shifts work into review, context, and cleanup
AI can make code faster and cheaper to write. But the important work around coding has moved to the steps before and after generation. Teams still need to know exactly what to ask for, give enough context, catch wrong , and check .
They also need to decide what should actually be shipped and clean up code that runs but does not fit the system. The job has shifted from typing code to steering, reviewing, and integrating work. is closer to a very fast first draft than finished work.
That may be fine for a prototype, but in a real codebase the costly part is often making sure a change fits the system.
Key points
- AI lowers the cost of writing code but does not remove the full engineering workload.
- The work moves toward clear instructions, context, review, and cleanup.
- should be treated as a fast draft, not finished work.
- A prototype can tolerate rough output more easily than a real codebase.
- Cost savings should include review and time, not only token spending.