📖 docs: ACMM is the AI Codebase Maturity Model everywhere

docs/content/community/what-is-hive-commons.md

@@ -12,8 +12,8 @@ human, and governance is enforced in code rather than in prose.
 
 Hive is a control layer for running governed fleets of AI coding agents.
 Agents pick up issues, open pull requests, review code, repair CI, and answer
-contributors — under a six-level maturity model (ACMM, the AI-native
-Capability Maturity Model) that decides exactly what they may do and enforces
+contributors — under a six-level maturity model (ACMM, the AI Codebase
+Maturity Model) that decides exactly what they may do and enforces
 it with matching least-privilege GitHub token scopes.
 
 - **Hub and spokes.** A single Go binary that runs as a Kubernetes workload, a

docs/content/hive/architecture.md

@@ -271,7 +271,7 @@ repo outside the configured set. Only `api.github.com` is inspected; `github.com
 
 ## 6. ACMM — controlling agent autonomy
 
-The **AI-native Capability Maturity Model** is the single dial an operator turns.
+The **AI Codebase Maturity Model** is the single dial an operator turns.
 The level maps deterministically to per-agent modes via `DefaultAgentMode`, which
 in turn sets the guardrails in §5. Raising the level is always a human decision.
 

docs/content/hive/overview/intro.md

@@ -112,7 +112,7 @@ Agents run inside tmux sessions managed by the Go binary. The container runs thr
 
 ## ACMM levels
 
-Hive uses an **AI-native Capability Maturity Model** (ACMM) with six levels that control what agents are allowed to do:
+Hive uses an **AI Codebase Maturity Model** (ACMM) with six levels that control what agents are allowed to do:
 
 | Level | Name | Agents | What agents can do |
 |-------|------|--------|-------------------|