eggplantiny

8 ms·

1.
by eggplantiny 7mo ago
The "consumption" frame is more honest than "craft," agreed. But it falls into the exact same hole. Taste accumulation, attention capture, gift economy, signal fortress—they're all variations of "how do I asset
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by eggplantiny 7mo ago
Haha I agree that my opinion is kind of that But more like ports & adapters for semantic space, not just IO boundaries. If we can abstract the tools one layer further for ai, it might reduce the attention it needs to spend navigating t
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by eggplantiny 7mo ago
I'm looking at this from a slightly different level of abstraction. The CLI approach definitely has practical benefits for token reduction. Not stuffing the entire schema into the runtime context is a clear win. But my main interest li
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by eggplantiny 8mo ago
I broadly agree with the caution against naive "conscious AI" narratives, but I think this essay underestimates a key idea from Hofstadter’s GEB. Hofstadter's claim was not that consciousness is "just computation" i
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by eggplantiny 8mo ago
Hi HN, I've been building autonomous agents and noticed a recurring failure mode: as business logic becomes more complex, even the most capable LLMs struggle to maintain consistency. I realized the problem isn't just the "bra
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by eggplantiny 8mo ago
I see Engram less as a memory efficiency trick and more as an architectural attempt to address *context drift*, which feels like a fundamental issue in current LLMs. As context grows, models are forced to continuously re-derive what should
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Moving Beyond Agent-Centric Design: World-Centric Orchestration for AI(dev.to)
1 points by eggplantiny 8mo ago|1 comments
8.
by eggplantiny 8mo ago
Hi HN, I've been building autonomous agents and noticed a recurring failure mode: as business logic becomes more complex, even the most capable LLMs struggle to maintain consistency. I realized the problem isn't just the "bra
9.
by eggplantiny 8mo ago
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
10.
by eggplantiny 9mo ago
I’ve been debugging LLM-based agents for a while, and I kept running into the same failures: impossible action loops, irreproducible state, and “I have no idea why this happened” moments. This post is my attempt to explain why those failure
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by eggplantiny 9mo ago
This is a 1-page concept describing a formal semantic interface layer that exposes software state, transitions, and action space to AI agents — avoiding DOM heuristics and non-deterministic UI behavior. Includes schema mode, core, and G
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by eggplantiny 9mo ago
"OP here. Currently, most agents rely on computer vision (pixels) or raw DOM parsing. I argue that this is insufficient for deterministic B2B use cases because it misses 'invisible' logic (e.g., why is a button disabled?). Th
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Show HN: Manifesto – An AI-Native UI Framework Intent-to-State, Not Text-to-App(manifesto-ai.dev)
2 points by eggplantiny 10mo ago|0 comments
14.
by eggplantiny 10mo ago
I wrote an essay about why UI generation alone isn’t enough in the AI era. The core argument: modern applications expose almost none of their internal semantics to AI agents. We give agents screenshots, DOM trees, or heuristics… but not the