nimforum mirror - What A Time To Be Alive

Niminem (orginal) [2026-04-30T17:48:20+02:00] view original

For my fun time I've been working on a game engine in Nim since January of last year. It's built on top of SDL3, using SDL3's new GPU API (this API is bangin you should try it).

Took me a year to learn how to draw a triangle, learn how to draw 'many' triangles, learn how to render 3D geometry like cubes and spheres, texture things, make a controllable camera, load .obj models and manipulate them in 3D space, basic lighting.

Good progress, but that's about all I got after a year.

The game engine I want to create is super demanding. Ultimately it's being built for an ambitious online multiplayer, open world, zombie survival game in VR. The first of its kind.

I need things like stereo instancing, clustered forward renderer, world streaming, GPU-driven rendering, cascaded shadow mapping, and plethora of other optimizations baked in from the very beginning to make the game I want.

With so much to do and so little time, over the last two weeks I decided to take the architecture of what I needed and build out small plans to work on with AI.

I knocked out one or two features a day before bed. Very carefully guiding, reviewing, profiling, testing. Step-by-step, file-by-file.

In just two weeks I implemented more than what I would have been able to do in a year or two. I'm not even kidding. And it's not slop either. You can't slop an engine or it's going to perform like shit.

I had an example with a couple hundred models, a few lights, and other things to sort of 'simulate' a demanding scene environment. My implementation before ran at about 90 FPS. After working with the AI the same scene is at 1200 FPS, capped by my operating system. We have GPU-driven rendering, shadow maps, PBR, so many features that would have taken me no less than the rest of this year to learn and implement it all in an efficient manner.

I'm in such awe right now.

I think I'm actually going to be able to have a very 'usable' engine in a month or so to really start playing around with game development.

I've always tried separated myself from the end goal in things and enjoy the journey. One reason being is that I don't want to get discouraged by fixating the end goal is soooooo far away. I'm sure you know what I'm talking about!

Anyways, man, what a time to be alive. We can actually take our ability to think creatively and logically, problem solve, plan, our engineering expertise, all of these things and combine it with today's frontier LLMs to achieve literal god levels of work in just a fraction of the time.

dneumann42 (orginal) [2026-04-30T18:09:55+02:00] view original

Thats really cool! I am working on something very similar using SDL3 and the GPU api, AI was very useful in finding those little errors that are very hard to spot, like misaligned GPU buffers or flawed shader logic. I had a lot of confidence in AI after implementing the 3d rendering, so I had it try shadow mapping, my geometry is laid out in a unique way because of the type of game I am building, so ill give it some slack, the first pass was pretty great, I saw shadows but there were many artifacts. I had the AI generate images of the scene, then use that to debug the shadow mapping, and thats where I started seeing it fail, I would explain the artifact I was seeing and what I believe it was, it would "fix" it by removing shadows all together and claim success. AI is such a useful tool but I don't think it will solve this shadow problem until I fully understand it myself.

hahaitsfunny (orginal) [2026-05-01T02:17:24+02:00] view original

Enjoy it while it lasts! Copilot just switched to usage based billing. The AI companies have been heavily subsidizing the compute costs these models demand, and I doubt they'll be able to sustain the current business model for very long. There's no clear path to profitability for them either.

kobi (orginal) [2026-05-01T04:24:41+02:00] view original

I think people were afraid of the consequences of depending on it. Now it became more mainstream, so less of that reputation worry. But suppose there's a bug, and you don't understand the academia level code, and suddenly ai costs not 1$ but a 1000$, there's a reputation, responsibility, and possibly even security entering this equation. On the other hand, it's an awesome multiplier. And what if it's really a situation of "enjoy it while it lasts". I recognized this early on, that this option might exist (though open source models exist now). Using it for writing a transpiler, libs for low level embedded domain, and various tools, and computer fields that are massively underutilized (i see great potential in reviving constraints solvers, they're deterministic and can fulfill a lot of what AI is used for today). AI on the other hand, is amazing with pattern recognition, finding themes and correlations, cross reference and intersections. I feel content, analysis, and understanding deep meaning in the world's greatest works is the better goal. But with us, systems and programmers, the whole data world - geopolitics, OSINT, satellite info, - combined, can bring you a bird-view understanding. Same thing with knowledge seeking - compare news outlets and media predictions to what actually happened. See which theories held better against reality. This is also a product that needs the natural language processing expertise of AI. of course i am just pointing to a few observations about where i find ai most useful. i fully endorse your project.

Hobbyman (orginal) [2026-05-01T11:08:14+02:00] view original

@ kobi

When I paraphrase you statement, the marketing process might be: corps give the AI-service for free untill the client is hooked and dependant, and after that crank up the price. User-dependancy is the known and frequently used approach to create (local or temporary) monopolies. Good for the company, but bad for the customer or dependant business-owner.

So that gives the risk of vendor-lock-in. The more important it is (and always was) to:

(let the AI) partition your code in small (or even granular) blocks, that are easier for a human (or alternative AI!) to understand and/or update.

(let the AI) document the code. (besides the standard documentation let the AI document and explain the used code-patterns).

make sure you understand the code at least crudely.

also make sure you have an in-house copy of the code.

check the the small print of the corp that there are no code-appropriating clauses.

On the other hand, the spreading of the tech may render monopolization efforts fruitless.

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