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Culture War Roundup for the week of October 5, 2026

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Why haven't they done this already?

As I said, if the scaling stops tomorrow then maybe the models simply are not good enough to do this autonomously and other human labor is required to guide them along. If it continues at this rate for another year or two things change dramatically.

Even in coding, which they have been optimized for, the data that I've seen indicates that trust by developers has fallen as adoption has risen, and that as LLMs have increasingly been adopted in coding, the amount of insecure code has risen substantially while deployments have actually slightly dropped.

Just as a personal example, the other day I asked Sonnet 5 to implement a design and it decided to simplify the product on its own recognizance. For me, it's a little annoying. But obviously at scale for a real-world product that's disastrous.

I don't have time right now to rehash this debate again. using sonnet instead of opus, not having a proper harness and planning/review cycle. I've seen the thing go, I've put out projects in weeks that would have taken months. If you don't believe it has the juice then so be it.

I'm getting inference for free, it's being subsidized.

You're getting pennies of sonnet for free, I'm burning through $3k+ in tokens a month. Although the psychology here is confusing to me. You'd have to consider your time basically worthless to avoid playing $20/month for some opus 5.5 usage instead of sonnet 5.

As I said, if the scaling stops tomorrow then maybe the models simply are not good enough to do this autonomously and other human labor is required to guide them along. If it continues at this rate for another year or two things change dramatically.

If things continue at this rate then OpenAI and Anthropic run out of money, that's kinda the problem.

I don't have time right now to rehash this debate again.

And that's fine, I understand time priorities. But this is, from what I've seen, a pretty typical blow-off when discussing the issues with models. "Pfft I know what it does for me" and not looking at the broader data or reviewing the literature for the downsides. And hey, that might not be a good use of your time! Just please understand where I am coming from, which again is very much not an "AI is useless" perspective. I have to consider how the average user will interface with the product. I don't think [insert Microsoft product] is useless, either, but that doesn't stop me from complaining at you for an hour about inserting pictures into Word being cognizant of the downsides.

using sonnet instead of opus, not having a proper harness and planning/review cycle.

Upthread you joke about "go ahead and stand up any product that would be profitable to run by a wrapper company, make no mistakes." Now, we both know that's a joke, but I suggest that AIs need too much human hand-holding to just be turned loose to solve problems, and when I illustrated this with a personal example, your response is...that I'm not properly hand-holding the AI. And fair enough, I don't disagree, but I think it rather proves my point.

You'd have to consider your time basically worthless to avoid playing $20/month for some opus 5.5 usage instead of sonnet 5.

I believe most AI users still use free plans (to my point about subsidized provision). As it happens, I actually do have access to Opus (and I've had issues with it too). It's just something I use for work and not when I am screwing around with strictly personal stuff.

However, I think this example is salient because "agentic swarms" are going to use more lightweight models to accomplish some tasks instead of doing it all on the latest model. Furthermore, Anthropic advertises Sonnet as a coding model. If your argument is "the models are actually bad at doing the things they are advertised to be good at" then you're agreeing with me that AI is overhyped.

(Which is fine! There's nothing inherently contradictory about thinking that AI is a marvelous tool and also that salespeople overhype things!)

In this particular case, though, the issue wasn't that there was anything wrong with the coding, and I think it proves nothing about that; it was a feature implementation decision.