Stages: rename titles, fix execution order, remove all numbered references

projects/passepartout/architecture/knowledge-layers/_index.org

@@ -124,7 +124,7 @@ The provenance store must be populated with validated data before it can enforce
 
 3. **Validation through use.** Every time the system runs a computation and receives experimental feedback (or the user provides a measurement), the comparison is recorded. Disagreements between prediction and measurement trigger parameter updates. Over hundreds of comparisons, the provenance store's confidence intervals tighten.
 
-4. **Community amplification (Stage 1+).** Through the social protocol, instances share validated parameter sets with provenance chains. A force field validated by one instance for ethanol and another for DMSO accumulates a broader validity envelope than either alone. The network effect compounds the cold-start investment.
+4. **Community amplification (Social Protocol onwards).** Through the social protocol, instances share validated parameter sets with provenance chains. A force field validated by one instance for ethanol and another for DMSO accumulates a broader validity envelope than either alone. The network effect compounds the cold-start investment.
 
 The cold start never reaches the same confidence as a mature instance with years of experimental feedback. But even a seeded provenance store with provisional parameters is strictly better than a system with no provenance — because the provisional parameters are explicitly tagged as provisional, and the user can see the confidence for every result rather than trusting a single unmarked number.
 
@@ -132,15 +132,15 @@ The cold start never reaches the same confidence as a mature instance with years
 
 The knowledge-layers infrastructure is staged, not all-at-once:
 
-- **Stage 0 (current).** The probabilistic oracle exists (the LLM). The provenance store does not. The deductive engine partially exists through Hermes skills (symbolic gate rules as Python, not ACL2). The empirical layer is invisible — the LLM reasons about chemistry, biology, and engineering using training data alone, without systematic provenance.
+- **Development (current).** The probabilistic oracle exists (the LLM). The provenance store does not. The deductive engine partially exists through Hermes skills (symbolic gate rules as Python, not ACL2). The empirical layer is invisible — the LLM reasons about chemistry, biology, and engineering using training data alone, without systematic provenance.
 
-- **Stage 1 (social protocol).** The provenance store prototype can be introduced as a side effect of signed messages and data exchange. When instances share a validated parameter set, the message carries a signature and source. The receiving instance stores it with provenance. Natural crawl before full infrastructure.
+- **Social Protocol (social protocol).** The provenance store prototype can be introduced as a side effect of signed messages and data exchange. When instances share a validated parameter set, the message carries a signature and source. The receiving instance stores it with provenance. Natural crawl before full infrastructure.
 
-- **Stage 2 (gate as software).** The provenance store becomes operational infrastructure. The gate checks scientific validity alongside security policy. The provenance store integrates with the Knowledge subsystem as a structured data store — the symbolic index holds formal facts; the provenance store holds empirical parameters. Same storage mechanism, different data type.
+- **Neurosymbolic Agent (gate as software).** The provenance store becomes operational infrastructure. The gate checks scientific validity alongside security policy. The provenance store integrates with the Knowledge subsystem as a structured data store — the symbolic index holds formal facts; the provenance store holds empirical parameters. Same storage mechanism, different data type.
 
-- **Stage 3 (Lisp machine).** The symbolic engine is native in one address space. ACL2 runs at hardware level. The provenance store becomes a native Lisp hash table with persistence. The gate checks validity predicates in the evaluation loop itself. The LLM proposes model selections; every proposal is verified against the provenance store before execution. All three layers in one address space.
+- **Lisp Machine (Lisp machine).** The symbolic engine is native in one address space. ACL2 runs at hardware level. The provenance store becomes a native Lisp hash table with persistence. The gate checks validity predicates in the evaluation loop itself. The LLM proposes model selections; every proposal is verified against the provenance store before execution. All three layers in one address space.
 
-- **Stage 4+ (in-process inference).** The LLM moves in-process. All three components share one address space. No IPC between them. The query cycle is: LLM proposes → symbolic engine checks against provenance store → if valid, execute → if invalid, return to LLM with diagnostic. This loop runs at native speed.
+- **AI Inference onwards (in-process inference).** The LLM moves in-process. All three components share one address space. No IPC between them. The query cycle is: LLM proposes → symbolic engine checks against provenance store → if valid, execute → if invalid, return to LLM with diagnostic. This loop runs at native speed.
 
 * What This Changes in the Architecture