docs: [verified] connect Strategy through practical Delivery journey

docs/strategy/roadmap.mdx

@@ -15,7 +15,7 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
 
 **Humans direct, guide and review throughout.** Stage 1 standardizes skills in human + AI Agent work across the SDLC. Proven skills, measurements and working practices become the foundation for Stage 2: the future Autonomous Agent in [Target](./target-operating-model.mdx).
 
-Target operating model—not deployed autonomy, an agreed schedule or approved KPI thresholds.
+Target operating model—not deployed autonomy, an agreed schedule or approved KPI thresholds. Stage 1 is useful in its own right; Stage 2 requires a separately justified change in authority, not graduation for using enough skills.
 
 ## Stage 1: Delivery first
 
@@ -33,14 +33,16 @@ Repeat this loop within every phase—not as six global roadmap stages. Skills t
 
 **Understand the engineering path first:** codebase structure and existing principles → system-logic source → tests → builds and packaging → deployments. Inspect actual practices, tooling, controls and problems with the people doing the work, rather than assuming the documented process is the real one.
 
-**Establish the comparison, then engineer skills.** Define metrics/KPIs and a baseline for comparable work before changing it. [Skills Measurement](./measurement/index.mdx) explains collection and calculation. Connect reviewed skills to the engineering path, with clear triggers, dependencies and acceptance checks.
+**Establish the comparison, then engineer skills.** Select relevant metrics/KPIs and a baseline for comparable work before changing it. [Measurement](./measurement/index.mdx) supplies optional definitions; [Baseline](./baseline.mdx) records the actual starting position or gaps. Connect skills to the engineering path, with clear triggers, dependencies and acceptance checks; [Quality](./skills-quality.mdx) qualifies the candidate before bounded real use.
 
-**Use, collect, compare, repeat.** A human works with an AI Agent on real changes. Collect results, friction and feedback alongside quality, cost and verification effort. Compare with the baseline to understand the new current situation; revise the skills and working practices, then run the loop again.
+**Use, collect, compare, repeat.** A human works with an AI Agent on real changes. Collect results, friction and feedback alongside quality, cost and verification effort. Compare with the baseline to understand the new current situation; retain, improve, stop or propose expansion. Changed revisions return to qualification; changed workflows need a fresh comparison.
+
+Follow the **illustrative Delivery workflow** in [Stage 01](./stage-01-skills-adoption.mdx): prepare a bounded code change and regression tests, then hand the exact artifact to independent review. Its dependency diagram shows what passes between activities and who decides whether work can progress. Governance and Measurement support the whole loop; they are not one-time gates.
 
 <details>
-<summary>Supporting gate evidence and hold conditions</summary>
+<summary>Readiness questions behind the roadmap</summary>
 
-These are recommended implementation gates, not assigned human owners, approved thresholds or installed integrations. Agree acceptance criteria for each selected workflow before evaluating it.
+These are readiness questions, not additional roadmap stages. Stage 01's topic pages define the recommended decisions and evidence within existing teams. Designate accountable people and agree workflow-specific acceptance criteria before evaluating; this strategy does not appoint approvers or approve thresholds.
 
 ### Understand the current situation
 
@@ -64,7 +66,7 @@ Use evidence to choose the next SDLC phase; no second or third phase is assigned
 
 ### Prepare for the future Autonomous Agent
 
-Stage 2 builds on proven skills, measurements and working practices—not permission inferred from adoption alone. Before granting scoped execution authority, prove observation and evidence assembly, then proposing and routing work. Recommended controls include exact-artifact approvals, idempotency, duplicate/outage recovery, separation of duties, audit and kill-switch drills. Prove human takeover; never infer permission from missing evidence. The agent ultimately executes and governs the cycle, not only routes tasks, while humans retain direction and review. Keep sensitive decisions human. Changed client, provider, data or authority boundaries reopen the relevant checks.
+Stage 2 builds on proven skills, measurements and working practices—not permission inferred from adoption alone. [Stage 02](./stage-02-autonomous-agent.mdx) owns the separate authority/readiness decision. Recommended controls include exact-artifact approvals, idempotency, duplicate/outage recovery, separation of duties, audit and kill-switch drills. Prove human takeover; never infer permission from missing evidence. Keep sensitive decisions human. Changed client, provider, data or authority boundaries reopen the relevant checks.
 
 </details>