You own Quadrants end to end: the API, the IR and lowering, the optimization passes, the numerical primitives, and the roadmap.
Our ultimate objective: engineers write for readability and maintainability, never for performance. They write the version of an algorithm they are most comfortable with, and Quadrants rebuilds it into kernels that run as if an expert had hand-tuned them. Performance is the compiler’s job, not theirs. Getting there is a frontier problem, part research and part engineering, and we intend to define the state of the art on it, relentlessly pushing the limit further.
It calls for two things at once: the low-level GPU and compiler skill to make a single kernel optimal, and the ability to keep the whole system coherent as it grows.
The core tradeoff is settled: usability comes first. When usability and performance collide, usability wins, unless the cost is severe. We will limit what the system supports to go fast (static shapes and fixed-size allocation baked into kernels, say), but never the convenience of the API itself. Experts who want maximum performance and full control over the generated code get lower-level escape hatches, down to inline assembly, C, or PTX.