AI is built on silicon. The world can’t design enough of it.
ChipGPT is the foundation for designing silicon with AI — higher quality, fewer bugs, and far greater speed.
Every wave of AI runs on silicon.
Physical AI, robotics, the way whole industries and societies are reorganizing around intelligence — all of it is built on silicon. Demand for it is compounding faster than any technology before it.
But designing silicon is a scarce, specialized craft.
There will never be enough high-quality silicon engineers to design all the chips the AI era needs — not fast enough, not affordably enough, not at the energy efficiency the world requires.
The binding constraint on the AI buildout isn’t fabs or capital. It’s engineering.
So silicon has to be designed with AI.
Not to replace the engineer — to multiply them. Four things have to change at once:
A full-stack foundation for AI-designed silicon.
Not a single tool, and not a fixed menu of agents. A stack — built from the memory up — that any design org can stand its own AI co-workers on.
Data & memory
Ingest a design org’s entire history — RTL, bugs, specs, reports — and make it recallable. Vectorized, chunked, and optimized for prompt-efficient retrieval.
Agent infrastructure
The guardrails and harnesses to build silicon agents safely on top of that memory.
Agents
Example co-workers we ship — and the tools for your own engineers to build theirs.
Reliability
Debug tooling, CI/CD, and benchmarks that keep AI-designed silicon trustworthy as it scales.
Engineering RLE: how we evaluate agentsRead it bottom-up: memory is the foundation — nothing runs until it holds — and reliability wraps everything above it.
It already finds real bugs in real silicon.
The first co-workers run today on production open-source chips — every finding proven, formally or in simulation, before it’s ever reported.
A virtual-address check off by one bit — proven with a counterexample.
A missing clock-domain synchronizer — the kind simulation can’t see.
A counter that silently never increments — reproduced in the target’s own testbench.
Accelerate Engineering Through Specialized AI Co-Workers
We work with a small number of design-partner programs each cycle.
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