Yongol
Systems Make Genius Shine Brighter
Genius without structure drifts, and structure alone is mediocre. Only when genius and structure multiply does the real value emerge. The ZenFlow benchmark (Claude Sonnet, 32 endpoints, 43 minutes) and historical proof from B-17, Toyota, and WHO checklists all demonstrate the same principle.
Why Drift Never Dies
Drift keeps coming back no matter how many times you fix it. I closed business logic with SSOT, only to watch the same drift climb one layer up -- into the generator that builds that SSOT. I rebuild the answer from entropy upward: why this thing never dies.
Class 4. Decisions Outside Code — yongol and Declarative Full-Stack Control
AI can't distinguish decisions from implementation details mixed in code — that's the root cause of drift. yongol separates decisions into 10 declarative specifications and catches contradictions across layers with 287 rules.
Ratchet Code That Exploits IFEval
LLM sycophancy bias is not a bug but an asset. Combine the instruction-following ability that IFEval measures with deterministic feedback, and even a 4.5B local model produces a convergence loop that generates correct code.
yongol — The Keel of AI-Coded SaaS
Vibe coding collapses at 200 endpoints because AI cannot distinguish decisions from implementation details. yongol shifts the AI workload from code to 10 declarative specs and enforces cross-layer consistency before compilation. Harness with reins.
Feature Chain — Tracing the full stack with one operationId
Which files do you need to touch to modify a single feature? Feature Chain takes one operationId and automatically extracts the entire scope — API spec, DB schema, authorization policy, state diagram, function implementations, test scenarios, and frontend.