incrudible

This argument would be more convincing if, due to performance reasons, most Python code didn't use C extensions, where exploits are highly prevalent.

Python is a poor target for compilation, even the best JIT is never gonna make fundamental design flaws (that some may consider beloved features) disappear. It's never going to give "good" performance.

In my view, the right course of action is to specify an official strictly typed subset of the language with compilation and static analysis as the justification, then implement both JIT and AOT on top of that. Legacy code can be rewritten or thrown out in phases, C extensions can be ported.

Of course, any such proposal would invite monumental amounts of bikeshedding, which is why it wouldn't get far, much like the JIT proposal.

I can see that you only work with true scotsmen, but the machine really does write most of the code now, at least from a pure numbers perspective.

Where are these 180 IQ models? Even Fable needs guidance so it actually produces output I consider on par with what I could have written myself in a domain I am familiar with, and I am certainly not at the frontier in those domains.

Is it actually better though? Can you even measure it? Unguided, Claude will just produce mediocrity which by its own existence becomes almost worthless, and the newer versions become increasingly difficult to guide while also being obnoxious to read. If I did not have to interact with it, it would not be a big deal, but then also I could not get value out of it.

It is not the jargon per se, it is the style. Other models even in the same family are not as bad, and I still have to babysit it, so the voice matters.

Opus 5 is literally unbearable to read for me, but more importantly, it is much worse than 4.8 and that one was already annoying. The more they train it on its own output, the more pronounced its idiosyncrasies become.

Manufacturers know demand will last to the extent that big companies are willing to commit to purchases over a given period of time, but supply today is still constrained by capacity built for the pre LLM era. The 500 billion put in by Samsung/SKHynix will increase modern DRAM by roughly 50% but it wont be fully online until 2030.

It can definitely create a software stack for you if you hold it right, but the software stack supported by a trillion dollar company with decades of expertise, that also uses AI to improve its stack is probably gonna be better.

People are reading this as a slight against single authors, but it is a slight against the belief that anyone deeply understands complex code they wrote even a week ago. It is just a bullshit belief. Yes, you build an intuition about it, but you need to constantly refresh your understanding. That is just how the brain works.

Now, if you have program that is highly complex, written by a single author who is not you, hinging on the ongoing goodwill and capability of that single author, that is a liability you do not want to have, operationally. Again, that is just how it is.

No codebase worth being deeply invested in is deeply understood by anyone, including the original authors. The eternal maintenance argument is tiresome. If there is a problem in need of fixing, you figure it out, you do not depend on some author being available, and LLMs are exceptionally helpful in this regard as well. Then, if the LLM has trouble figuring out, so will another human. It is a code smell.

Picking a DVD to watch is a rather inconsequential decision. LLMs already do this sometimes, asking you to pick one of a few options, but without domain expertise you will invariably make worse decisions, but if all the n-th order consequences were first explained to you, that would result in you having built domain expertise, but also erasing most of the speed advantage LLMs give you. Moreover, you will never know about the options that are never presented.

Inevitably, this is the new tradeoff to make, above average quality comes from asking for more, and knowing what to ask for comes from expertise.

You are completely off base with your assumption about what it costs to serve models. Nobody is gonna serve you K3 as cheaply as Anthropic is serving you Opus on any of their plans. Nobody has that kind of money to burn. Kimi does not even sell you a plan right now.

That's not how you should use it and LLMs aren't that bad anymore. Either you just accept the quality level of LLM code wholesale, which means accept mediocrity in exchange for volume, or you at least leverage the LLM to improve the process surrounding the production code.

I read it more as pointing out the inevitable and accepting the implications. You can not call it the result of poor practice when every business beyond a certain size has this problem.

Perhaps the problem could be mitigated by keeping the company itself small, but that has nothing to do with programming anymore.