🧬 Methodology
How it was built — constrained evolution, K-NOME programming, and the operational playbook.
The methodology is biological: evolve under constraint, validate against published science, compose from small parts, track everything. Two ideas drive everything else — constrained evolution (remove dependencies, force genuine capability) and K-NOME (AI as collaborator under human constraint, every generation tested against published results).
| I want to… | Read this |
|---|---|
| Understand the core theory | Constrained Evolution — Formal — why removing CUDA produced vendor-independent GPU compute, and other constraint-driven innovations |
| See how AI-assisted development works | K-NOME Programming — the operational model: human domain expertise + AI implementation, every generation validated |
| Start my own spring | How to Start a Spring — the phased playbook: Python → Rust → GPU → composition |
| See what could be built next | Knowledge Commons Targets — 9 domains where public data + cheap hardware unlocks sovereign alternatives |
| Understand the licensing | scyBorg Licensing — AGPL + ORC + CC-BY-SA: three independent nonprofits, no single entity can revoke |
| Explore the theoretical foundation | P vs NP and the Enzyme Thesis — why generation/verification asymmetry matters for computation and biology |