Making games in Go: 3 months without LLMs vs. 3 days with LLMs

What I like about this post is that it highlights something a lot of devs gloss over: the coding part of game development was never really the bottleneck. A solo developer can crank out mechanics pretty quickly, with or without AI. The real grind is in all the invisible layers on top; balancing the loop, tuning difficulty, creating assets that don’t look uncanny, and building enough polish to hold someone’s attention for more than 5 minutes.

That’s why we’re not suddenly drowning in brilliant Steam releases post-LLMs. The tech has lowered one wall, but the taller walls remain. It’s like the rise of Unity in the 2010s: the engine democratized making games, but we didn’t see a proportional explosion of good game, just more attempts. LLMs are doing the same thing for code, and image models are starting to do it for art, but neither can tell you if your game is actually fun.

The interesting question to me is: what happens when AI can not only implement but also playtest -- running thousands of iterations of your loop, surfacing which mechanics keep simulated players engaged? That’s when we start moving beyond "AI as productivity hack" into "AI as collaborator in design." We’re not there yet, but this article feels like an early data point along that trajectory.

> The interesting question to me is: what happens when AI can not only implement but also playtest -- running thousands of iterations of your loop, surfacing which mechanics keep simulated players engaged?

How is AI supposed to simulate a player, and why should it be able to determine what real people would find engaging?

Game companies already collect heaps of data about players, which mechanics they interact with, which mechanics they don't, retention, play time, etc.

I don't think it's much of a stretch to take this data over multiple games, versions, and genres, and train a model to take in a set of mechanics, stats, or even video and audio to rate the different aspects of a game prototype.

I wouldn't even be surprised if I heard this is already being done somewhere.

> Game companies already collect heaps of data about players, which mechanics they interact with, which mechanics they don't, retention, play time, etc.

Yes, that's how games like Concord get made. Very successful approach to create art based on data about what's popular and focus groups.

Isn't Concord massively unpopular? I'd think that's a terrible example

Edit: yup, it shut down nearly a year ago

I think it was a sarcastic example - in other words, all the data and metrics and trend-chasing in the world is not a replacement for human vision, creativity, and risk-taking.

Was Concord made the way it was because of data? I got the impression that the designers were chasing misguided trends with the art direction, and on top of that the game part was just mediocre.