ByteByteGo published an argument on 24 August about a ratio rather than a technology. For years writing code was the slow, expensive step and reviewing it was a smaller task at the end. AI tools now produce a working function in seconds and a full feature in minutes, so the volume of machine-generated code a team ships each month keeps rising while the reviewer still has to read it.
The framing worth keeping is the gap it names: the distance between code that executes fine and code that is actually safe to trust is widening quickly. Those are different properties, and only the first one got cheaper. Producing code is now fast and relatively easy, which makes verification the harder part — not because review became more difficult, but because nothing about review scaled with generation.
That is the same constraint this site has recorded as a pattern, verification bandwidth being the scarce resource, and observed in practice where judgment becomes the scarce resource in agent workflows and where a three-person team shipping hundreds of pull requests moved the bottleneck into review. The coding agents hub tracks it.
This is an industry explainer arguing a trend, not a measurement of review throughput or defect escape rates, and the post carries sponsored placement alongside the argument. The condition to watch is whether teams publish review-capacity numbers next to generation volume, because a widening trust gap is only manageable once someone counts both sides of it.