- LLM proposes code at every bootstrap stage (microcode, CIC kernel,
macro layers, gate rules) — symbolic engine verifies before accepting
- Weak model = more retries (5-15), strong model = fewer (1-3)
Both produce 100% verified output because the symbolic engine catches
all mistakes
- The critical transition: not better LLMs, but the sufficiency flip
applied to hardware. Once enough facts about runtime behavior
accumulate, the system proposes microcode optimizations with zero
LLM tokens.
- Surprise result: a barely competent LLM is sufficient for the full
bootstrapping chain. It's slower and costs more in API calls, but
reaches the same destination.
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