I should note that I'm not the same person that you were talking to you the chain. So I hope we're not mixing conversations and people. I don't think I've said that much in this chain, so I can't answer much.

But sure:

>why do you feel so strongly about LLM products?

Personally, I work in games. So pretty much everything in the discourse of LLMs and Gen AI has been amplified 5x for me. The layoffs, the gamers' reaction to stuff utilizing AI, the impact on hardware prices, the politics, etc.

Theres a war of consumers and executives, and I'm trapped in the middle taking heat from both. It's tiring and it's clear who to blame for all of this. I want all of this to pop so the true innovation can rise out, instead of all the gold rush going on right now.

Also,game code is very performance sensitive. It's not like a website or app where I can just "add 5 seconds to a load time" unless I'm working on a simple 2D game, nor throw more hardware to improve performance. Even if LLMs could code up the game, I'd spend more time optimizing what it makes than it saved. It simply doesn't help for the kind of software I work with.

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Philpax a day ago | parent | next [-]

I have worked in games in the past, and currently work in games-adjacent. I'm sympathetic to the concerns you've mentioned, especially given how controversial it is (the recent reveal of DLSS5, which I find directionally interesting but executed poorly, is but one of many examples.)

From speaking to my friends in the industry, it seems like uptake for code is happening slowly, but unevenly, and the results are largely dependent on the level of documentation, which is often lacking. (I know of a few people using AI for (high-quality!) work on Godot, and their AIs struggle with many of the implicit conventions present in the codebase.)

With that being said, I would say that LLMs have generally been quite the boon for the (limited) gameplay work that I have done of recent. Because the cost of generation is so cheap [0], it is trivial to try something out, experiment with variations, and then polish it up or discard it entirely.

This also applies to performance work: if it's a metric that the AI can see and autonomously work on, it can be optimised. This is, of course, not always possible - it's hard to tell your AI to optimise arbitrary content - but it's often more possible than not, especially if you get creative. (Asking it to extract a particularly hot loop out from the code it resides within, and then optimising that, for example: entirely feasible.)

I think there are still growing pains, but I'm confident that LLMs will rock the world of gamedev, just like they're doing to other more well-attested fields of programming.

[0]: https://simonwillison.net/guides/agentic-engineering-pattern...

	▲	johnnyanmac a day ago \| parent [-]
		>directionally interesting but executed poorly Yeah, that sums up a lot of my thoughts with AI c. 2026. I do take some schedenfreude knowing that AI training also struggles with the utter lack of documentation here. That may be a win in and of itself if this paradigm forces the games industry to properly care for tech writing. >Because the cost of generation is so cheap [0], it is trivial to try something out, experiment with variations, and then polish it up or discard it entirely. Well, that's another thing I'm less confident about. The cost is low, for now. But we also know these companies are in loss leader mode. It'll probably always be cheap for a company to afford agents, but I fear reliance on these giant server models will quickly price out ICs and smaller work environments. That might be something China beats us too. They seem to be focusing on optimizing models that works on local machines out of necessity, as opposed to running tens of billions of dollars of compute. My other big bias is wanting to properly own as much of my pipeline as possible (to the point where my eventual indie journey is planning around OS tools and engines, despite my experience in both Unity and UE), and current incentives for these companies don't want that.

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smj-edison a day ago | parent | prev [-]

Crap, you're right. I swear, tiny usernames is both a boon and a curse...

> Personally, I work in games. So pretty much everything in the discourse of LLMs and Gen AI has been amplified 5x for me. The layoffs, the gamers' reaction to stuff utilizing AI, the impact on hardware prices, the politics, etc.

> Theres a war of consumers and executives, and I'm trapped in the middle taking heat from both. It's tiring and it's clear who to blame for all of this. I want all of this to pop so the true innovation can rise out, instead of all the gold rush going on right now.

That makes a lot of sense. I've been pretty fed up with the hyperbole and sliminess, and I can't imagine how difficult it is to be squeezed between angry gamers and naive and dense executives.

When you say "true innovation", is that in terms of non-AI innovation, or non-slimy AI innovation? I guess I personally still believe that LLMs are useful, but only as another tool amongst many others.

I'm also a big believer in human centered UX design, and it's kinda sad that the dominant experience is all textual.

> Also,game code is very performance sensitive

It does seem like game programming is the last bastion of performance, at least in terms of normal hardware, since the game has to go to the consumer's hardware. The "silver bullet" mentality drives me a little crazy because it clearly doesn't work in all situations.

Anyways, I don't know if this response really has a point, but I wanted to at least acknowledge your experience.

	▲	johnnyanmac a day ago \| parent [-]
		>When you say "true innovation", is that in terms of non-AI innovation, or non-slimy AI innovation? A bit of both. Similar to other tech investment, all the gaming centric accelerators are looking for is AI pitches. Makes me wonder what innovations thr past few years have been overlooked in lieu of the Ai Gold Rush. But I can see the long term (likely 5+ years out) potebtial of Ai as well. Once we stop using it as a means to steal from and remove artists, I can see all kinds of tedious problems with assets that Ai can accelerate. Generative fill is a glimpse of a genuinely useful tool that helps artists instead of pretending to be an artist itself. Can it eventually write performant code? Maybe. The other big issue is that 1) a lot of code isn't online to train on and 2) a lot of that code is still a mess to process, with little standards to follow. Maybe it can help with graphics code (which is much more structured) in the near future.