docs: [verified] group Strategy into adoption and autonomy stages

docs/strategy/measurement.mdx

@@ -1,7 +1,7 @@
 ---
 id: measurement
 title: Skills Measurement
-sidebar_label: Skills Measurement
+sidebar_label: Measurement
 description: Which KPIs to collect during skills adoption, where the evidence comes from, how to calculate them and when to report.
 hide_table_of_contents: true
 ---

docs/strategy/roadmap.mdx

@@ -68,6 +68,6 @@ Stage 2 builds on proven skills, measurements and working practices—not permis
 
 </details>
 
-**Next:** [Return to the strategy destination →](./target-operating-model.mdx)
+**Next:** [Stage - 01 - Skills Adoption →](./stage-01-skills-adoption.mdx)
 
 </div>

docs/strategy/skills-maintenance.mdx

@@ -44,6 +44,6 @@ Owner ratification is required before adoption. Review earlier after incidents o
 
 </details>
 
-**Next:** [Use exit evidence to choose the next rollout stage →](./roadmap.mdx)
+**Next:** [Stage - 02 - Autonomous Agent →](./stage-02-autonomous-agent.mdx)
 
 </div>

docs/strategy/stage-01-skills-adoption.mdx

@@ -0,0 +1,36 @@
+---
+id: stage-01-skills-adoption
+title: Stage - 01 - Skills Adoption
+description: Build proven skills and measurable working practices through human and AI Agent collaboration, starting with Delivery.
+hide_table_of_contents: true
+---
+
+<div className="strategy-content">
+
+**Human + AI Agent → proven skills and working practices → future Autonomous Agent.**
+
+This first stage of the [Roadmap](./roadmap.mdx) standardizes skills in real human + AI Agent work. It builds the foundation for [Target](./target-operating-model.mdx), while people direct the work, verify outcomes and improve the skills.
+
+## Delivery first
+
+Start with the engineering path: codebase structure and existing principles → system-logic source → tests → builds and packaging → deployments. Understand actual practices, tooling, controls and problems before changing them.
+
+Adoption then extends to other SDLC phases; their order is not yet decided. Delivery keeps improving as adoption expands.
+
+## Repeat within each phase
+
+**Understand the current situation → establish KPIs and a baseline → engineer skills topology → use skills in real work → collect metrics and feedback → understand the new current situation → repeat.**
+
+Skills topology connects what skills exist, how they relate, when they are used and how they work together. Compare accepted outcomes, quality, cost and review effort with the baseline; use friction and feedback to revise the skills and working practices. These are repeating steps within each phase, not additional roadmap stages.
+
+## Put the foundation into practice
+
+- [Governance](./skills-governance.mdx) — define ownership, authority and approval of skills.
+- [Quality](./skills-quality.mdx) — qualify skills and verify their outcomes before wider use.
+- [Adoption](./skills-adoption.mdx) — coach bounded workflows with a supported client and a manual path.
+- [Measurement](./measurement.mdx) — establish KPIs, collect evidence and compare outcomes with the baseline.
+- [Maintenance](./skills-maintenance.mdx) — review feedback, control versions and recover from unsafe updates.
+
+Proven skills, measurements and working practices support [Stage - 02 - Autonomous Agent](./stage-02-autonomous-agent.mdx); adoption alone does not grant autonomous execution authority.
+
+</div>

docs/strategy/stage-02-autonomous-agent.mdx

@@ -0,0 +1,24 @@
+---
+id: stage-02-autonomous-agent
+title: Stage - 02 - Autonomous Agent
+description: Introduce the future Autonomous Agent on proven skills and measured practices while humans retain direction and review.
+hide_table_of_contents: true
+---
+
+<div className="strategy-content">
+
+**Proven skills and measured practices → future Autonomous Agent → human-directed SDLC.**
+
+This future stage of the [Roadmap](./roadmap.mdx) builds on [Stage - 01 - Skills Adoption](./stage-01-skills-adoption.mdx). The destination is [Target](./target-operating-model.mdx): an Autonomous Agent that executes and governs the SDLC cycle, with humans retaining direction and review.
+
+## Build on what has been proven
+
+Carry forward proven skills, measurements and working practices from real human + AI Agent work. The skills foundation provides [governance](./skills-governance.mdx), [quality checks](./skills-quality.mdx), [adoption feedback](./skills-adoption.mdx), [measurement](./measurement.mdx) and [maintenance](./skills-maintenance.mdx); it is not permission to expand authority automatically.
+
+## Introduce authority deliberately
+
+Establish reliable observation and evidence assembly, then proposing and routing work, before granting scoped execution authority. The Roadmap describes recommended controls and hold conditions, including exact-artifact approvals, independent review, recovery and human takeover. Sensitive decisions remain human; missing evidence never means permission.
+
+This is future direction, not deployed autonomy, agreed delivery dates or approved KPI thresholds. The transition depends on reviewed evidence and explicit authority decisions, not adoption volume alone.
+
+</div>

docs/strategy/target-operating-model.mdx

@@ -162,6 +162,6 @@ Success means accepted outcomes with maintained quality, controlled risk and und
 
 </details>
 
-**Next:** [Decide who owns and approves each skill →](./skills-governance.mdx)
+**Next:** [Follow the Roadmap toward Target →](./roadmap.mdx)
 
 </div>