This is a coding agent implementation I am working on, which delivers what this promises (at least on the "lean" part), except it's actually fully open source, and even more lean (few MBs of runtime memory usage).
MIT-licensed, written in C, multi-provider / multi-model, minimalist approach to system prompt and tools (think kinda like pi, but with a bit more "batteries included", like subagents and background tasks out of the box), polished presentation, inspectable (usable transcript view), etc.
They can one shot entire games, with relatively minor issues.
And obviously asking for small code snippets and integrating them yourself has been well supported for five years.
But in Agent mode... not so much. I was asking frontier models to make simple changes to my Pong game (you know like the one from 1972) and it constantly failed to make simple changes or would break something else in the process.
The main issue is that they can't see what they're doing. Actually one of the agents tried playing the pong game by screenshotting every frame, and it ran for about 20 minutes before I realized what it was doing, and told it to calm down.
It takes about 10 seconds to process an image, so it was running the game at 0.1 frames per second... 600x slower than realtime. The technology is not quite there yet.
If your game is something turn-based though, with discrete States and well-defined transitions between them, they can help out a lot more with that.
"I thought using loops was cheating, so I programmed my own using samples. I then thought using samples was cheating, so I recorded real drums. I then thought that programming it was cheating, so I learned to play drums for real. I then thought using bought drums was cheating, so I learned to make my own. I then thought using premade skins was cheating, so I killed a goat and skinned it. I then thought that that was cheating too, so I grew my own goat from a baby goat. I also think that is cheating, but I’m not sure where to go from here. I haven’t made any music lately, what with the goat farming and all."
Compare/contrast: people who develop games on top of high-level genre-specific game engines like RPG Maker are still considered to be "building a game." What's the difference between using a pre-made purpose-fit engine like RPG Maker, vs. asking an AI (or, for that matter, a contracted software company) to build you a custom purpose-fit engine?
as for why stop here yep, the goal is to be able to find the best sweet spot in being self contained v.s. all-in-one bloat ware. for example, we still use a bundled `tmux` skill for the orchestration.
- Ante installs a pinned, checksum-verified official llama.cpp build matched to your machine (Metal on Apple silicon; CUDA, Vulkan, or CPU on Linux) and handles upgrades when the pin changes. - It discovers GGUF files already on disk (~/.ante/models, the llama.cpp and Hugging Face caches), attaches to llama servers already running on local ports, and estimates RAM/VRAM from model size and context window before anything loads. - `ante --offline-model /path/to/model.gguf "prompt"` boots the server, runs the session, and shuts it down. `/offline-mode` does the same interactively; `ante serve --offline-model` loads a model once for many clients. - No API key, no account. Once the model is on disk, inference needs no network at all; set ANTE_TELEMETRY=off and no telemetry is exported either.
On capability, we'd rather publish the number than oversell: we benchmark local models with the same harness and auditable runs as frontier ones, and Qwen3.6 27B (a 17 GB download) scores 56.2% on Terminal-Bench 2.1 across 445 trials (live results: https://antigma.ai/eval). That's a real gap from frontier models. The design bet is that you mix: hosted providers and local live in the same catalog, `/providers` switches mid-session, so sensitive repos or high-volume work go local and hard problems go frontier.
Hosted models work with your own keys or subscription. But nothing about trying Ante requires signing up for anything: download the binary, point it at a GGUF.
Offline mode is under active development and has rough edges with the overview at https://ante.run/local/overview. I'll be in the comments.
> Ante installs a pinned, checksum-verified official llama.cpp
> Ante ships its own inference engine
One could even argue what defines AI instructability is heuristics as opposed to specifics
And you won't get purity tests from the layperson: in the end, you're responsible for the build quality so if you tirelessly labor/oversee those teams you're considered capable; if it ends sub-par, then you're a stooge.
A coding agent is more like a carpenter, a mason, an electrician,... rather than a hammer in that case.
So sometimes when I want to hear what my song COULD be if I were good at every one of those, I will use Suno. But I do not let it change my lyrics, or chose it's own arrangement. I will give it a VERY ROUGH demo (out of key singing, basic drums and strums, and it will "polish" my turds into really shiny turds.