I have no idea why people believe AI will not be good at all the other things. It's a general reasoning machine, it surely can reason on many things beside the actual code.

I've been hearing this "writing code is not what being an enginner is" mantra for years like some sort of gotcha. (It was prevalent even before AI, and I think people underestimated a lot how many people were simply incapable of writing code even given all the specs and design choices.)

Technically it is not a reasoning machine. If it was a reasoning machine then we would not see results like this:

> To systematically investigate the role of end-user semantics of derivational traces, we set up a controlled study where we train transformer models from scratch on formally verifiable reasoning traces and the solutions they lead to. We notice that, despite gains over the solution-only baseline, models trained on entirely correct traces can still produce invalid reasoning traces even when arriving at correct solutions. More interestingly, our experiments also show that models trained on corrupted traces, whose intermediate reasoning steps bear no relation to the problem they accompany, perform similarly to those trained on correct ones, and even generalize better on out-of-distribution tasks.

https://arxiv.org/abs/2505.13775

Beyond Semantics: The Unreasonable Effectiveness of Reasonless Intermediate Tokens

Because it’s not about being “good at things”. You missed the whole point of the article. It’s not about AI vs. human capabilities, even a human could not build software if they are not in the right context.

Here’s an example: back in the 2000s, everyone was afraid programming was going to get outsourced to India or other countries. It didn’t happen, Sillicon Valley continues to spend billions to import engineers to work in person even though it’s 10x cheaper to hire remote outsourcers in India who are just as skilled programmers. Why do they spend 10x to move physical bodies to the office? Because it’s impossible to write good software without being in the physical context of the problem domain and team.

Similarly you cannot outsource to AI, because it cannot have complete context. No matter how good AI is, the problem is not mechanically solvable.

It can't reason at all. This has been shown time and time again, and is inherent to the very nature of how LLMs work.