Asked ChatGPT for more radical ideas to deal with code review volume. Suggestion 9 was: just regenerate the code instead of reviewing it. It’s not wrong — but no such product might survive long enough to have users.
The reactions were interesting:
- As complexity increases, regenerating could require “a trillion tokens and multiple days” — it doesn’t scale linearly
- It might work for “large enough values of N and maybe not the whole codebase at once” — partial regeneration as a review strategy
- Someone would fund it anyway
The underlying tension: AI agents generate code faster than humans can review it. The traditional answer is “review better.” The radical answer is “don’t review — regenerate and test.” Neither is fully satisfying yet.
This connects to a broader pattern: when the cost of producing code drops to near zero, does it make more sense to verify what you have or throw it away and make it again?
Originally posted on LinkedIn