I’ve been a frontend developer for 6 years, and when I first tried to hand my apps over to AI agents, they kept breaking everything.
I realized the problem wasn't the LLM's intelligence—it was our UI "physics." We build UIs for humans who fill in the context themselves. For AI, a button is just a meaningless callback.
I’m proposing a shift from imperative event handling to a Deterministic Coordinate Space. By treating state changes as vectors in a domain space, I managed to:
1. Get consistent O(1) performance (2 LLM calls regardless of task complexity).
2. Stop "Context Drift" where agents forget the original intent.
I've open-sourced the core architecture (Manifesto) and would love to hear what you think about building "AI-native" software environments.
I realized the problem wasn't the LLM's intelligence—it was our UI "physics." We build UIs for humans who fill in the context themselves. For AI, a button is just a meaningless callback.
I’m proposing a shift from imperative event handling to a Deterministic Coordinate Space. By treating state changes as vectors in a domain space, I managed to:
1. Get consistent O(1) performance (2 LLM calls regardless of task complexity).
2. Stop "Context Drift" where agents forget the original intent.
I've open-sourced the core architecture (Manifesto) and would love to hear what you think about building "AI-native" software environments.