In theory experienced humans introduce less bugs. That sounds reasonable and believable, but anyone who's ever been paid to write software knows that finding reliable humans is not an easy task unless you're at a large established company.
In my experience, they are not even close.
I would frame it differently. There are developers successfully shipping product X. Those developer are, on average, as skilled as necessary to work on project X. else they would have moved on or the project would have failed.
Can LLMs produce the same level of quality as project X developers? The only projects I know of where this is true are toy and hobby projects.
Of course not, you have switched “quality” in this statement to modify the developer instead of their work. Regarding the work, each project, as you agree with me on from your reply, has an average quality for its code. Some developers bring that down on the whole, others bring it up. An LLM would have a place somewhere on that spectrum.
Its the same reason a junior + senior engineer is about as fast as a senior + 100 junior engineers. The senior's review time becomes the bottleneck and does not scale.
And even with the latest models and tooling, the quality of the code is below what I expect from a junior. But you sure can get it fast.
I've been doing 10-12 hour days paired with Claude for months. The velocity gains are absolutely real, I am shipping things I would have never attempted solo before AI and shipping them faster then ever. BUT the cognitive cost of reviewing AI output is significantly higher than reviewing human code. It's verbose, plausible-looking, and wrong in ways that require sustained deep attention to catch.
The study found "transient velocity increase" followed by "persistent complexity increase." That matches exactly. The speed feels incredible at first, then the review burden compounds and you're spending more time verifying than you saved generating.
The fix isn't "apply traditional methods" — it's recognizing that AI shifts the bottleneck from production to verification, and that verification under sustained cognitive load degrades in ways nobody's measuring yet. I think I've found some fixes to help me personally with this and for me velocity is still high, but only time will tell if this remains true for long.
Just make sure it hasn't mocked so many things that nothing is actually being tested. Which I've witnessed.
You have to actually care about quality with these power saws or you end up with poorly-fitting cabinets and might even lose a thumb in the process.
This is the same pattern I observed with IDEs. Autocomplete and being able to jump to a definition means spaghetti code can be successfully navigated so there's no "natural" barrier to writing spaghetti code.