I foresee this laying the foundation for whole football stadia filled to the brim with people wanting to watch (and bet on!) competing teams of AI trained on military tactics and strategies!
Soon enough we shall have AI-Olympics! Imagine that, MY FELLOW OXYGEN CONVERTING HUMAN FRIEND! Tens of thousands of robots and drones, all competing against each other in stadia across the planet, at the same time!
I foresee a world wide, synchronized countdown marking the beginning of the biggest, greatest and definitively most unique, one-time-only spectacle in human history!
I know visualization is far from the most important goal here, but it really gets me how there's fairly elaborately rendered terrain, and then the units are just unnamed roombas with hard to read status indicators that have no intuitive meaning. Even in the match viewer I have no clue what's going on, there is no overlay or tooltip when you hover or click units either. There is a unit list that tries (and mostly fails) to give you some information, but because units don't have names you have to hover them in the list to have them highlighted in the field (the reverse does not work). Not exactly a spectator sport. Oh, but there is a way to switch from having all units in one sidebar to having one sidebar per player, as if that made a difference.
I find this pretty funny because it seems like a perfect representation of what's easy with today's tools and what isn't
Yeah, it's all what you get when you basically ask an agent "Build X" without any constraints about how the UI and UX actually should work, and since the agents have about 0 expertise when it comes to "How would a human perceive and use this?", you end up with UIs that don't make much sense for humans unless you strictly steer them with what you know.
Or maybe the simple answer is it looks exactly like the referenced game screeps. Probably a better explanation than hand waving away the faults of an agent.
This is a really interesting direction. RTS games are a much better testbed for agent capability than most static benchmarks because they combine partial observability, long-term planning, resource management, and real-time adaptation.
It reminds me a bit of OpenAI Five — not just because it played a complex game, but because the real value wasn’t “AI plays Dota,” it was observing how coordination, strategy formation, and adaptation emerged under competitive pressure. A controlled RTS environment like this feels like a lightweight, reproducible version of that idea.
What I especially like here is that it lowers the barrier for experimentation. If researchers and hobbyists can plug different models into the same competitive sandbox, we might start seeing meaningful AI-vs-AI evaluations beyond static leaderboards. Competitive dynamics often expose weaknesses much faster than isolated benchmarks do.
Curious whether you’re planning to support self-play training loops or if the focus is primarily on inference-time agents?
> partial observability, long-term planning, resource management, and real-time adaptation
Note, this project doesn't have that best I can tell? Its two static AI scripts having a go. LLMs generate the scripts and they are aware of past "results", but I'm not sure what that means.
Reminds me of Screeps, which I never took the time to fully play, but now I'm wondering if using Claude Code to play Screeps is cheating. Additionally, Screeps lets you host your own backend... What if we started benchmarking coding LLMs with Screeps?... Oh God... If anyone wants to do this let me know, I don't want to burn money on every LLM out there... I'll throw in my Claude Subscription into the contest...
Actually the repo README indeed says its inspired by Screeps. I don't know why they didn't just build on top of Screeps, maybe the idea is to have something anyone can pick up off the shelf for free?
That calculates the ELOs for each AI implementation, and I feed it to different agents so they get really creative trying to beat each other. Also making rule changes to the game and seeing how some scripts get weaker/stronger is a nice way to measure balance.
I'd love to see text-only spatial reasoning. As in, the LLM is presented some kind of textual projection of what's happening in 2d/3d space and makes decisions about what to do in that space based on that. It kind of works when a writer is describing something in a book, for example, but not sure how that could generalize.
believe it or not my 8th grade son was given a US History homework assignment to play Oregon Trail. I was very amused watching him "do his homework". I wonder how an LLM would fare in that game since it's mostly a text choose-your-adventure type interface.
Wouldn't it be interesting if the LLMs would write realtime RTS-commands instead of Code? After all it is a RTS game.
This would bring another dimension to it since then quality of tokens would be one dimension (RTS-language: Decision Making) and speed of tokens the other (RTS-language: Actions Per Minute; APM).
I’ve also been exploring this idea. What if you could bring your own (or pull in a 3rd party) “CPU player” into a game?
Using an LLM friendly api with a snapshot of game state and calculated heuristics, legal moves, and varying levels of strategy in working out nicely. They can play a web based game via curl.
This reminds me of this yearly StarCraft AI competition (since 2010), however I think it uses a special API that makes it easy for bots to access the game
Very interesting project. I'm a bit confused about the lack of hardware specification. The rules make it clear that one's bot has defined deadlines:
> Make sure that each onframe call does not run longer than 42ms. Entries that slow down games by repeatedly exceeding this time limit will lose games on time.
But I'm missing something like: "Your program will be pinned to CPU cores 5-8 and your bot has access to a dedicated RTX 5090 GPU." Also no mention about whether my bot can have network access to offload some high-level latency insensitive planning. Maybe that's just a bad idea in general, haven't played SC in ages.
Yay, I love how we just keep coming up with magic tricks, like toddlers playing with velcro.. These magic tricks do nothing but convince people who don't know any better that LLMs are the real deal, when they simply aren't.
This is just free propaganda for Anthropic && OpenAI who will leverage these (useless) capabilities to convince your boss to give your salary to them, or at least a substantial portion of it.
> I’ve been an engineer for almost 40 years and love seeing what Claude Code can do.
You would say that because otherwise you'd be afraid as being seen as "too old for this job", and hence risking getting kicked out of it all, meaning no future employment opportunities. I know that feeling, because I myself have been doing this programming job for 20+ years already (so not a young one by any means), but let's just cut the crap about it all and let's tell it how it is.
Really? That's a lot of presumption and reductionism to LLMs enthusiasts.
People of varied ages, already leverage LLMs on a daily basis. And LLMs will only get better.
Yesterday, Opus did work for me that would have taken me weeks. And the result was verified with a comprehensive suite of unit tests plus smoke tests by myself. The code looks exactly as the rest of the code in the 10y+ old, hand-written, enterprise project, no slop.
And you actually should be afraid of being left behind in dev related fields if you don't use LLMs. In most areas in fact.
Once the market corrects for LLM assisted production, the expectations will raise. So right now there is a small window to leverage LLMs as a time saving advantage before it becomes the norm and everyone is forced to use it because expecttions will reflect that.
> You would say that because otherwise you'd be afraid as being seen as "too old for this job"
Um... I am still an active reverse engineer of both ring-0 and ring0 applications on both macOS and Windows (I worked on both the VS and Xcode teams). I'm developing a new tool for macOS that allows users to "see behind" active windows without the constant need for cmd/alt+tabbing. My age has zero bearing on my skill set or ability to understand technology. https://imgur.com/a/seymour-r9whXO5
> let's just cut the crap about it all and let's tell it how it is
The reality is, as I said, that this technology exists and it isn't going anywhere. Young people are going to use it as a tool just like we did when GUI operating systems first became prevalent.
I don't even remotely buy into the AI hype but I'm not going put the blinders on either. There is utility in this technology.
I'm pretty young and hate this technology with a passion. I didn't spend 100k on education, and studying for a decade to have my job reduced to being a project manager for a bot or to play with a prompt slot machine all day. This crap is reducing the thing I genuinely love doing more than anything, writing code, into nothing.. Reviewing code that lacks any sweat, any intention. I really can't stand this garbage.
I can't stand you old heads, I'm very happy for you that you got to stash away 40 years of SWE salaries. Its just ladder kicking behavior to be honest. Typical boomer, you got your nut and don't care what happens after.
25% of new college grads in STEM are unemployed and a bunch of companies (controlled by people in your age group) have laid off 400k Americans over the last 16 months while equities and profits are at an all time highs.
The replies : ItS NoT Ai, ItS cUz FrEe MoNeY fRoM CoViD HaS DrIeD uP.
The world is changing and instead of embracing that change (ensuring that you will be the next leader) you are actively fighting against technology?
The world was once entirely analog; generations of analog engineers had to throw away their knowledge and start over during the digital transition. It wasn't always pretty but they did it.
If you can't embrace technological change you might have wasted $100k.
…while burning unreasonable amounts of energy for nothing.
Not a fan. Make games with in-game AIs that are interesting but are not large language models: that's wasteful and lazy. You probably had more large language models put this together for you. Lazy.
Yeah, I guess the tens of thousands of PhDs who are working on LLMs full time are just collectively wasting their lives. Everyone except you is simply too dumb to see it.
I swear people (esp here on HN) are actually blind to the weaknesses of Gemini.
I must be among the handful of people who know how thoroughly lobotomized any AI agent from Google must be given their extremely radical historical and contemporaneous practices of censorship.
I foresee this laying the foundation for whole football stadia filled to the brim with people wanting to watch (and bet on!) competing teams of AI trained on military tactics and strategies!
Soon enough we shall have AI-Olympics! Imagine that, MY FELLOW OXYGEN CONVERTING HUMAN FRIEND! Tens of thousands of robots and drones, all competing against each other in stadia across the planet, at the same time!
I foresee a world wide, synchronized countdown marking the beginning of the biggest, greatest and definitively most unique, one-time-only spectacle in human history!
Keep up the good work!
I find this pretty funny because it seems like a perfect representation of what's easy with today's tools and what isn't
Love the idea though
It reminds me a bit of OpenAI Five — not just because it played a complex game, but because the real value wasn’t “AI plays Dota,” it was observing how coordination, strategy formation, and adaptation emerged under competitive pressure. A controlled RTS environment like this feels like a lightweight, reproducible version of that idea.
What I especially like here is that it lowers the barrier for experimentation. If researchers and hobbyists can plug different models into the same competitive sandbox, we might start seeing meaningful AI-vs-AI evaluations beyond static leaderboards. Competitive dynamics often expose weaknesses much faster than isolated benchmarks do.
Curious whether you’re planning to support self-play training loops or if the focus is primarily on inference-time agents?
You can watch the matche videos from training runs: https://www.youtube.com/@Sscaitournament/videos
I don't think BWAPI has ever integrated modern AI models, but I haven't followed its progress in several years.
Note, this project doesn't have that best I can tell? Its two static AI scripts having a go. LLMs generate the scripts and they are aware of past "results", but I'm not sure what that means.
I was proud for getting the highest-ranked JavaScript-based implementation, but got absolutely crushed by the eventual winner.
1. https://github.com/aichallenge/aichallenge
Actually the repo README indeed says its inspired by Screeps. I don't know why they didn't just build on top of Screeps, maybe the idea is to have something anyone can pick up off the shelf for free?
https://egeozcan.github.io/unnamed_rts/game/
I occasionally run my tournament script: https://github.com/egeozcan/unnamed_rts/blob/main/src/script...
That calculates the ELOs for each AI implementation, and I feed it to different agents so they get really creative trying to beat each other. Also making rule changes to the game and seeing how some scripts get weaker/stronger is a nice way to measure balance.
Funny thing, Codex gets really aggressive and starts cheating a lot of times: https://bsky.app/profile/egeozcan.bsky.social/post/3mfdtj5dh...
Opus needs to learn to kite.
This would bring another dimension to it since then quality of tokens would be one dimension (RTS-language: Decision Making) and speed of tokens the other (RTS-language: Actions Per Minute; APM).
Also there are a lot of coding benchmarks, that way it would test something more abstract, similar to AlphaStar https://en.wikipedia.org/wiki/AlphaStar_(software)
You could just use the exposed APIs of OpenAI, Anthropic etc. and let them battle.
Using an LLM friendly api with a snapshot of game state and calculated heuristics, legal moves, and varying levels of strategy in working out nicely. They can play a web based game via curl.
Maybe they are already doing this? Are there logs of the model's thinking?
Edit: Forgot link: https://davechurchill.ca/starcraft/
> Make sure that each onframe call does not run longer than 42ms. Entries that slow down games by repeatedly exceeding this time limit will lose games on time.
But I'm missing something like: "Your program will be pinned to CPU cores 5-8 and your bot has access to a dedicated RTX 5090 GPU." Also no mention about whether my bot can have network access to offload some high-level latency insensitive planning. Maybe that's just a bad idea in general, haven't played SC in ages.
This is just free propaganda for Anthropic && OpenAI who will leverage these (useless) capabilities to convince your boss to give your salary to them, or at least a substantial portion of it.
I’ve been an engineer for almost 40 years and love seeing what Claude Code can do.
Like it or not, young people will not know a world where this technology doesn’t exist. It is just part of their toolset now.
You would say that because otherwise you'd be afraid as being seen as "too old for this job", and hence risking getting kicked out of it all, meaning no future employment opportunities. I know that feeling, because I myself have been doing this programming job for 20+ years already (so not a young one by any means), but let's just cut the crap about it all and let's tell it how it is.
People of varied ages, already leverage LLMs on a daily basis. And LLMs will only get better.
Yesterday, Opus did work for me that would have taken me weeks. And the result was verified with a comprehensive suite of unit tests plus smoke tests by myself. The code looks exactly as the rest of the code in the 10y+ old, hand-written, enterprise project, no slop.
And you actually should be afraid of being left behind in dev related fields if you don't use LLMs. In most areas in fact.
Once the market corrects for LLM assisted production, the expectations will raise. So right now there is a small window to leverage LLMs as a time saving advantage before it becomes the norm and everyone is forced to use it because expecttions will reflect that.
Um... I am still an active reverse engineer of both ring-0 and ring0 applications on both macOS and Windows (I worked on both the VS and Xcode teams). I'm developing a new tool for macOS that allows users to "see behind" active windows without the constant need for cmd/alt+tabbing. My age has zero bearing on my skill set or ability to understand technology. https://imgur.com/a/seymour-r9whXO5
> let's just cut the crap about it all and let's tell it how it is
The reality is, as I said, that this technology exists and it isn't going anywhere. Young people are going to use it as a tool just like we did when GUI operating systems first became prevalent.
I don't even remotely buy into the AI hype but I'm not going put the blinders on either. There is utility in this technology.
I can't stand you old heads, I'm very happy for you that you got to stash away 40 years of SWE salaries. Its just ladder kicking behavior to be honest. Typical boomer, you got your nut and don't care what happens after.
25% of new college grads in STEM are unemployed and a bunch of companies (controlled by people in your age group) have laid off 400k Americans over the last 16 months while equities and profits are at an all time highs.
The replies : ItS NoT Ai, ItS cUz FrEe MoNeY fRoM CoViD HaS DrIeD uP.
The world was once entirely analog; generations of analog engineers had to throw away their knowledge and start over during the digital transition. It wasn't always pretty but they did it.
If you can't embrace technological change you might have wasted $100k.
Not a fan. Make games with in-game AIs that are interesting but are not large language models: that's wasteful and lazy. You probably had more large language models put this together for you. Lazy.
I swear people (esp here on HN) are actually blind to the weaknesses of Gemini.
I must be among the handful of people who know how thoroughly lobotomized any AI agent from Google must be given their extremely radical historical and contemporaneous practices of censorship.
For complex code I have been having using Sonnet/Opus as usual with a mix of GPT5.3-Codex.
I wonder if an LLM could call on another strategy AI to help.
Maybe the LLM could be more of a coordinator of its own thinking by incorporating other types of AI's.
I haven't.