For sure it was overkill/not the most efficient approach - really I was more just curious if it would work. The answer was "kind of", but even that is pretty amazing. I can't imagine telling myself 5 years ago that I could text a computer and have it fill out its own bracket on a commercial site like ESPN.
its going to be cool when you put in your todo list in the morning that you need to fill out your espn bracket and by lunch your agent will have 3 different versions ready for your review
Really cool idea. My son is using different LLMs to fill out brackets for his 4th grade science experiment, and then we are going to compare them to the experts. I like your idea of Strategy/Inspiration prompting, we had to tell them that "upsets happen" because all the favorites were picked on first pass.
Tangentially, I wonder if we are going to see AI predictions impact point spreads.
> This is a known limitation with small LLMs (0.6B-1.2B) doing tool calling.
To me this is this nut to crack, wrt tool calling and locally running inference. This seems like a really cool project and I'm going to dive around a little later but if it's hallucinating for something as basic as this makes me think it's more of POC stage right now (to echo other sentiment here).
That's a fair read. Tool calling reliability with sub-4B models is
genuinely the hardest unsolved problem in on-device AI right now.
The inference engine (MetalRT) is production-grade, the pipeline architecture
is solid, but the models at this size are still the weak link for
complex tool routing. Larger model support (where tool calling is
much more reliable) is next on the roadmap. Please stay tuned!
It needs a canonical source of truth, something isolated agents can't provide easily. There are tools out there like specularis that help you do that and keep specs in sync.
One example: I let the agent culminate the essence of all previous discussions into a spec.md file, check it for completeness, and remove all previous context before continuing.
Does fastlane still hang for a little before every command? I used to optimize build pipelines for a large company's iOS teams and it always seemed to stall for a little before doing the work. We eventually moved to Xcode Cloud (mainly to avoid code signing) and ran xcodebuild directly.
reply