this post was submitted on 23 Feb 2026
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Screenshot of this question was making the rounds last week. But this article covers testing against all the well-known models out there.

Also includes outtakes on the 'reasoning' models.

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[โ€“] Greg Fawcett@piefed.social 61 points 10 hours ago (1 children)

What worries me is the consistency test, where they ask the same thing ten times and get opposite answers.

One of the really important properties of computers is that they are massively repeatable, which makes debugging possible by re-running the code. But as soon as you include an AI API in the code, you cease being able to reason about the outcome. And there will be the temptation to say "must have been the AI" instead of doing the legwork to track down the actual bug.

I think we're heading for a period of serious software instability.

[โ€“] bss03@infosec.pub 2 points 8 hours ago* (last edited 7 hours ago)

Yeah, software is already not as deterministic as I'd like. I've encountered several bugs in my career where erroneous behavior would only show up if uninitialized memory happened to have "the wrong" values -- not zero values, and not the fences that the debugger might try to use. And, mocking or stubbing remote API calls is another way replicable behavior evades realization.

Having "AI" make a control flow decision is just insane. Especially even the most sophisticated LLMs are just not fit to task.

What we need is more proved-correct programs via some marriage of proof assistants and CompCert (or another verified compiler pipeline), not more vague specifications and ad-hoc implementations that happen to escape into production.

But, I'm very biased (I'm sure "AI" has "stolen" my IP, and "AI" is coming for my (programming) job(s).), and quite unimpressed with the "AI" models I've interacted with especially in areas I'm an expert in, but also in areas where I'm not an expert for am very interested and capable of doing any sort of critical verification.