Study finds coding efficiency gains get “absorbed” by human review “bottleneck.”

Well, that's a pretty shitty way to phrase "LLMs are useless, actually".

Very CEO-brained kind of language. Very much portrays human employees as a "problem"/"obstacle" to be worked around. And LLMs as the "solution".

Just like junior devs!

Every time I test and LLM solution and am pleased with how well it works, and I look at the code and it looks reasonable, it’s a lie. It may work, and even look okay, but unless the change was minuscule it’s always doing weird things when I look closely. By the time I’m done fixing the code I could have done it significantly faster myself.

Edit: in case anyone is wondering I only ever use frontier models (the anthropic and openAI ones), I have unlimited access to them from work and mandates to use them.

Any efficiency increased during the actual coding phase, the study authors find, is “absorbed by downstream constraints in the production process”; as “the code review process significantly increases in length, pull requests are more likely to require revisions, and reviewers leave more comments.”

Yep. Almost like actually understanding problems and computers was the job, and not just typing.

Solution is clear, just let an LLM review the PRs!

The moment AI can take the dumbest, completely lacking detail, uninformed, uneducated, unmotivated idea from a (Project/Program/Moron) Manager and turn it into something worth value... I'll know that my job is in danger.

Yeah this rings true to my experience.

Study finds coding efficiency gains get “absorbed” by human review “bottleneck.”

Reviews? I very much doubt anyone is reviewing anything.

At best tests (also made by the machine) pass... but since no one is reviewing the tests either, who knows if they're actually testing what they're supposed to test.

Easier to vibe code a new update whenever the latest one breaks anything important. Who cares if every windows update causes widespread errors and millions in losses? Certainly not microsoft.