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Fair points, but verification is usually way cheaper than generation. If one actual human PhD can monitor a dozen AI agents, it is plausible that the value prop makes sense.
In a lot of tasks, including AI research and coding, you can also automate the verification process. Does the code compile and pass all tests? Does the new proposed optimizer beat Adam or Muon on a toy run?
That might be true today (and tomorrow, or next year), but the companies are betting hard on their models being capable of doing much more, and hence getting paying customers willing to shell out more. The true goal is recursive self-improvement, and the belief that this has far more dollars associated with it than even capturing all the money on earth today. Of course, they need market share and ongoing revenue to justify the investments to get there, which is why you can buy in relatively cheap. Competition also keeps them mostly honest, OAI would probably be charging a great deal more or gatekeeping their best if Google or Anthropic weren't around.
Not if P = NP
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Not necessarily! It's an adage among programmers that reviewing somebody else's code is often harder than making your own, because you have to figure it all out and then try to create some ideal version in your head and mesh the two together.
It's actually a big issue with vibe-coding - I end up with a codebase I don't understand and then have to do the work of figuring out the framework for myself anyway.
I would argue that this is a temporary state of affairs. Current AI coding is at the level of an over-caffeinated intern (who is very knowledgeable, but less than practical). Thus, a great deal of oversight is necessary to make sure they aren't shooting themselves in the foot.
But consider the potential SOTA in a year or two, when they're comfortably at par with mid-level coders. A senior SWE is usually happy to delegate to multiple experienced juniors, without worrying too much about the exact implementation details. My impression is that we're not there yet.
https://x.com/METR_Evals/status/1955747420324946037
In other words, a lot (but not all) of the theoretical time savings are eaten up by the need to understand, edit and improve their code. At present.
AFAIK it's usually mandatory for all written code to be reviewed before it's merged into the code base. At my last company every Pull Request (submitted code) had to be reviewed by two people, plus or including the 'owner' of the files in question. Review is usually considered a very onerous duty to be avoided where possible, and in theory reviewers bear as much responsibility for the final output as the original writer. The purpose is partly to inspect the quality of the code and to make sure it's doing what's expected (even senior guys fuck up) and partly to make sure that at least a few people are familiar with each part of the codebase.
This was at a 'move-fast-and-break-things' company. The review standards at somewhere like Intel are of course significantly higher.
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