Framework
Deterministic Core, LLM Edges
Run the same compute twice and get the same answer twice. Physical products demand reproducibility. Large language models, left unguarded, cannot guarantee it.
How it works
- 1All geometry, physics, and manufacturability computation runs deterministically on Encube's GPU-accelerated spatial compute engine.
- 2LLMs are reserved for translation and explanation: 'explain it like I'm five,' 'do a deep dive,' 'summarize this drawing.'
- 3LLMs never touch the math, the stress calculations, or anything irreversible.
- 4Stochastic answers that drift by 0.1 in software produce a slightly quirky chatbot reply. In hardware, they produce a faulty part.
Hear it on the podcast
The Physicist Building a Compiler for the Real World | Hugo Nordell, EncubeListen to the episodeMore from this episode
The Three KPIs That Actually Matter in HardwareMost hardware teams track the wrong numbers. Hugo's framework focuses on the three levers that actually compound into competitive advantage.Shift LeftSurface trade-offs and manufacturability problems early in the design process, when they are still cheap to fix. By the time you reach production, the cost of a change can be measured in months.The Hardware CompilerSoftware AI agents are powerful because they can self-correct — there is a right answer and a fast feedback loop. Hardware never had that. Encube is building the equivalent.Zero to One Before Zero to One HundredThe dream of AI capturing decades of tribal engineering knowledge is real — but it is a future state. You cannot skip the unsexy infrastructure work that makes it possible.The Conductor ModelWhen computation takes over the heavy lifting, the engineer stops being a button pusher and becomes an orchestrator — exploring many design paths in the time it used to take to explore one.
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