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

projects/passepartout/strategy/adoption.org

@@ -18,10 +18,10 @@ independent dynamics. Each has its own phases, defined by different
 metrics. They run concurrently and reinforce each other, but neither is a
 precondition for the other. Each section below defines its own phases.
 
-Phases are distinct from the architecture's development Stages (Stage 0
-= now/Linux-hosted, Stage 1 = social protocol, Stage 2 = verification
-TUI, Stage 3 = Lisp machine, Stage 4 = inference ASIC). The clock for
-both adoptions starts when Stage 2 ships (TUI complete). See
+Phases are distinct from the architecture's development Stages (Development
+= now/Linux-hosted, Social Protocol = social protocol, Neurosymbolic Agent = verification
+TUI, Lisp Machine = Lisp machine, AI Inference = inference ASIC). The clock for
+both adoptions starts when Neurosymbolic Agent ships (TUI complete). See
 [[id:dc2e4f22-1c4c-5d4a-a151-f96e5d3b0d70][Development timeline]] for the Stage breakdown.
 
 * Social adoption

projects/passepartout/strategy/competitors/rainbird-ai-case-study.org

@@ -79,7 +79,7 @@ Because the LLM never makes a decision — it only translates — there are zero
 | Graph growth | Manual — human experts build and update in Studio | Automatic — autodidactic loop hardens from Gate decisions |
 | LLM role | Natural language translation only | Proposes actions, facts, interpretations; cannot overrule Gate |
 | Audit trail | Proof trees from reasoning engine | Full decision log from every Gate action |
-| Execution environment | Conventional cloud/SaaS | Lisp address space, bare metal at Stage 3+ |
+| Execution environment | Conventional cloud/SaaS | Lisp address space, bare metal at Lisp Machine onwards |
 | Identity | User accounts in SaaS | Self-sovereign DID |
 | Social protocol | None | DIDComm, PDS, relay, compute marketplace, liquid democracy |
 | Openness | Proprietary, closed source | Designed to be open and self-hosted |
@@ -102,7 +102,7 @@ Because the LLM never makes a decision — it only translates — there are zero
 
 * Implications for Passepartout
 
-**Validation.** Rainbird proves the market exists. Enterprises will pay significant sums for deterministic symbolic AI over a natural language interface. Every Rainbird case study — especially in regulated industries — validates the revenue model Passepartout targets for Stage 2.
+**Validation.** Rainbird proves the market exists. Enterprises will pay significant sums for deterministic symbolic AI over a natural language interface. Every Rainbird case study — especially in regulated industries — validates the revenue model Passepartout targets for the Neurosymbolic Agent stage.
 
 **Differentiation.** Rainbird's weaknesses are Passepartout's strengths. The autodidactic loop, the evaluation loop interposition, the social protocol, the Lisp address space, the self-hosted pricing — these are gaps in Rainbird's offering that Passepartout can exploit.
 

projects/passepartout/strategy/domain-sequencing.org

@@ -17,7 +17,7 @@ This is the bootstrap — the system must build itself before it can build anyth
 
 - The gate stack seeds 50-70 entity classes from its own code (files, commands, processes, networks, dependencies)
 - Every git commit, build error, test failure, and shell command is a gate outcome — accumulating toward sufficiency without manual curation
-- The reasoner is born as a Screamer-based CL prototype shared via the social protocol at Stage 1, hardens into the gate at Stage 2, and enters self-improvement under the in-process LLM at Stage 4
+- The reasoner is born as a Screamer-based CL prototype shared via the social protocol at the Social Protocol stage, hardens into the gate at the Neurosymbolic Agent stage, and enters self-improvement under the in-process LLM at the AI Inference stage
 - The social protocol itself is software — its correctness is verified by the same gate that software engineering produces
 
 Sufficiency in software engineering means the system can propose, verify, and apply changes to its own codebase under gate supervision. This is the bootstrap completion signal.
@@ -43,7 +43,7 @@ This is where the verification economy produces real revenue, not just knowledge
 
 4. **First-mover advantage is real.** The first gate configuration for HIPAA risk assessments becomes the template. Every audit that passes against it is a data point. Late entrants must either replicate years of accumulated gate outcomes or buy access to the commons. A proprietary compliance vendor cannot compete with a commons that improves with every customer.
 
-5. **The ontology work can happen in parallel with hardware maturation.** Encoding HIPAA rules as gate predicates is a Stage 2 activity (software layer on conventional hardware). Enforcement at scale — passing a SOC 2 Type II audit — waits for Stage 3 (Lisp machine). But the encoding, testing, and network convergence happen years before the silicon is ready.
+5. **The ontology work can happen in parallel with hardware maturation.** Encoding HIPAA rules as gate predicates is a Neurosymbolic Agent activity (software layer on conventional hardware). Enforcement at scale — passing a SOC 2 Type II audit — waits for the Lisp Machine. But the encoding, testing, and network convergence happen years before the silicon is ready.
 
 **Fourth: Physics, chemistry, and the rest of science can wait.**
 

projects/passepartout/strategy/game-theory.org

@@ -498,7 +498,7 @@ but connected through resource flows:
 
 - **Institutional → Social:** Compliance revenue would accelerate the
   social protocol's development timeline, but the architecture is
-  self-developing after Stage 2 — the bootstrap loop means engineering
+  self-developing after the Neurosymbolic Agent stage — the bootstrap loop means engineering
   does not depend on external funding. Revenue is amplificatory, not
   necessary.
 - **Social → Institutional (late stage):** At Phase 3+, the social
@@ -515,7 +515,7 @@ directions. Institutional success can exist without social success
 without institutional success — the social protocol reaches critical
 mass through pure platform competition, and its development is not
 blocked by lack of institutional revenue because the architecture is
-self-developing after Stage 2 (the agent writes its own code; the
+self-developing after the Neurosymbolic Agent stage (the agent writes its own code; the
 bootstrap loop makes engineering self-sustaining). The coupling is
 amplificatory, not foundational: each side's success makes the other
 more valuable, but neither depends on the other to survive.

projects/passepartout/strategy/hosting-economics.org

@@ -8,7 +8,7 @@
 
 * Assumptions
 
-- Stage 2 instance: one SBCL Lisp process with Gate + PDS + environment in one address space
+- Neurosymbolic Agent instance: one SBCL Lisp process with Gate + PDS + environment in one address space
 - User brings own LLM API key — no AI token cost to the provider
 - Containerized: Docker image running on cloud VMs (AWS spot instances)
 - Instances are embarrassingly parallel — no cross-instance coordination