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358 points maloga | 1 comments | | HN request time: 0s | source
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starchild3001 ◴[] No.45006027[source]
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.

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1. moron4hire ◴[] No.45007758[source]
Is that the takeaway? When they say, "I cloned the backend for Truco and gave Claude a long prompt explaining the rules of Escoba and asking it to refactor the code to implement it", that doesn't really make it sound like a good heads-up comparison from which we could then say, "the coding part was not the most significant part of the problem".

I mean, the entire article is problematic as proof of anything. For starters, they didn't go through a design process for a game at all, they copied existing games. Then there are all these weird technical rabbit holes they went down that really weren't anywhere near "simplest path to MVP".

I just don't think there is anything to glean from this article. Like most posts about individual experiences with AI, it's functionally equivalent to, "I had a weird dream last night".