11 — Implementation Plan
MVP objective
Build a CNS 8.0 prototype that can process a small evidence corpus, produce SNOs, identify productive contradictions, perform proof-constrained synthesis, recover simple latent predicates on synthetic tasks, and emit an orthesis candidate with evidence, proof traces, residuals, and uncertainty recorded.
Phase 0 — Repository skeleton
Deliverables:
cns8/Python package;tests/with deterministic toy cases;configs/cns8_mvp.yaml;- JSON schemas;
- run manifest format.
Phase 1 — Evidence and SNO extraction
Components:
- EvidenceStore
- EvidenceAtom
- SNO parser
- Claim/Relation extractor interface
- citation validator
Acceptance criteria:
- every evidence atom has stable ID and hash;
- missing evidence IDs reject invalid inputs;
- parser handles valid and invalid SNOs;
- citation validity measured per claim.
Phase 2 — Grounding critics
Components:
- entailment scorer;
- source quality scorer;
- access-state validator;
- proof status assigner.
Acceptance criteria:
- strict claims require valid citation and entailment;
- invalid citation causes rejection;
- access states do not masquerade as truth values.
Phase 3 — Chirality and entanglement
Components:
- evidence overlap;
- graph chirality;
- evidence-polarity chirality;
- round-trip language–logic residual;
- Productive Conflict Score.
Acceptance criteria:
- pair selector ranks synthetic productive conflicts above unrelated conflicts;
- high overlap/agreement is not misclassified as synthesis target;
- high contradiction/no overlap is downgraded.
Phase 4 — Tensor proof closure
Components:
- rule registry;
- zero-temperature closure;
- proof trace recorder;
- ZTHR metric.
Acceptance criteria:
- strict claims carry proof traces;
- unsupported claims cannot be promoted;
- closure produces expected atoms on toy rules.
Phase 5 — Residual tensor and predicate invention
Components:
- residual tensor builder;
- factorization sketch;
- latent predicate candidate generator;
- predicate grounding gate;
- PIU metric.
Acceptance criteria:
- synthetic hidden contexts recovered above baseline;
- spurious predicates rejected by grounding/complexity gates;
- residual energy decreases when correct latent predicate is accepted.
Phase 6 — Synthesizer and orthesis loop
Components:
- structured synthesis planner;
- LLM renderer with bounded prompt;
- re-grounding loop;
- round-trip residual scorer;
- orthesis report.
Acceptance criteria:
- synthesized SNO preserves evidence provenance;
- round-trip residual decreases over iterations;
- final strict claims have proof traces;
- unresolved contradictions are reported, not hidden.
Phase 7 — Multiverse and audit layer
Components:
- possible-world generator;
- posterior scoring;
- calibration report;
- audit renderer.
Acceptance criteria:
- worlds include access assumptions;
- posterior report does not replace synthesized SNO;
- final output separates strict, likely, hypothesis, unresolved, and rejected claims.
Engineering stack
Recommended:
- Python for MVP proof algorithms;
- Pydantic or dataclasses for schemas;
- NetworkX for topology;
- NumPy/PyTorch for tensor operations;
- sentence-transformers or equivalent for embeddings;
- NLI model for entailment;
- optional LoRA for extraction;
- simple CLI before dashboard.
CLI sketch
cns8 ingest corpus.jsonl --out runs/evidence.jsonl
cns8 propose runs/evidence.jsonl --out runs/snos.jsonl
cns8 critique runs/snos.jsonl --out runs/critic.jsonl
cns8 select-pairs runs/snos.jsonl --out runs/pairs.jsonl
cns8 synthesize runs/pairs.jsonl --out runs/synthesized_snos.jsonl
cns8 orthesis runs/synthesized_snos.jsonl --out runs/orthesis_report.json
cns8 report runs/orthesis_report.json --format markdown
Build order warning
Do not build a dashboard first. Do not build a large multi-agent runtime first. Build the proof-bearing SNO loop first.