Making Games in Go: 3 Months Without Llms Vs. 3 Days with Llms
Posted5 months agoActive4 months ago
marianogappa.github.ioTechstoryHigh profile
heatedmixed
Debate
80/100
Game DevelopmentLlmsGo Programming Language
Key topics
Game Development
Llms
Go Programming Language
The author compares making a card game in Go with and without LLMs, sparking a discussion on the role of LLMs in game development and software development in general.
Snapshot generated from the HN discussion
Discussion Activity
Very active discussionFirst comment
1h
Peak period
135
0-12h
Avg / period
22.9
Comment distribution160 data points
Loading chart...
Based on 160 loaded comments
Key moments
- 01Story posted
Aug 24, 2025 at 11:01 AM EDT
5 months ago
Step 01 - 02First comment
Aug 24, 2025 at 12:31 PM EDT
1h after posting
Step 02 - 03Peak activity
135 comments in 0-12h
Hottest window of the conversation
Step 03 - 04Latest activity
Sep 1, 2025 at 12:19 AM EDT
4 months ago
Step 04
Generating AI Summary...
Analyzing up to 500 comments to identify key contributors and discussion patterns
ID: 45004728Type: storyLast synced: 11/20/2025, 8:28:07 PM
Want the full context?
Jump to the original sources
Read the primary article or dive into the live Hacker News thread when you're ready.
So it’s interesting to think about what the gaps are between fulfilling a single prompt and completing a project.
You may as well buy a shooter game starter pack or whatever that can save you >1year of coding, no llm needed.
Code is not a hard part.
Making mechanics fun and good assets is what is hard and takes forever.
Sure you can use llm to write a generic game, but its easier to find same game on github and just use that code, why would you write it again with llm.
But if you mean copying an already successful PC game with AI Slop assets and putting absolutely no thought into what makes the game good, then you probably should work in a field you actually care about instead
Having a good and semi unique idea, is a rare. If I had a great game mechanic idea, the rest would be trivial.
Say you do get a good game loop together that you feel will be successful. You will also now need to loop in art teams for artistic direction, music, character design, etc. A good game loop isnt enough, it needs to be presented in an equally interesting and unique way.
Finally, there is the risk. There is a massive time investment in making games, and you are catering to an audience that is not only accustomed to pirating but finds it morally righteous to steal your work. This is why app developers prefer to make iOS apps. The customers are accustomed to paying and have little interest in pirating.
post-launch and even before that, your job becomes paying and convincing streamers to play your game constantly in the HOPE people start to notice it.
All of this stress and work to hopefully just make an ok amount of money. I have so many excellent games in my steam library by indie devs that gave up after one or two very successful games. And I doubt it's because everything was going so well.
https://steamdb.info/stats/releases/
Which is really easy to argue it's more down to Unity + successors making game dev accessible as it starts in 2015.
No huge spike since Claude code got released or anything like that.
Not really. The jump from 2023 to 2024 is bigger than the jump from 2019-2022 in raw numbers and 2020-2022 in %. So the jump of 3 to 4 years happened in a single year.
Also the jump in 2024 is only around 10-15% more games than we would have expected from the previous trend. Assuming all of that is directly down to AI, I wouldn’t call that an explosion.
From what I’ve seen, most of the growth was in NSFW shovelware and was just people noticing a business opportunity. This also explains why the number it takes in 2025 isn’t showing similar growth.
No we're not. Use Wayback machine or whatever and this year is 1k+ ahead at the same date.
https://web.archive.org/web/20240822090931/https://steamdb.i...
>Also the jump in 2024 is only around 10-15% more games than we would have expected from the previous trend. Assuming all of that is directly down to AI, I wouldn’t call that an explosion.
How many games do you imagine can be released per day even with the help of current Sota LLMs ? Nevermind the fact that you have to pay $100 to distribute your game on Steam. You're not making a game you'd pay $100 to distribute in 3 days, LLM help or not.
But fair, exploded is probably overstating it.
>How many games do you imagine can be released per day even with the help of current Sota LLMs ?
Given the number of people who want to make games—if code is the bottleneck, and LLMs can really make you hugely more productive, I’d expect to see an actual explosion.
My experience is that neither of those assumptions are true though.
Game development is not a zero sum game. There can be multiple bottlenecks or difficult hurdles.
>and LLMs can really make you hugely more productive, I’d expect to see an actual explosion.
Well growth was double the previous year. Maybe you might not call that an explosion, it's still a very noticeable uptick.
I think it’s much more likely that LLMs don’t actually boost productivity all that much.
Just look at something like ludum dare and all the top entries (out of thousands of games submitted) are all usually quite polished given the timespan.
The open secret is that they might not start coding or building assets until the start time, but they have spent a lot of time thinking about the ideas before then (even when the "theme" isn't known before hand people tend to make ideas fit theme with tweaks), which just speaks to the "code is not the bottleneck" thesis.
1: Even with AI, it's a lot of work to make a full game. When most people think "I have a cool game idea", they're usually imagining something polished and non-trivial, possibly 3d. You could make a short text adventure in a few days with AI, or a very simplistic 2d game, but anything more ambitious (like 3d) is going to take a lot more effort.
2: Releasing on steam requires you to pay $100. I imagine this is a substantial deterrent for "3-day projects", unless you think it'll sell $100 worth.
3: There's more to game development than creating assets and writing code. The author of the article recreated an existing game, which sidesteps one of the most difficult parts of gamedev: design. Creating a compelling game is surprisingly difficult. Granted, you don't need a compelling game in order to release on steam, but I myself have made many prototypes over the years which I've abandoned because the idea just wasn't as interesting as I thought it would be.
4: I've made a few prototypes with AI assets, and one issue I frequently run into with image generation is: it still takes a fair amount of work to generate the same character in different poses, facial expressions, outfits, etc.
5: There is still considerable prejudice against using AI to make game assets. I think some people (myself included) are hesitant to release a game with lots of AI generated assets at the current moment, for fear of public backlash. Eventually that will calm down and it will become more socially acceptable to use AI to generate game assets.
I am bullish about AI improvement over the next decade, and I think we'll gradually see all of these issues resolve themselves as AI improves. But at the present moment, it's not quite as easy as the article makes it seem.
This is mostly from artists themselves. Most people are ok with even fully generated content if it's fun and interesting. Anyway, solo developer cannot afford even single artist, musician, writer.
That's where LLM helps. I recently tried GPT5 for story telling. Gave it a single image (in a bar, women, man, and a gun) and asked for a short story. Then asked for the next part 6 times. Every time at the end for illustration. The result was consistent and readable. Images generated had even similar faces. Remember, that was a problem with earlier models. I'm sure this will be used fill Amazon's bookshelves.
Also the idea that a dev who could making a game in 24 hour would create something professional and polished in 3 days is a joke. The answer to “where are all the games” is simple: LLMs don’t actually make a huge impact on making a real game.
…Joking…. For now
Watching LLM generating the code doesn't help with producing the dopamine.
Both groups wanted to make games.
All of these take time and many of them are iterative processes where you might not even know if it fits or is right before multiple tries.
There are a bunch of games made using heavy gen ai but it is usually for art and dialogue. Most players can tell quickly and drop the game. Games are fundamentally creative things and most interesting art work was not done in 5s with a prompt.
I thought this was the start of a joke or something, I guess if you use LLMs you are a "LLM lover" then.
Also, a refactor is by definition rewriting code without changing the behaviour. Worth knowing the difference.
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.
Each one would require a different kind of model and model technique to make, so I wouldn't be surprised that ChatGPT has issues with it. A sprite animation loop would be better done by a potentially specialized video-oriented model, for example, and the current image and video models are barely trained on that kind of video data.
It looks like retrodiffusion.ai in particular has something close.
We definitely saw an explosion of good indie games by around early half of 2010s. Whether it had anything to do with Unity is another moot point.
Maybe something else is currently holding back another bunch of good ideas in gaming. Once another threshold gets lowered, we will see another wave of good games enabled by by that, and a return to the average rate of creation again.
In the case you're working as part of team large enough to have dedicated programmers, the majority of the roles will usually be in content creation, design and QA.
How is AI supposed to simulate a player, and why should it be able to determine what real people would find engaging?
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.
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.
I think what the previous comment meant was that there is data on how player play, and that tends to be varied but more predictable.
AI/fuzzers can't get far enough in games, yet, without a lot of help. But I think that's because we don't have models really well suited for them.
Edit: yup, it shut down nearly a year ago
Compare that to Helldivers 2 (online-only live service game, same platforms and publisher) which had a lot of personality (the heavy Starship Troopers movie vibe) and some unique gameplay elements like the strategems.
And sometimes it works; Apex Legends came out of nowhere and became one of the big live service titles. Fortnite did a battle royale mode out of nowhere and became huge.
Everything is measured and analysed and optimised for engagement and monetisation.
When you have 200 people making a game, "luck" or "art" doesn't factor in at all. You test, get data, and make decisions based on the data, not feelings.
Solo devs can still make artsy games and stumble upon success.
Where we used AI (machine learning, not LLM) was in terms trying to figure out what kind of human you would want to play with. We also used machine learning to try figure out what cohort of players you were in so we could tweak engagement.
Where LLMs could really shine, in my opinion: Gamers love to play people, not AI (now). People are unpredictable, they communicate, they play well but in ways a human could (like they don't have superhuman reflexes or speed). You can play all kinds of games against AI (StarCraft, Civilization, training of all kinds of FPS) but it isn't fun for long because you see the robotic patterns. However, an LLM might be able to mix it up like humans, talk to you, and you could probably make it have imperfect reaction time, coordination, etc. That would really help a lot of games that have lulls in human player activity, or too much toxicity.
I would be shocked if some games aren't doing this now. It seems like it still be hard to make a bot seem human, and it probably only works if you sprinkle it in.
Edit : oh yeah. A quick google search proved it : https://marvelsnapzone.com/bots/
Whether that set is actually useful is a separate issue but someone is trying this over there for sure.
I'm sure you could conjure up any number of ways to do that, but they won't be trivial, and maintaining those tests while you iterate will only slow you down. And what's the point? Even if the unit-move-and-attack test passes, it's not going to tell you if it looks good, or if it's fun.
Ultimately you just have to play the game, constantly, to make sure the interactions are fun and working as you expect.
You can easily write a 'simulation' version of your event loop and dependency inject that. Once time can be simulated, any deterministic interaction can be unit tested.
You're right that "unit test" has taken on another, rather bizarre definition in the intervening years that doesn't reflect any kind of tests anyone actually writes in the real world, save where they are trying to write "unit tests" specifically to please the bizarre definition, but anyone concerned about definitional purity enough to quibble about it will use the original definition anyway...
You use a second enemy that spawns, moves towards the "enemy", and attacks.
Like letting speed runners skip half your game. :)
The real reason? It's because writing tests is a different skill and they don't actually know how to do it.
Sounds very much like the description of a big ball of mud.
An interesting gamedev video I saw recently basically boiled down to: "Build systems, not games." It was aimed at indie devs to help with the issue of always chasing new projects and making code that's modular enough to be able to reuse it.
But taking a step back, that very much feels like it should apply to entire games, where you should have boundaries between the components and so that the scope of any such pivot is managed well enough not to tank your velocity.
Other than that, it'd be just the regular growing pains of TDD or even just needing to manage good test coverage - saying that tests will eventually need changes isn't the best argument against them in webdev, nor should it be anywhere else.
I mean, yeah, kinda.
For any given object in the game world, it's funnest for that object to be able to interact with as many other objects as possible in as many ways as possible. A game object's handles for interaction need to be globally available and can't impose many invariants—especially if you don't want level designers to have to be constantly re-architecting the engine code to punch new holes for themselves in the API. Thus, a lot of the logic in a given level tends to live inside the callback hooks of level objects, and tends to depend on the state of the rest of the level for correctness.
Modularity is a property of high cohesion and low coupling, which are themselves only possible when you can pin down your design and hide information behind abstraction boundaries. But games are a flexible and dynamic enough field that engines have to basically let designers do whatever they want, whenever they want in order for the engine to be able to build arbitrary games. So game design is naturally a highly-coupled, incohesive problem space that is poorly suited to unit testing.
Poorly suited? Perhaps, but so are certain web system architectures as well, neither is impossible to test.
I think Factorio is an example that it can be done if you care about it... it's just that most studios shipping games don't.
https://www.factorio.com/blog/post/fff-438
https://www.factorio.com/blog/post/fff-366
Of course, in their case it can actually be justified, because the game itself is very dependent on the logic working correctly, rather than your typical FPS game slop that just needs to look good.
https://www.youtube.com/watch?v=AmliviVGX8Q (kovarex - Factorio lets fix video #1)
And note, this is not AI as in asking an LLM what to do, this is more classical machine learning and deep learning.
Games have goals, and players are prone to 'optimising the fun out of games', by doing some save strategy over and over again to reach that goal, even if it's not fun. Think eg grinding in an RPG, instead of facing tough battles with strategy and wits and the risk of failure.
Even if AIs are terrible at determining what's engaging, you can probably at least use them to relatively quickly find ways that you accidentally opened that let players get in the way of their own fun.
But we did? We've come a long way from the limited XBLA catalog. It didn't happen overnight, but doubtless we wouldn't have the volume of games we have today without Unity, Godot, Gamemaker, Renpy, RPG Maker...
I'm not sure the 2 of you are disagreeing. We definitely saw an explosion of indie games. In 2010, there were less than 10 indie games released on steam per month. By 2022, there were ~500/mo, and today there's ~750/mo (I expect that the 250/mo jump around 2022 can likely be attributed to LLMs).
What's hard to say is if this increase significantly increased the number of good games. Mostly because "good" is highly subjective, but also, I think something else happens. I've been playing games for the better part of 40 years, and what I noticed, is that in that time, the number of must play games each year has largely gone unchanged, despite the industry being orders of magnitude larger than it was 40 years ago. But that is also tricky, because 2 things happen every year, our standards get higher, and our preferences get more refined.
https://steamdb.info/stats/releases/?tagid=492
Think of the negative reputation the Unity engine gained among gamers, even though a lot of excellent games and even performant games (DSP) have been made with it.
More competitors does also raise the bar required for novelty, so it is possible that standards are also rising in parallel.
Unity + Steam just makes this process a bit easier and more streamlined. I think the new thing is that as well as the dickwads who are trying to rip people off, there are well-intentioned newbie or indie developers releasing their unpolished attempts. These folks couldn't publish their work in the old days, because making CDs costs money, while now they can.
I don’t think we would’ve seen a Hollow Knight without Unity, built by a team of 2-3 devs.
A 90s PC can't do a complex 3d engine because it lacks the grunt. A 2020s game dev can't do a complex 3d engine themselves because they don't know how to do complex 3d.
Maybe it only got visible to the consoles generation around the time of XBLA arcade, and even that was already predated by PS Yaroze and PS2Linux efforts.
Before Unity, we had SDL, Ogre3D, SFML,... but naturally all of those require more coding skills than engines designed with UI workflows in mind.
This is not true at all. I have never worked on games and it will take me quite a while (even months) to write a "basic" game. While I know a lot of good practices about software development and decade+ of FAANG experience, I don't know the intricacies or even the basics of game development.
I recently experienced this for a different usecase. As an experienced backend developer, I wanted to automate some javascript/browser stuff. I tried on my own for 2-3 days and had couple of prototypes but nothing actually worked. I spent 2 hours with an AI and I had a working solution. We even iterated together quickly and solved some runtime issues and the solution is working for me seamlessly now.
So, I definitely see value of AI even for coding for experienced developers like myself.
You're contradicting yourself. I promise it wouldn't take you months, unless you're just a really bad developer.
And that's the part AI is not going to be able to help you with.
Just think of the speciality in which you aren't an expert, javascript/storage/networking ...
It's not that difficult to get a base level game up and running; ESPECIALLY with modern tooling.
It can do this. From Atari games to StarCraft this has been a thing since before LLMs.
> surfacing which mechanics keep simulated players engaged
This it's unclear how to operationalize. Among other things, not all games appeal to all people.
AI is insane. It can do like 10,000 actions per second lol
https://youtu.be/0p34y7X0VCM?si=GSAjOyRmK6kNmYdx
And this isn't surprising: git-style revision control hit the scene almost 20 years ago, it was like 5 years until it was totally dialed in anywhere, another 5 before elite companies had it totally figured out, and its been slowely diffusing since, today its pretty figured out. And this is harder to use right than git.
I think it would go faster actually if every product release, every OSS tool, every god-damned blog post wasn't hell bent on saying "its done, its solved, old way cooked, new world arrived".
We're figuring it out and it takes time. That's OK.
If it was done, then we'd be drowning in great software. We're not, we're breaking even, which is impressive for a big new thing 1-2 years in.
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".
Doesn't look exactly that to me. The author built a server, studied React, built a frontend, made the card game work.
Then, with most bits needed for a card game already in place, he asked Claude to alter the existing code to implement a different card game. Understandably, it took much shorter. But it would also take much shorter if a human engineer did the same.
In traditional business apps, your goal is to make your app work and look intuitive enough for a human to use. When developing a game, you have a few extra goals, it also has to be fun, rewarding and different enough from other games that came before. It feels like the former group will be much easier to judge by non-humans than the latter.
I think this is the core insight. An AI will not be able to experience a game (or anything else for that matter) remotely in the same way that a human can experience it. It might be able to guess, based on human rankings of other similar games. But AI will never be able to actually have fun playing your game.
This concept will define the workforce that comes out of this AI boom. Maybe an AI can write a document or code like a human, only based on past samples of similar behavior, but it won't be able to synthesize exactly what it means to be a human. The human element will still need to be traded on. Your value as a human cannot be replaced, you might just have to think differently about that value.
more like, more than 5 seconds.
LLMs are only different because the interface is more accessible. But all the same problems are still there. AI is not a panacea.
[1] https://www.reddit.com/r/ProgrammerHumor/comments/1mudy12/th...
Much the same as we do today in games and film both, something saccharine and mediocre built to appeal to a wide majority. Worse, if this process becomes streamlined and widely accessible, you're competing with a hundred other saccharine and mediocre built to a wide majority games. AI generated shovelware, it's like the shovelware of today where anything remotely popular generates dozens of cheap clones, but with AI.
The best games take risks and aren't min/maxed.
65 more comments available on Hacker News