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Patent Strategy

Likely patentable:

  • Probabilistic-deterministic split with deterministic gates between LLM proposal and execution (vs every competitor using prompt-based guardrails)
  • Foveal-peripheral context model with Org-tree structured retrieval (targets 2,000-4,000 tokens)
  • Merkle-tree memory with copy-on-write snapshots and operation-level undo/redo
  • Gate-to-fact bootstrap with sufficiency criterion (mechanically extracting facts from gate stack data structures)
  • Macro-layer-as-skill bootstrapping architecture (theorem-proving as hot-reloadable skills)

Likely not patentable (known techniques):

  • ACL2 itself (decades old)
  • Screamer for consistency checking (obvious application)
  • Hot-reloadable skills (40 years old)
  • Org-mode as a data format

Strongest single claim: The specific combination of probabilistic model + deterministic zero-token safety gates + Merkle memory + symbolic engine with sufficiency criterion. Each element is known; the combination is novel and non-obvious.

Counterargument: A patent examiner will argue these are standard OS microkernel architecture, locality of reference, content-addressed storage, and capability-based security applied to an AI agent. The defense: they have never been combined in an AI agent, producing emergent effects no single principle produces. These patents would feed into a licensing strategy and create moats against competitors.