> [I give a small introduction to myself and my own work, that I’m omitting here, as you’re on my website]

kkukshtel: You should keep that info, with links, even if its links to your site. Dont burden the reader.

Edit: I read the first half of the article then skimmed the rest (I dont use LLMs outside of occasional searches).

I've been a gamedev for five years. I have a hunch LLMs will not take over game development because of the necessity to control many, many small details to shape a great experience for the player, and because some parts of development cannot be described with words.

Small details: My hunch is when it comes time to polish and fine tune all the moving parts, this process will remain much faster to do by hand. It will be faster to update a specific field or line of code and test/iterate than to prompt your way through that process (the last 20% of the work takes 80% of the time)

Describing without words: An artist with a vision can only bring that vision to life with body movements. It is not possible to communicate all the details that go into a great piece of art with words. The colors, lines, shapes, positioning, specific emotions, history... is beyond spoken language.

> I stand by a lot of what I’ve said, but am in the process of shipping a project where I’ve also used none of this. I think the scale I’m targeting here is really larger projects.

The author appears to be on track to learn an important lesson about LLMs and art. LLMs have completely solved the coding side of game development. But this was never the hard part. Not even close.

The fixed randomness and determinism thing sounds great on paper (all of this does), but in reality this is an extremely confining way to build a video game. Ensuring you maintain determinism across many platforms is where things get super nasty.

If you want a turnkey AI game development experience, why not double down on diffusion? This sidesteps virtually all of the tooling and integration concerns. There is no game engine to integrate with if you use a diffusion model.

I started coding because of gamedev, seeing this and potentially having some agents take care of the coding part is a blessing. I doubt this works as advertised but imagine iterating on stuff with a couple prompts and you can alt tab back into blender or libresprite. Very cool, lets put economics and employment aside

This matches what I came up with on a small project. The biggest ones being screenshots and separated simulation.

Meta level, just push your agent to make things more legible, it’ll figure it out.

One other observation, remember that your agent is infinitely patient. So prompts like “build an interactive design doc with videos of each game mechanic in the style of Factorio dev diaries” can make reviewing changes easier. The general idea, all the small QoL dev tools that you don’t have time for, you can just spawn a side agent to build; if they are orthogonal to your main thread you can just progress them in the background.

One thing I think game dev has not (AFAIK) invested as much in is observability. There’s a lot of perf instrumentation available in debug builds, but things like measuring DPS, health, etc as an exported metric time series I have not seen before. I think agents will benefit from this disproportionately more than humans, eg for inspecting progression curves and balance.

A lot of the points the author made about game dev with AI are things that I notice in my experience as well. That is why me and a friend started to work on https://folly.gg an AI game maker that internalizes several of these learnings.

I was able to get a decent FPS out of around 40k lines (excluding tooling). Tooling consisted mostly of level editing and asset conversion which I tried to keep out of the main code-base.

"LLMs are Bad At Games"

Oh no they're not. I built dozens of small games for the web and five games in Swift and they're spectacular, getting better since day one. Not like Call of Duty but just fun and bug-free enough to play them every day

I recommend to also take a look at Godogen[1][2] which includes other insights as well. I also tried it to produce 2D animations of fairy tales.

[1] https://github.com/htdt/godogen

[2] https://hn.algolia.com/?q=godogen

AI can definitely do all aspects of game development now, but this advice seems to mostly apply to small indie titles or experiments.

For example, the Thing approach is reasonable for a small game, but it's a dead end for a performance budget or layered subsystems. In a reasonably sized 3D game, iterating and copying 30 subsystems of 1000's of Things is impossible to do in frame time, the only fix is a total rewrite of literally everyThing. That's why there's ECS, SOA, etc. which needs a different kind of harness.

Also, art completely dominates the production cycle of modern games, which (even if AI generated) needs its own category of harness not mentioned here. And AI can be very good at optimizing, but samply won't diagnose your overdraw, and GPU needs its own ablation and attribution.

For the time being there's no panacea and we still need "game developers", though the bar for prototypes (and certain genres) is lowered.