abm53

That doesn’t change my argument.

I’m not saying it won’t happen, I’m saying it’s outweighed for most by other concerns.

You’ve leapt to the most extreme scenario to declare these contracts worthless.

Of course something like what you describe could happen. But under the central case, ensuring some privacy (with the ability to seek damages if breached) whilst still providing access to frontier models seems like a reasonable trade-off with a lot of value.

There’s obviously a strong interaction between the hackability of the target and the economic value of hacking the target.

Perhaps the latest models change that relationship in a meaningful way.

I’ve seen people recommend writing “failure is an option” into AGENTS.md as a non-training based crutch.

You’re trying to make a logical argument from first principles about a complex, dynamic and ultimately social system that admits no such argument.

I wouldn’t say the pessimists fall into that category.

In my experience they are mostly the subset of engineers who enjoyed coding in and of itself and ——in some cases—— without concern for the end product.

I think GP was a joke about the ability of a typical programmer.

I certainly read it as one and found it funny.

The article doesn’t present any hypotheses regarding this, and I suspect we simply don’t know yet.

But if true presumably it’s one of the usual reasons for observing data with low likelihood according to a model: misspecification or statistical bias/variance.

The rebuttal to this would be that you can do many such tasks in parallel.

I’m not sure it’s really true in practice yet, but that would certainly be the claim.

I’m unsure exactly in what way you believe it has gone “down the hill” so this isn’t aimed at you specifically but more a general pattern I see.

That pattern is people complaining that a particular model has degraded in quality of its responses over time or that it has been “nerfed” etc.

Although the models may evolve, and the tools calling them may change, I suspect a huge amount of this is simply confirmation bias.

> If you're the type of programmer who thinks of yourself as just a programmer, and take pride in your secure code, ability to optimize functions and algorithms, you're exactly the kind of programmer AI will replace.

The most successful engineers are the ones who can accurately assess the trade-offs regarding those things. The things you list still may be critical for many applications and worth obsessing over.

The question becomes can we still achieve the same trade-offs without writing code by hand in those cases.

That’s an open question.

More to the point: is randomness of representation or implementation an inherent issue if the desired semantics of a program are still obeyed?

This is not really a point about whether LLMs can currently be used as English compilers, but more questioning whether determinism of the final machine code output is a critical property of a build system.

Correct… reading code is a much more difficult and ultimately, productive, task.

I suspect those using the tools in the best way are thinking harder than ever for this reason.