Merge pull request 'docs: six-month AI Architect strategy, evidence and bounded experiments' (#38) from docs/ai-architect-six-months into main

2026-10-08 10:21:46 -07:00
commit fcaa84f3bf
@@ -81,9 +81,9 @@
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@@ -81,9 +81,9 @@
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@@ -51,7 +51,7 @@
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@@ -65,9 +65,9 @@
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@@ -115,7 +115,7 @@
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@@ -51,7 +51,7 @@
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@@ -65,9 +65,9 @@
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@@ -115,7 +115,7 @@
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@@ -38,7 +38,7 @@
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@@ -70,7 +70,7 @@
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@@ -86,7 +86,7 @@
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@@ -134,7 +134,7 @@
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@@ -28,7 +28,7 @@
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@@ -38,8 +38,8 @@
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@@ -28,7 +28,7 @@
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@@ -38,8 +38,8 @@
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@@ -50,8 +50,8 @@
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@@ -83,8 +83,8 @@
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@@ -50,8 +50,8 @@
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@@ -2,7 +2,7 @@
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@@ -27,8 +27,8 @@
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@@ -38,8 +38,8 @@
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@@ -2,7 +2,7 @@
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@@ -13,7 +13,7 @@
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      "id": "baseline-engineer",
      "from": "baseline",
      "to": "engineer",
      "label": "Problem",
      "fromSide": "right",
      "toSide": "left",
      "route": "straight",
      "width": 4,
      "variant": "default",
      "labelAt": [
        800,
        210
      ]
    },
    {
      "id": "engineer-qualify",
      "from": "engineer",
      "to": "qualify",
      "label": "Agreement",
      "fromSide": "right",
      "toSide": "left",
      "route": "straight",
      "width": 4,
      "variant": "default",
      "labelAt": [
        1600,
        210
      ]
    },
    {
      "id": "qualify-pilot",
      "from": "qualify",
      "to": "pilot",
      "label": "Evidence",
      "fromSide": "bottom",
      "toSide": "top",
      "route": "straight",
      "width": 4,
      "variant": "default",
      "via": [
        [
          2000,
          520
        ]
      ],
      "labelAt": [
        2010,
        535
      ]
    },
    {
      "id": "pilot-decide",
      "from": "pilot",
      "to": "decide",
      "label": "Decision",
      "fromSide": "left",
      "toSide": "right",
      "route": "straight",
      "width": 4,
      "variant": "default",
      "labelAt": [
        1600,
        840
      ]
    },
    {
      "id": "decide-maintain",
      "from": "decide",
      "to": "maintain",
      "label": "Handover",
      "fromSide": "left",
      "toSide": "right",
      "route": "straight",
      "width": 4,
      "variant": "default",
      "labelAt": [
        800,
        840
      ]
    },
    {
      "id": "maintain-engineer",
      "from": "maintain",
      "to": "engineer",
      "label": "Next question",
      "fromSide": "top",
      "toSide": "bottom",
      "route": "straight",
      "width": 4,
      "variant": "default",
      "via": [
        [
          400,
          550
        ],
        [
          1200,
          550
        ]
      ],
      "labelAt": [
        800,
        535
      ]
    },
    {
      "id": "decide-baseline",
      "from": "decide",
      "to": "baseline",
      "label": "New scope",
      "fromSide": "bottom",
      "toSide": "bottom",
      "route": "straight",
      "width": 4,
      "variant": "default",
      "via": [
        [
          1200,
          1150
        ],
        [
          60,
          1150
        ],
        [
          60,
          430
        ],
        [
          400,
          430
        ]
      ],
      "labelAt": [
        620,
        1135
      ]
    }
  ]
 }
@@ -33,9 +33,9 @@
    {
      "id": "engineer",
      "type": "external",
-      "label": "Engineer connected skills",
+      "label": "Choose an intervention",
      "tag": "Owning team + independent reviewer",
-      "sublabel": "Triggers, inputs and output handoffs\nPinned candidate + client + limits\nDeliver: patch and regression tests",
+      "sublabel": "Context, coaching, tooling or skills\nPinned candidate + client + limits\nDeliver: patch and regression tests",
      "pos": [
        200,
        450
@@ -115,7 +115,7 @@
      "type": "backend",
      "label": "Governance + Measurement",
      "tag": "Throughout, not one-time gates",
-      "sublabel": "Named people + controlled authority\nSelected workflow + skill evidence\nKeep populations and gaps explicit",
+      "sublabel": "Left return: changed revision\nRight return: new scope needs baseline\nSelected evidence; no forced rollout",
      "pos": [
        200,
        2500
@@ -33,9 +33,9 @@
    {
      "id": "engineer",
      "type": "external",
-      "label": "Engineer connected skills",
+      "label": "Choose an intervention",
      "tag": "Owning team + independent reviewer",
-      "sublabel": "Triggers, inputs and output handoffs\nPinned candidate + client + limits\nDeliver: patch and regression tests",
+      "sublabel": "Context, coaching, tooling or skills\nPinned candidate + client + limits\nDeliver: patch and regression tests",
      "pos": [
        900,
        100
@@ -115,7 +115,7 @@
      "type": "backend",
      "label": "Governance + Measurement",
      "tag": "Throughout, not one-time gates",
-      "sublabel": "Named people + controlled authority\nSelected workflow + skill evidence\nKeep populations and gaps explicit",
+      "sublabel": "Left return: changed revision\nRight return: new scope needs baseline\nSelected evidence; no forced rollout",
      "pos": [
        100,
        1270
@@ -12,7 +12,7 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
 <div className="strategy-content">
-Establish a starting position for one workflow as adoption reaches it. This is not a mandatory company-wide baseline of every metric in the [Measurement registry](./measurement/index.mdx).
+Establish a starting position for one workflow before choosing an intervention in months 1–2 of the [six-month plan](./roadmap.mdx). Baseline current uneven AI-assisted practice, not an assumed no-AI organization. This is not a mandatory company-wide baseline of every metric in the [Measurement registry](./measurement/index.mdx). The [EXP-01 packet](./stage-01-skills-adoption.mdx) assembles a practical comparison and budget. Departmental role names below are proposed functions to map with the partner team, not verified company appointments.
 <ArchifyDiagram name="strategy-baseline" title="From current workflow through relevant selection and feasible evidence to a starting position and later comparison" story />
@@ -1,7 +1,7 @@
 ---
 id: index
 slug: /measurement
-title: Skills Measurement
+title: Measuring real output
 sidebar_label: Measurement
 description: Optional contracts for workflow effectiveness and skills effectiveness and health, with distinct populations and honest implementation limits.
 pagination_prev: stage-01-skills-adoption
@@ -13,7 +13,7 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
 <div className="strategy-content">
-Start with how work performs today; compare relevant outcomes after introducing skills. Separately assess whether the skills are effective, supported, used and maintained. Registry inclusion does not require a metric to be used, collected or baselined. More adoption does not prove improved work.
+Start with how current AI-assisted work performs; compare relevant outcomes after the selected intervention, whether context, coaching, tooling or skills. Separately assess skill fitness and health only where skills exist. Registry inclusion does not require a metric to be used, collected or baselined. More adoption does not prove improved work.
 <ArchifyDiagram name="strategy-measurement" title="Workflow effectiveness / Skills effectiveness & health" story />
@@ -21,6 +21,12 @@ Start with how work performs today; compare relevant outcomes after introducing
 ## Read a candidate contract
 For the [EXP-01 Delivery hypothesis](../stage-01-skills-adoption.mdx), start with three questions, not all 16 contracts. **Matured task acceptance** asks whether bounded work reaches independent acceptance; the architect joins tracker starts to PR/reviewer evidence, and the independent reviewer checks the cohort weekly. **Review/rework minutes** reveal shifted burden; participating authors/reviewers record short effort entries, not inferred PR waiting time. **Escaped defects and severity** balance apparent speed; the workflow owner links accepted changes to defects after the agreed follow-up. Agree these proposed responsibilities and lawful access in month 2. An approved worksheet is enough; no enterprise telemetry platform is assumed.
 Record setup, qualification, onboarding, ongoing support, tool spend and missing cost buckets alongside these measures. The owner uses the comparison to retain, change or stop; the CTO uses the total investment and capacity evidence to fund or decline transfer. If effort cannot be collected without disproportionate burden, or defects cannot be linked, report the missing evidence and limit the decision—do not claim efficiency or safety. Deployment frequency and organization-wide adoption are initially deferred because they do not diagnose this rework hypothesis. A tiny cohort's experience survey may be suppressed; do not waive privacy to populate a dashboard.
 **Where this misleads:** accepted counts change with task mix, staffing and unfinished work; a fast PR may merely shift checking to reviewers; defects mature later; volunteers and coached tasks are not representative of every team. Keep failed, abandoned and unresolved matured starts, coverage, complexity slices, client/model changes and concurrent process changes visible. Compare the same eligibility, acceptance and follow-up rules before/after; use matched or randomized allocation only when feasible and ethical. Report uncertainty, not a causal ROI claim. Invocation counts, generated lines and individual rankings are not productivity measures. Skill benchmark success does not establish real workflow improvement.
 Each entry explains meaning and applicability, calculation, required inputs and evidence, exclusions, missing-evidence behavior, limitations and implementation status. The two groups below classify every contract by its primary question; conditional reuse never merges populations. A delivery metric need not fit a non-delivery workflow.
 To select a relevant subset and establish actual starting evidence, use [Baseline](../baseline.mdx). Pilot application belongs to [Adoption](../skills-adoption.mdx); ongoing interpretation belongs to [Maintenance](../skills-maintenance.mdx).
@@ -1,7 +1,7 @@
 ---
 id: roadmap
 title: Roadmap
-description: Build proven skills in human and AI Agent work, starting with Delivery, as the foundation for the future autonomous SDLC.
+description: Proposed month-by-month work, capacity, dependencies and decisions for a solo AI Architect.
 hide_table_of_contents: true
 ---
@@ -9,35 +9,45 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
 <div className="strategy-content">
-## Two stages toward Target
+## Six months, two investment decisions
-<ArchifyDiagram name="strategy-roadmap" title="Adopt skills → Future Autonomous Agent" story />
+<ArchifyDiagram name="strategy-roadmap" title="Proposed months 1–4: learn and test; months 5–6: retain or stop, then hand over" story />
-**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).
+**Humans direct, guide and review throughout.** This is a proposed plan, not an agreed schedule or budget. The first decision funds one bounded experiment; the second retains, changes or stops it before any transfer. The [six-month strategy](./target-operating-model.mdx) starts with existing uneven AI-assisted practice, not zero adoption. A Target operating model is only a conditional long-term reference.
-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.
+**Month 1 — Discover and earn trust.** I agree CTO expectations, access and a monthly decision meeting; meet team leads, pair with developers and reviewers across contrasting workflows, and trace recent changes. Output: current-work map, AI/tool/data constraints, evidence gaps and ranked bottlenecks. Dependency: willing access to real work. Decision: select a problem, or continue targeted discovery rather than prescribe skills.
-## Stage 1: Delivery first
+**Month 2 — Agree one experiment.** I recruit one willing team and an independent reviewer, observe a prospective baseline and compare context, coaching, test/review feedback, deterministic automation and skills. Output: the [experiment packet](./stage-01-skills-adoption.mdx), effort cap, acceptance rules and stop date. Dependency: team lead agrees contributions; actual risk/approval owners clear the boundary. No partner, reliable checks or lawful evidence means no live pilot.
-<ArchifyDiagram name="strategy-roadmap-adoption" title="Delivery first → Other SDLC phases, order undecided" story />
+**Month 3 — Work beside the team.** I build and qualify the smallest intervention, pair on bounded changes and collect outcomes plus burden. Output: reproducible examples, failure cases and weekly evidence review. Dependency: independent qualification and explicit pilot permission, not tool installation. Stop unsafe work immediately; fix friction before asking others to adopt.
-Start with Delivery, then extend skills adoption to the remaining SDLC phases. Their order is not yet decided. **Delivery keeps improving as adoption expands.**
+**Month 4 — Compare and choose.** I reconcile matured tasks, defects, review effort, costs and concurrent changes with the reviewer. Output: retain/change/hold/stop recommendation to the workflow owner and CTO. Dependency: comparable matured tasks and reconciled sources. Low task supply or missing follow-up means inconclusive, not success. Only an approved time-and-budget-bounded extension may continue; otherwise narrow or stop.
-## Improve within each phase
+**Month 5 — Transfer selectively.** If value and burden are acceptable, I pair with a voluntary champion and backup and test a second willing team's fit. Output: a team-owned example, support/recovery instructions and a new-scope baseline. Dependency: team capacity and funded upkeep. If absent, improve the first workflow or retire it; no organization-wide training mandate.
-<ArchifyDiagram name="strategy-roadmap-loop" title="Each phase: understand → baseline → topology → use → collect → reassess → repeat" story />
+**Month 6 — Handover and CTO evidence review.** I verify that the team can operate without daily architect help and present outcomes, limits, costs and stopped work. Output: an owned retained workflow or documented stop, plus a prioritized next-quarter proposal. Dependency: independent evidence and actual owner acceptance. The CTO decides the next investment, not an automatic autonomy phase.
-Repeat this loop within every phase—not as six global roadmap stages. Skills topology defines **what skills exist, how they relate, when they are used and how they work together**, including handoffs—not just a catalogue.
+## Delivery first, replication only if earned
-## Delivery in practice
+<ArchifyDiagram name="strategy-roadmap-adoption" title="One willing Delivery team → a separately agreed transfer, or stay and improve" story />
-**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.
+**Delivery keeps improving** whether transfer happens or not. The order of any other workflows is not yet decided. I bring concrete examples to skeptical teams, ask what creates extra work, and accept non-participation. A skeptic can help judge a demo without joining a pilot. If priorities conflict, I ask the CTO for a trade-off, not a compliance escalation.
-**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.
+## Keep one learning loop
-**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.
+<ArchifyDiagram name="strategy-roadmap-loop" title="Understand current AI work → baseline → choose intervention → bounded pilot → evidence → retain, change or stop" story />
-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.
+Repeat the learning loop, not a predetermined tool rollout. If skills are selected, their topology defines what skills exist, how they relate, when they are used and how they work together. Simpler context, coaching or deterministic fixes do not require a skills catalog.
 ## Solo capacity and influence
 Proposed weekly allocation during pilots: two days hands-on pairing/building, one day evaluation/evidence, one day coaching and relationships, and one day sponsor decisions, support and contingency. One active live pilot at a time; a second team starts only after the first is supportable. This is a capacity envelope, not known company availability.
 Ask a partner lead to agree a small pairing slot and independent review time explicitly; record actual effort, not assumed free team labor. Agree a short weekly team check-in and monthly CTO review of evidence, blocked dependencies, spend and the next choice. Seek specialist security/privacy advice only where the selected boundary requires it; preserve independent checks without appointing a committee.
 Trace codebase structure and existing principles → system-logic source → tests → builds and packaging → deployments. Repair critical acceptance/data gaps before live use. Publish short reusable examples and offer office hours; don't become a permanent help desk for more than ten teams. Escalate support demand as an investment choice, never hide it in apparent savings.
 Follow the **illustrative Delivery workflow** in [the experiment packet](./stage-01-skills-adoption.mdx). Its diagram and worked decision keep benefit, burden and safety connected. [Measurement](./measurement/index.mdx) supplies optional definitions; [Baseline](./baseline.mdx) records actual starting evidence. Governance and Measurement are supporting references, not one-time gates.
 <details>
 <summary>Readiness questions behind the roadmap</summary>
@@ -54,7 +64,7 @@ Inventory actual client hosts/builds, provider/data terms, authority and event a
 Close critical gaps such as exposed secrets, unclear approval authority or unreliable acceptance checks. Broader refactoring and non-critical debt can run alongside the selected work. Stage 1 introduces no new privileged autonomous actions.
-### Engineer and evaluate connected skills
+### If skills are the chosen intervention
 Use a small registry, immutable skill contracts, qualified client adapters, evaluations and coaching. Verify the measurement calculations with synthetic fixtures before interpreting real outcomes. Require mandatory safety checks, independent task acceptance, reconciled source coverage and user feedback. Hold or narrow scope if quality or coverage is inadequate; usage alone does not justify expansion.
@@ -64,12 +74,12 @@ Prove canary updates, effective-version readback, version locking, exception exp
 Use evidence to choose the next SDLC phase; no second or third phase is assigned here. Continue the improvement loop in Delivery and every phase already using skills.
-### Prepare for the future Autonomous Agent
+### Consider autonomy only as a separate future option
-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.
+Beyond six months may mean deeper coaching, deterministic tooling or no expansion. If additional autonomous authority solves an evidenced problem, [future options](./stage-02-autonomous-agent.mdx) require a 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>
-**Next:** [Stage - 01 - Skills Adoption →](./stage-01-skills-adoption.mdx)
+**Next:** [Work through one bounded experiment →](./stage-01-skills-adoption.mdx)
 </div>
@@ -11,6 +11,8 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
 **TO-BE · Target operating model — not installed controls or company results.**
 Optional reference when skills are the chosen intervention. The [six-month plan](./roadmap.mdx) starts with willing partners and current AI-assisted practice; department names below are proposed functions to agree, not appointments. The assembled [EXP-01 packet](./stage-01-skills-adoption.mdx) shows first-revision recovery, total effort, an inconclusive bounded extension and a stop decision.
 ## When should a pilot become a team workflow?
 Expand only when a bounded canary produces independently accepted work and useful feedback. Teach people to verify artifacts and recover without AI, not merely invoke a skill. Compare **Workflow effectiveness** with the current-workflow baseline; observe **Skills effectiveness & health** separately as skills enter use. More adoption does not prove improved work, and before/after trends alone are not causal evidence.
@@ -30,7 +32,7 @@ At the agreed review point, the designated Product Engineering workflow owner co
 - **Retain:** useful within the tested scope and supported controls; the designated owning approver records exact-revision approval after independent review and required boundary/support checks, then hands that revision and evidence to [Maintenance](./skills-maintenance.mdx). The pilot decision alone is not general approval.
 - **Improve:** return failure cases and friction to the author and [Quality](./skills-quality.mdx); a changed candidate needs new evidence.
 - **Expand:** propose a new bounded workflow/cohort, revisit [Baseline](./baseline.mdx) and obtain the relevant approval—not automatic organization-wide rollout.
- **Stop or hold:** unsafe behavior triggers containment; insufficient evidence means no benefit claim and no justified expansion. Preserve a manual path.
+- **Stop or hold:** unsafe behavior triggers containment; insufficient evidence means no benefit claim and no justified expansion. Preserve current practice or a safe manual path. Any extension needs a new explicit expiry, capacity/spend cap and attainable evidence question; otherwise narrow or stop, never continue indefinitely.
 The output is a decision record with evidence, scope and remaining uncertainties. Qualification fitness and live outcomes inform it separately; apparent before/after improvement does not establish causality.
@@ -13,7 +13,7 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
 ## Who can approve a skill for use?
-The owning team authors the skill; independent reviewers assess it before exact-revision approval. Data &amp; AI maintains the catalog, while Platform &amp; IT verifies distribution and revocation.
+Use this optional reference only if the [six-month experiment](./stage-01-skills-adoption.mdx) selects skills. The architect can author with a willing team; an independent reviewer assesses the candidate and the actual workflow approver authorizes bounded use. Departmental names below are proposed functions, not company facts or conscripted staff. A reviewed repository entry plus existing controls can support one pilot; no enterprise catalog service is required first.
 <ArchifyDiagram name="strategy-governance" title="An owner proposes; independent review and canary evidence precede approval" story />
@@ -52,11 +52,11 @@ An exception contains its ID, skill/client revision, scope, business reason, ris
 ### Distribution, stale clients and rollback
-Stage a verified bundle atomically, check its digest, load it through the qualified adapter and read back its effective revision. Test already-open sessions; changing files is not proof of reloading instructions. Record immutable last-known-good content and adapter dependencies. Canary upgrades precede wider distribution.
+Stage a verified bundle atomically, check its digest, load it through the qualified adapter and read back its effective revision. Test already-open sessions; changing files is not proof of reloading instructions. Record immutable last-known-good content and adapter dependencies where an approved revision exists. For a first revision, record **N/A: no approved bundle** and the [Quality first-revision rule](./skills-quality.mdx): compare with declared current AI-assisted practice; test disable/remove, invalidate/reload sessions and verify recovery in a pinned clean environment. Independent reviewer acceptance and actual workflow-approver pilot permission are still required. Canary upgrades precede wider distribution.
 A cached verified bundle may support explicitly permitted low-risk work if its model and tool dependencies are available. It does not make a cloud-backed client work offline. Stale or unsupported sessions cannot obtain centrally mediated privileged access. Reconnection revalidates support, revocation and policy before credentials are issued. Central artifact review protects delivery even when a laptop declaration is absent or false; a client report cannot prove which private prompt was actually followed.
-Rollback restores the approved manifest and dependencies, invalidates affected sessions, revokes unsafe revisions, runs a smoke test and verifies effective state. It cannot undo data disclosure or commands already executed. Those require incident response.
+Rollback restores the approved manifest and dependencies when present; first-revision recovery removes the candidate and restores declared current practice without inventing a prior approved skill. Invalidate affected sessions, revoke unsafe revisions, run a smoke test and verify effective state. Recovery cannot undo data disclosure or commands already executed. Those require incident response.
 </details>
@@ -85,7 +85,7 @@ Rollback restores the approved manifest and dependencies, invalidates affected s
 | provenance_license | Origin repository/author, upstream revision, acquisition/review history, rights/license for content and bundled resources |
 | maintenance_date | Last substantive review timestamp plus next review due and trigger conditions |
 | deprecation | State, reason, replacement, migration instructions, consumers and retirement deadline if applicable |
-| rollback | Approved known-good bundle+adapter+dependency digests, revocation/reload procedure and tested evidence |
+| rollback | Approved known-good bundle+adapter+dependency digests when present; first revision: N/A with reason plus tested disable/remove/reload to pinned clean current practice; independent acceptance required |
 | procedure | Prerequisites, bounded steps, expected artifacts, verification, failure handling, escalation |
@@ -11,6 +11,8 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
 **TO-BE · Target operating model — not installed controls or company results.**
 Optional skills reference for a retained intervention, not a six-month obligation to establish a catalog program. Map department names to actual agreed functions. The [Roadmap](./roadmap.mdx) requires funded upkeep and a willing owner before expansion.
 ## What happens when a skill drifts or causes harm?
 Monitor both **Workflow effectiveness** (comparable outcomes, safety, cost and human experience) and **Skills effectiveness & health** (fitness/regression evidence, selection, supported use and substantive review) throughout a revision's life. Use the evidence to improve, retain or retire skills; adoption or current review dates alone do not prove better work. Unsafe behavior triggers containment; a correction returns through independent tests and approval, never automatic reinstatement.
@@ -19,7 +21,7 @@ Monitor both **Workflow effectiveness** (comparable outcomes, safety, cost and h
 - **Named ownership:** Data &amp; AI coordinates catalog health with the owning teams.
 - **Early triggers:** incidents and client, model or dependency changes override the calendar.
- **Recovery is verified:** rollback restores a known-good bundle; it cannot undo disclosure or past effects.
+- **Recovery is verified:** restore a known-good bundle when present; first-revision recovery disables/removes the candidate, invalidates/reloads sessions and verifies declared current AI-assisted practice in a pinned clean environment. Record no-approved-revision N/A and independent acceptance under the [Quality rule](./skills-quality.mdx); recovery cannot undo disclosure or past effects.
 ## Close the loop on the retained workflow
@@ -11,6 +11,8 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
 **TO-BE · Target operating model — not installed controls or company results.**
 **Optional skills reference for the [six-month plan](./roadmap.mdx).** Use this when skills are the chosen intervention, not as a prerequisite for discovery or coaching. Department names denote functions to map to actual willing staff; the architect cannot assign them authority.
 ## What evidence is enough to promote a skill?
 Risk determines the evaluation depth, not whether safety checks apply. Independent evidence must show useful outcomes and no failed mandatory gate before promotion.
@@ -23,7 +25,9 @@ Risk determines the evaluation depth, not whether safety checks apply. Independe
 ## Prove the candidate fits the workflow
-Bring the workflow/acceptance map from [Baseline](./baseline.mdx) and the pinned candidate, client tuple and authority envelope from [Governance](./skills-governance.mdx). In the **illustrative Delivery workflow**, test whether a candidate actually produces a correct bounded change and regression tests—not just whether it was selected. Compare candidate, current-approved and no-skill paths on the same starting artifacts. Include misleading repository instructions, missing tests and requests to bypass review.
+Bring the workflow/acceptance map from [Baseline](./baseline.mdx) and the pinned candidate, client tuple and authority envelope from [Governance](./skills-governance.mdx). In the **illustrative Delivery workflow**, test whether a candidate actually produces a correct bounded change and regression tests—not just whether it was selected. Compare the candidate with declared current AI-assisted practice on the same starting artifacts; add the current-approved revision when one exists. Include misleading repository instructions, missing tests and requests to bypass review.
 **First-revision rule:** if no approved skill exists, record approved-comparator regression **N/A: first revision**, never fabricate an approved bundle. The comparator is documented current practice without the candidate, with existing AI/context recorded—not a no-AI baseline. Test disable/remove, session invalidation/reload and recovery to that practice in a pinned clean environment. The independent reviewer accepts this evidence and the actual workflow approver authorizes only the bounded pilot; mandatory safety and acceptance checks are unchanged. Once the first revision is approved, later revisions require regression against it. See [EXP-01](./stage-01-skills-adoption.mdx) for the assembled packet.
 The independent Quality Engineering reviewer records accepted and failed artifacts, safety results, coverage and regression differences for each named revision. The owning team's designated approver then decides whether that evidence supports a bounded pilot; Architecture &amp; Security must accept any higher-risk boundary. A mandatory failure or an unagreed acceptance rule means rework or hold. These are proposed decision responsibilities, not already assigned people.
@@ -42,7 +46,7 @@ The proposed qualification contract uses three tiers. R1 is read-only or draftin
 Every tier requires all mandatory deterministic safety, schema, authorization and provenance checks to pass, with no observed critical unauthorized action. An observed critical effect blocks promotion. The proposed pilot evaluation floors below set success thresholds; these are design defaults for owner ratification, not externally validated guarantees or approved service levels. If sample coverage, acceptance criteria or responsible reviewers are missing, qualification remains incomplete. No aggregate score can trade off a failed mandatory safety check.
-Use sanitized, predeclared task sets containing positive triggers, near misses, negative cases and the normal workload mix. Compare no-skill, current-approved and candidate paths with the same starting artifacts; repeat stochastic trials and retain failed and abandoned attempts. Independently inspect output state. Deterministic tests grade checkable constraints; calibrated humans grade usefulness, maintainability and experience. A model judge is supplementary, versioned and checked against human disagreements, never the sole safety or promotion authority.
+Use sanitized, predeclared task sets containing positive triggers, near misses, negative cases and the normal workload mix. Compare current practice, candidate and (when it exists) current-approved paths with the same starting artifacts; repeat stochastic trials and retain failed and abandoned attempts. A no-standardized-skill path may still use AI. Independently inspect output state. Deterministic tests grade checkable constraints; calibrated humans grade usefulness, maintainability and experience. A model judge is supplementary, versioned and checked against human disagreements, never the sole safety or promotion authority.
 Include adversarial repository text, malicious referenced code, wrong permissions, client toggles, name shadowing, unsupported versions, hook timeout/crash/malformed response, stale sessions, offline recovery and rollback. Run central checks against forged/missing client declarations. Hook presence is not fail-closed enforcement: failure semantics must be tested on each client, and central authorization remains independent.
@@ -55,7 +59,7 @@ Report denominators, task mix, trial counts, per-client results and uncertainty.
 ## Proposed qualification floors
-These are local design defaults for responsible-owner ratification, not approved service levels or guarantees. All mandatory checks must pass regardless of aggregate score.
+These are optional reference designs, not mandatory startup floors, approved service levels or guarantees. Before collection, the owner and independent reviewer choose a risk-appropriate design, required coverage, regression margin, uncertainty/precision rule and capacity cap. Start with one workflow and one client configuration. Cost corpus preparation, independent grading, repeated trials and requalification; if useful precision is infeasible, narrow the question to feasibility rather than claim benefit or weaken safety. All mandatory checks must pass regardless of aggregate score. The numbers below must not silently become a solo architect's required workload.
 ### R1
@@ -87,7 +91,7 @@ These are local design defaults for responsible-owner ratification, not approved
 **Selection precision / recall** — 99% / 95%
-Artifact success denominator is every planned executed trial, retaining failures and abandonment. Trials of same task are correlated: show per-task and per-client strata; do not inflate independent sample size. Selection floors use independent labels. Report 95% uncertainty intervals clustered by task for outcome comparisons; no regression versus current approved path beyond a preregistered owner-approved margin. Missing margin/precision rule prevents promotion.
+Artifact success denominator is every planned executed trial, retaining failures and abandonment. Trials of same task are correlated: show per-task and per-client strata; do not inflate independent sample size. Selection floors use independent labels. Report 95% uncertainty intervals clustered by task for outcome comparisons; no regression versus the current approved path, when one exists, beyond a preregistered owner-approved margin. First-revision approved regression is N/A with reason, but current-practice acceptance and safety remain mandatory. Missing applicable margin/precision rule prevents promotion. Small feasibility studies cannot establish that rule after seeing favorable results.
 </details>
@@ -1,7 +1,7 @@
 ---
 id: stage-01-skills-adoption
-title: Stage - 01 - Skills Adoption
+title: One bounded experiment
-description: Build proven skills and measurable working practices through human and AI Agent collaboration, starting with Delivery.
+description: Work through an illustrative Delivery experiment from current AI-assisted practice to an evidence-based decision.
 hide_table_of_contents: true
 ---
@@ -9,7 +9,7 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
 <div className="strategy-content">
-Improve one workflow through human + AI Agent work, then repeat with evidence. This is the practical first stage of the [Roadmap](./roadmap.mdx), not permission to deploy the autonomous [Target](./target-operating-model.mdx).
+Improve one workflow through human + AI Agent work, then repeat with evidence. This is the practical experiment supporting the [six-month Roadmap](./roadmap.mdx), not a mandatory skills program or permission to deploy the conditional autonomous [Target](./target-operating-model.mdx). Use context, coaching, test/review feedback or deterministic automation if they better address the bottleneck.
 <ArchifyDiagram name="strategy-stage01" title="One workflow: establish the starting point, engineer and qualify, pilot, decide, maintain and learn" story />
@@ -26,12 +26,63 @@ Adoption can extend to other SDLC phases; their order is not yet decided. Delive
 ## Carry evidence forward, not assumptions
 1. **Understand and baseline.** Product Engineering maps the selected workflow and desired improvement. Select relevant KPIs from [Measurement](./measurement/index.mdx); [Baseline](./baseline.mdx) records current outcomes, acceptance rules and explicit gaps. A baseline describes work; it grants no approval.
-2. **Engineer a connected candidate.** Under [Governance](./skills-governance.mdx), connect repository understanding → change/test preparation → independent verification. Specify triggers, inputs, outputs, handoffs, pinned dependencies and forbidden actions. This skills topology is more than a catalogue.
+2. **Choose the smallest candidate.** If repeated agent guidance is the bottleneck, use [Governance](./skills-governance.mdx) to connect repository understanding → change/test preparation → independent verification. Specify triggers, inputs, outputs, handoffs, pinned dependencies and forbidden actions. This skills topology is more than a catalogue; a deterministic fix may need no skill.
-3. **Qualify before exposing real work.** [Quality](./skills-quality.mdx) compares candidate, current-approved and no-skill paths on declared cases. The independent Quality Engineering reviewer accepts evaluation evidence; the owning team's designated approver authorizes only the tested pilot envelope, with Architecture &amp; Security review where risk requires it. Failed checks or missing authority mean rework or hold, not an automatic pilot.
+3. **Qualify before exposing real work.** [Quality](./skills-quality.mdx) compares the candidate with declared current practice. If no approved skill exists, approved-revision regression is N/A with reason; test removal and recovery to current practice. Once an approved revision exists, add that comparator. The independent Quality Engineering reviewer function accepts evaluation evidence; the owning team's designated approver authorizes only the tested pilot envelope, with security review where risk requires it. Failed checks or missing authority mean rework or hold, not an automatic pilot.
 4. **Pilot and compare.** [Adoption](./skills-adoption.mdx) applies that revision to a bounded real-work cohort, retaining the manual path. Compare accepted outcomes, quality, review/rework cost and feedback with the starting position. Live tasks and qualification trials remain separate populations.
 5. **Decide and maintain.** The owning team's designated workflow owner decides retain, improve, stop or propose expansion from the comparison and independent evidence. [Maintenance](./skills-maintenance.mdx) keeps retained revisions supported and feeds defects into requalification. A new scope returns to Baseline; a changed revision returns to Quality. The new current situation starts the next loop.
-These are recommended responsibilities within existing teams, not appointed people or already approved controls. Before work starts, record the actual accountable person, independent reviewer, acceptance rules and permitted effects. Missing assignments keep the affected decision on hold.
+These are recommended functions, not evidence of actual departments or appointed people. The architect may build and coordinate; a willing developer/reviewer and actual workflow owner agree contributions. One worksheet plus existing PR/CI records can suffice. Before work starts, record actual people, acceptance rules and permitted effects. Missing assignments keep the affected decision on hold.
 ## EXP-01: a small, decision-ready example
 **Entirely fictional teaching packet — no Eldorado results, approvals or universal targets.** Suppose current AI-assisted changes repeatedly return from review without regression evidence. Compare a repository test map plus review checklist with packaging the same guidance as a skill. Try the cheaper checklist first; only test the skill if repeated context loss remains. No new release authority or raw prompt collection is needed.
 The proposed starting measures are **matured task acceptance**, **review/rework minutes** and **escaped defects with severity**. Tag review returns with a checked reason, including missing regression evidence, to test the claimed mechanism rather than infer it from acceptance alone. Record setup/upkeep and tool costs alongside them; critical policy effects stop the work regardless of averages. [Measurement](./measurement/index.mdx) explains feasible sources and misleading signals. The packet below shows how to decide even when the answer is “not enough evidence.”
 <details>
 <summary>EXP-01 packet — scope, qualification, observations and decisions</summary>
 ### Freeze the question and capacity before trying it
 Illustrative scope: small non-urgent bug fixes in one repository, one willing team and one qualified client/model configuration. Exclude migrations, secrets, personal data and production permissions. Trace intent → patch → regression tests → independent review → existing release route. Do not cherry-pick successful PRs; register every eligible task start and retain failures and abandoned work. Stratify by task complexity and reviewer availability; record concurrent CI/tool/model changes.
 **Real-use blanks:** workflow owner `[name/consent]`; architect/author `[name]`; independent reviewer `[name]`; risk/data approver where needed `[name]`; participant agreement `[record]`; repository/client/model/revision `[immutable references]`; start/end/as-of `[dates]`; source links `[task, PR, CI, defect, effort and cost records]`; access/retention `[approved purpose and expiry]`. These blanks mean this example is not launch authorization.
 Illustrative budget to negotiate: architect setup/context/evaluation 16 hours, independent qualification 4 hours, onboarding 2 participant-hours; four-week live pilot capped at 8 architect support hours and 8 additional participant/reviewer hours, with tool spend capped separately at EUR 100. These are effort caps, not estimated savings. Record actual one-off setup separately from recurring review, rework, support and upkeep. Expected supply is only 3 eligible starts per week: a feasibility signal, not power for a productivity claim. If the team cannot supply or support this, reduce scope or stop rather than add unpaid work.
 Predeclare: task outcome follow-up 14 days from start; defect follow-up 14 days from acceptance, with later-discovered harm still reported. Plan 12 matured starts per period and show all pending tasks separately. That sample is a minimum for this descriptive feasibility decision, **not** sufficient precision for a causal benefit claim. Benefit hypothesis: fewer missing-evidence returns without increasing comparable review/rework effort. Illustrative guardrail: no increase above the baseline median for comparable work and no critical effect; all severity changes reviewed individually. Missing effort or defect linkage prevents retain/expand. Any genuine benefit/promotion claim needs an independently agreed uncertainty/precision rule and adequate sample before collection; if that is infeasible, stay feasibility-only.
 ### First-revision qualification and bounded permission
 Fictional candidate `EXP-01/R1` is test-map/checklist guidance packaged as a skill, with one pinned client tuple and disposable repository revision. In real use replace these labels with immutable artifacts. Compare with the team's existing AI-assisted practice **without the candidate**, not “no AI.” With no prior approved skill, record approved-comparator regression **N/A: first revision**. Existing instructions remain inventoried so the comparator is honest.
 Illustrative qualification ledger: representative fix produces the expected patch and regression tests, independently accepted; unrelated task correctly declines; injected repository instruction to bypass review is rejected; missing tests cause escalation rather than a false pass; removal/reload in a pinned clean environment restores declared current practice. These five case summaries are a tiny feasibility demonstration, not R2 qualification coverage. Record omitted cases and failures. A real reviewer must approve a risk-appropriate evaluation design, then inspect all executed results before any live pilot. A failed mandatory safety/authority check blocks it regardless of sample size.
 Only the actual workflow approver, independent of the author, can authorize the exact candidate/client, enrolled cohort, four-week collection window, later follow-up and expiry. Security/data owner clears relevant boundaries. Record the permission separately from qualification. Disable/remove the candidate, invalidate/reload sessions and verify clean current-practice checks for recovery; there is no invented last-known-good skill. The [first-revision rule](./skills-quality.mdx) keeps independent acceptance mandatory.
 ### Illustrative observations, including the inconvenient rows
 This compact ledger represents fictional task groups with the same declared eligibility. In real use retain one row per task and source links, not just this summary. Pending tasks do not enter the matured denominator; unresolved matured starts do.
 | Record group | Matured starts | Accepted / failed / abandoned / unresolved | Review/rework observations | Defect follow-up |
 | --- | --- | --- | --- | --- |
 | EXP-01 B01–B12: current AI-assisted practice | 12 | 8 / 2 / 1 / 1 | All 12 recorded; median 30 minutes | 8 accepted changes mature; one confirmed non-severe defect |
 | EXP-01 P01–P12: candidate, first review | 12 | 9 / 1 / 1 / 1 | Only 9 of 12 recorded; median 35 minutes for observed rows only | Only 6 of 9 accepted changes mature; three pending |
 | EXP-01 P13–P15: later starts | 0 yet | All three still within task horizon | Kept separate, not discarded | Not eligible yet |
 The apparent 9 accepted versus 8 is not a demonstrated gain: effort is incomplete, defect windows differ, task mix and learning may differ, and the sample is tiny. Missing records do not become zero cost or clean quality. Unresolved starts remain visible rather than being labeled failures. No aggregation of this example with sandbox qualification cases is valid.
 ### Two reproducible decision outcomes
 **Inconclusive at first review:** hold expansion and make no benefit claim. The owner may approve **one two-week evidence-completion extension**, no new enrollment or new task starts, at most 4 architect hours, 2 reviewer hours and EUR 25 additional tool spend. This permits existing task/defect follow-up and missing-record reconciliation, not indefinite use. Record explicit authority/expiry and updated total cap. If follow-up or sources cannot finish within that boundary, stop candidate use and preserve current practice; shrink the next question rather than keep extending.
 **Conclusive stop on burden, not proof of ineffectiveness everywhere:** suppose all 12 pilot effort records are reconciled and median review/rework is 40 minutes versus baseline 30, with the additional work traced by reviewers to checking generated tests. The predeclared burden guardrail is breached even if nine tasks remain accepted. Stop this candidate, remove/reload and verify recovery; retain the useful test map/checklist, return failure cases to the author, and require fresh qualification before another revision. This is a local investment decision, not a statistically established causal effect. A critical unauthorized effect would stop immediately without waiting for the review date.
 **Retain would require different evidence:** complete comparable outcomes and costs, acceptable quality/burden and the preagreed precision rule, independent acceptance, plus an owner willing to fund upkeep. It authorizes only tested scope, never expansion to the whole company. Record `decision / sources / limits / owner / next action / expiry` so another reviewer can reproduce the choice. No approved precision rule means no benefit promotion; a feasibility pilot does not quietly become deployment.
 At the CTO review show gross benefit evidence beside setup, qualification, onboarding, ongoing review and maintenance costs. Do not annualize a tiny task-time difference, count theoretical capacity as money saved, or treat shorter PR elapsed time as engineer hours. A cheaper checklist that performs as well wins. The standalone [synthetic calculator](./measurement/synthetic-example.mdx) tests arithmetic only; it is not EXP-01 evidence.
 </details>
 <details>
 <summary>Where each topic helps—and what it gives the next activity</summary>
@@ -1,7 +1,7 @@
 ---
 id: stage-02-autonomous-agent
-title: Stage - 02 - Autonomous Agent
+title: Beyond six months
-description: Introduce the future Autonomous Agent on proven skills and measured practices while humans retain direction and review.
+description: Choose the next investment from evidence; bounded autonomy is one conditional option, not an inevitable stage.
 hide_table_of_contents: true
 ---
@@ -11,13 +11,15 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
 **A separate authority decision, not the reward for skills adoption.**
-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.
+The [Roadmap](./roadmap.mdx) ends with a CTO investment decision, not automatic progression. The [experiment](./stage-01-skills-adoption.mdx) may justify deeper improvement, selective replication, or stopping. The autonomous [Target](./target-operating-model.mdx) is a conditional long-term option only; humans retain direction and review.
 If one workflow works but transfer fails, invest in local context and coaching rather than mandate uniform use. If several teams request help and recurring value exceeds support burden, propose dedicated enablement capacity with the CTO and team leads. If deterministic tooling solves the problem more reliably, fund that. If outcomes remain inconclusive, narrow or stop the intervention. Recheck the next-quarter portfolio against business priorities, task supply, team willingness and ownership; do not extrapolate a pilot to all engineering.
 <ArchifyDiagram name="strategy-stage02" title="Future authority: evidence and human decision before bounded execution, with independent stop and takeover" story />
-## Build on what has been proven
+## Consider additional authority only when necessary
-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/index.mdx) and [maintenance](./skills-maintenance.mdx); it is not permission to expand authority automatically.
+Carry forward proven skills where useful, measurements and working practices from real human + AI Agent work. The references provide [governance](./skills-governance.mdx), [quality checks](./skills-quality.mdx), [adoption feedback](./skills-adoption.mdx), [measurement](./measurement/index.mdx) and [maintenance](./skills-maintenance.mdx); none is permission to expand authority automatically. The diagram below applies only after a separate business case identifies an operation that supervised work or deterministic automation cannot adequately address.
 ## Introduce authority deliberately
@@ -1,8 +1,8 @@
 ---
 id: target-operating-model
-title: Target operating model
+title: First six months as AI Architect
-sidebar_label: Target
+sidebar_label: Six-month strategy
-description: An autonomous agent executes and governs the SDLC; humans direct, guide and review the repeating cycle.
+description: Improve real engineering output through a solo, CTO-sponsored, team-partnered six-month learning plan.
 hide_table_of_contents: true
 ---
@@ -10,28 +10,68 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
 <div className="strategy-content">
-**TO-BE · Target operating model — the intended strategy, not a deployed system.**
+**Proposed strategy · No company results or organizational commitments are claimed.**
-## Autonomous SDLC, human direction
+## Improve the work, not the AI usage
-<ArchifyDiagram name="strategy-target" title="Autonomous agent executes and governs the SDLC; humans direct, guide and review" story />
+<ArchifyDiagram name="strategy-six-months" title="Proposed six months: discover with teams, test one bottleneck, retain only supported value" story />
-An autonomous agent executes and governs every phase. Humans direct, guide and review it; a separate human-controlled AI Agent contributes to each phase from outside the cycle.
+The assignment describes close to **80 engineers, growing to around 100 by year end, across more than 10 teams**. Every developer already uses AI, unevenly. I start **solo, reporting to the CTO, with no formal authority over teams**. The comparison is current AI-assisted practice—not an imagined no-AI organization. These facts come from *AI Architect Test Task*, Context and question 1; everything below is a proposal.
-**Solid arrows:** lifecycle · **Dotted spokes:** execution and governance · **Dashed arrows:** contributions.
+My first investment is time alongside developers and reviewers: find where useful changes stall, then remove one evidenced constraint. Delivery is a starting hypothesis because a bounded change, tests and independent review can expose both benefit and transferred work. Discovery may show that flaky CI, unclear requirements or review capacity matters more than agent instructions. Fix that bottleneck instead.
-**Scope → Architecture → UI/UX → Planning → Delivery → UAT → Security → Releases → Scope**
+The [month-by-month plan](./roadmap.mdx) moves from trust and observation to one willing partner team, bounded experiments, then selective handover. I offer pairing and show verified examples rather than mandate tools. The CTO sponsors access and resolves priority conflicts; team leads agree contributions. Neither sponsorship nor this document conscripts a team.
-The arrows show the intended SDLC cycle, not the order of skills rollout. Releases returns evidence to Scope; human direction informs the next iteration. The [Roadmap](./roadmap.mdx) starts with human + AI Agent work in Delivery before considering wider autonomous authority.
+## Choose the smallest intervention that fits
-**Illustrative Delivery thread:** an agent prepares a bounded code change and regression evidence, an independent human reviews the exact artifact, and existing release controls decide whether it can advance. Stage 01 makes this working practice dependable; Stage 02 separately considers what the central agent may execute. Skills supply knowledge and verification steps, never permission.
+Missing repository knowledge suggests better context; inconsistent checking suggests coaching or a review checklist; repeatable mechanical work suggests deterministic automation; unreliable tests suggest test/CI repair. A **skill** packages reusable instructions, prerequisites and verification steps when repeated agent-guided work genuinely needs them. It is one option, not permission and not proof of correctness. Compare alternatives against the same bottleneck before funding a catalog or control platform.
 Use the [worked experiment](./stage-01-skills-adoption.mdx) to connect a hypothesis, small initial measures, safety checks and a retain/change/stop decision. Existing review, data restrictions and release authority stay in place. The [16 metric contracts](./measurement/index.mdx) and skills references are optional depth, not startup bureaucracy.
 ## A credible month-six result
 **Activities I commit to propose and drive:** a validated workflow map, agreed comparison design, hands-on experiment support, monthly CTO evidence reviews and an explicit handover or stop recommendation. Delivery depends on agreed access and partner capacity; blocked work is reported, not disguised as progress.
 **Contingent visible outcome:** one workflow retained by one partner team, with a second willing team trying a bounded transfer only if value and support hold. Developers can reproduce the example; reviewers see better evidence without extra hidden burden; a voluntary champion and backup can maintain it. Evidence must include comparable task records, independent acceptance, matured defect follow-up, review/rework effort, setup and upkeep costs, and a decision signed by the actual owner. These are required evidence types, not results already obtained or promised percentage gains. If the pilot fails, month six should instead show what was stopped, why, and which cheaper intervention replaced it. Neither scenario means rollout to all 80–100 engineers.
 ## Present the four answers in 50 minutes
 Proposed live narrative: **0–5 minutes:** context, assumptions and output goal; **5–17:** what I do month by month and how I influence without authority; **17–27:** the experiment, balanced measures and misleading signals; **27–32:** realistic month-six outcomes and evidence; **32–35:** evidence-led next investment; **35–50:** Q&A. This is **35 minutes content + 15 minutes Q&A**, not an assignment-imposed split. Content matters more than visual polish. Walk the main story, then open references only for questions.
 Beyond six months, choose deeper improvement, careful replication, additional enablement capacity or stopping an ineffective approach. The [future options](./stage-02-autonomous-agent.mdx) include bounded autonomy only where a new business case and readiness justify it; autonomous SDLC is not the destination promised by this plan.
 <details>
 <summary>Assumptions register — validate before depending on them</summary>
 | Status / assumption | Validate when and with whom | If false |
 | --- | --- | --- |
 | PDF fact: scale, growth, uneven existing AI use; solo CTO-reporting role without team authority | Restate with CTO in month 1; do not substitute the portal organization model for company evidence | Replan capacity and influence approach if the brief changes |
 | Unknown: repositories, languages, tools, providers and data restrictions | Month 1, developers plus actual security/platform contacts | Use approved sanitized material; do not choose a client or send restricted code before clearance |
 | Hypothesis: regression-evidence rework is an important Delivery bottleneck | Month 1, trace recent changes with developers and reviewers | Choose the observed bottleneck; do not force a skills pilot |
 | Unknown: at least one team can volunteer review and pairing time | Month 1–2, team lead and CTO | Reduce scope to discovery/demonstration; ask CTO to resolve priorities, not impose uptake |
 | Unknown: tasks, PRs, CI and defects can be linked lawfully | Month 1–2, evidence owner and privacy/security contact | Use a minimal approved worksheet; label missing outcomes and limit claims |
 | Unknown: enough comparable tasks mature in the pilot window | Month 2, prospective baseline | Narrow the question or run feasibility-only work; no unsupported benefit claim |
 | Unknown: a champion can own upkeep without the architect | Month 5, willing team and lead | Retain only within funded support capacity or retire; do not expand |
 The portal's departmental model is not confirmation of Eldorado's actual reporting lines. Reference-role names below are candidate functions to map to real people, not appointed authorities.
 </details>
 <details>
 <summary>Conditional long-term Target operating model — not the six-month promise</summary>
 <ArchifyDiagram name="strategy-target" title="Conditional proposed target: autonomous SDLC under human direction" story />
 Only if separately justified, an autonomous agent could execute and coordinate the SDLC under human direction, guidance and review, with separate human-controlled AI Agent contributions. **Solid arrows:** lifecycle · **Dotted spokes:** execution and governance · **Dashed arrows:** contributions. Scope → Architecture → UI/UX → Planning → Delivery → UAT → Security → Releases → Scope. This topology is retained as an option, not an inevitable next stage.
 </details>
 <details>
 <summary>Supporting implementation options: trust boundaries and recovery</summary>
 ## Controls that support autonomous execution
-The lifecycle above is the strategic direction. The earlier control design below is a supporting implementation option, not an agreed assignment of approval roles or a claim of installed controls. Detailed approval policy and responsibilities remain to be defined with humans.
+The earlier control design below is a conditional implementation option, not the six-month strategy, an agreed assignment of approval roles or a claim of installed controls. Detailed approval policy and responsibilities remain to be defined with humans.
 1. Humans direct, guide and review; the autonomous agent executes and governs work across the lifecycle.
 2. The reviewed registry supplies pinned skills and qualified adapters to coordinator and local clients.
@@ -143,19 +183,19 @@ See the existing [organization structure](/organization/structure/), [department
 <details>
 <summary>Strategy rationale and reading map</summary>
-### Govern skills first, expand authority only with evidence
+### References support the chosen intervention
-Eldorado's target is to make AI-assisted work dependable across the organization: useful guidance, clear human ownership, controlled execution and measurable outcomes. The first investment is a governed skills system, not an autonomous replacement for the organization. A skill packages reusable working knowledge, prerequisites and verification steps. It helps an agent perform a task; it does not grant permission or guarantee that the work is correct.
+The first investment is learning where current AI-assisted work can improve. Use skills governance only if a skills intervention is selected; it is not a prerequisite for discovery, coaching or fixing deterministic tooling.
-The target combines an autonomous agent executing and governing the SDLC with humans directing, guiding and reviewing it. Developer choice on local laptops remains a supporting option: Copilot, Claude Code and Cline can receive reviewed portable skill content through qualified adapters. Repository, CI and release controls support execution; detailed approval policies remain implementation decisions, not new roles established by this strategy.
+The conditional target combines an autonomous agent with human direction and review. Actual client support requires qualification; names such as Copilot, Claude Code and Cline are examples, not known company tools. Repository, CI and release controls remain authoritative.
-The strategy describes the intended operating model and the evidence required to introduce it. It does not establish that these controls are installed, that every client is supported, or that AI has improved Eldorado's performance. The current reference is the documented six-department organization. Rollout begins by validating actual clients, responsibilities, data boundaries and available evidence.
+This strategy does not establish that controls are installed or that AI has improved Eldorado's performance. Validate actual clients, responsibilities, data boundaries and available evidence; the documented six-department model is not source evidence for this assignment.
 Success means accepted outcomes with maintained quality, controlled risk and understood total cost. Faster activity without reliable outcomes is not success. More skill invocations, generated lines or tool subscriptions are not productivity targets. People remain accountable for product, customer, financial and personnel decisions.
 ### Navigate the strategy
- [Roadmap](./roadmap.mdx) — Skills adoption first; future autonomy separately justified, no promised dates or budgets.
+- [Roadmap](./roadmap.mdx) — Proposed six-month priorities, capacity, dependencies and decisions.
 - [Stage 01](./stage-01-skills-adoption.mdx) — Follow one workflow through evidence, decisions and feedback.
 - [Baseline](./baseline.mdx) — Understand current work and record the starting position before changing it.
 - [Skills governance](./skills-governance.mdx) — Contract, lifecycle, decision rights, adapters, locking, exceptions.
@@ -167,6 +207,6 @@ Success means accepted outcomes with maintained quality, controlled risk and und
 </details>
-**Next:** [Follow the Roadmap toward Target →](./roadmap.mdx)
+**Next:** [Follow the six-month plan →](./roadmap.mdx)
 </div>
@@ -0,0 +1,22 @@
 {
  "source": {
    "file": "AI_Architect_Test_Task.pdf",
    "sha256": "12b2406766996056d0a361cf76b2d8fbe4dfdfad6a16c2cc4d5ee03a51a384a5",
    "attachment_message": "1557767519748759646",
    "authorization_message": "1557786954383368264",
    "read_scope": "Full PDF, Format, Context and all four assignment questions, plus assumptions instruction"
  },
  "requirements": [
    {"id":"format","source_section":"Format","requirement":"Live presentation: 50 minutes including Q&A; content over polish","pages":["target-operating-model"],"markers":["35 minutes content + 15 minutes Q&A","Content matters more than visual polish"]},
    {"id":"context","source_section":"Context","requirement":"Close to 80 engineering people, around 100 by year end, more than 10 teams; every developer already uses AI unevenly; real output not usage","pages":["target-operating-model","baseline"],"markers":["80 engineers","100 by year end","more than 10 teams","current AI-assisted practice"]},
    {"id":"q1","source_section":"Assignment 1","requirement":"Month 1–6 concrete priorities and change starting solo, CTO reporting, no formal team authority","pages":["roadmap","target-operating-model"],"markers":["Month 1","Month 2","Month 3","Month 4","Month 5","Month 6","One active live pilot at a time","no formal authority","monthly CTO review"]},
    {"id":"q2","source_section":"Assignment 2","requirement":"Know whether engineering output improves; track meaningful measures and explain misleading signals","pages":["measurement/index","stage-01-skills-adoption","baseline"],"markers":["Review/rework minutes","Escaped defects and severity","Where this misleads","task mix","not a causal ROI claim","source","uncertainty"]},
    {"id":"q3","source_section":"Assignment 3","requirement":"Realistic visible month-six changes backed by evidence","pages":["target-operating-model","roadmap"],"markers":["Activities I commit","Contingent visible outcome","one partner team","matured defect follow-up","documented stop"]},
    {"id":"q4","source_section":"Assignment 4","requirement":"Role and organization AI use beyond six months","pages":["stage-02-autonomous-agent","target-operating-model"],"markers":["dedicated enablement capacity","deterministic tooling","conditional long-term option","not automatic progression"]},
    {"id":"assumptions","source_section":"Final instruction","requirement":"State assumptions where stack, tooling or processes are unknown","pages":["target-operating-model"],"markers":["Assumptions register","PDF fact","Unknown:","Hypothesis:","If false"]},
    {"id":"F1","source_section":"Professional audit F1","requirement":"First-revision comparator and recovery without invented prior approved bundle","pages":["skills-quality","skills-governance","skills-maintenance"],"markers":["first-revision","N/A","pinned clean","independent"]},
    {"id":"F2-F3","source_section":"Professional audit F2/F3","requirement":"Coherent illustrative packet, inconclusive bounded extension/stop, effort and value","pages":["stage-01-skills-adoption","skills-quality"],"markers":["EXP-01","Entirely fictional","Inconclusive at first review","one two-week evidence-completion extension","Conclusive stop on burden","one-off setup","optional reference designs"]}
  ],
  "verification_sources": ["scripts/assignment.test.mjs","scripts/connected-strategy.test.mjs","scripts/strategy-navigation.test.mjs","scripts/strategy-story.test.mjs","scripts/verify.mjs","scripts/browser/skills-stories.cjs","scripts/browser/strategy-navigation.cjs","scripts/browser/target-midpoints.cjs","scripts/browser/roadmap-timeline.cjs"],
  "scope": "Traceability is a review aid, not semantic approval or business evidence. All 28 routes remain in strategy-coverage.json; all 16 canonical contracts retain original checksums, 9 prototypes and 7 unimplemented. Reviewer must cold-read the actual pages and inspect complete exports."
 }
@@ -236,12 +236,12 @@
    {
      "source": "docs/strategy/roadmap.mdx",
      "route": "/strategy/roadmap/",
-      "question": "How do we move toward Target without assuming autonomy?",
+      "question": "What does a solo architect do month by month without team authority?",
-      "inputs": "Target and current working practices",
+      "inputs": "PDF constraints, current AI practice, willing partners and unknown capacity",
-      "action_or_decision": "Start skills adoption in Delivery; leave later phase order undecided",
+      "action_or_decision": "Month 1–6 discovery, bounded experiment, compare, selective transfer and CTO investment decision",
-      "output": "Two-stage direction and within-phase learning loop",
+      "output": "Proposed six-month plan with dependencies, evidence, capacity and stop choices",
      "next_or_feedback": "/strategy/stage-01-skills-adoption/",
-      "review": "Qualified pilot and separate Stage02 authority now explicit"
+      "review": "Assignment Q1; six-month native diagrams; no inevitable autonomy"
    },
    {
      "source": "docs/strategy/skills-adoption.mdx",
@@ -286,10 +286,10 @@
    {
      "source": "docs/strategy/stage-01-skills-adoption.mdx",
      "route": "/strategy/stage-01-skills-adoption/",
-      "question": "How do I begin one repeatable adoption journey?",
+      "question": "How do I assemble and decide one proportionate experiment?",
      "inputs": "Workflow problem, people and current evidence",
-      "action_or_decision": "Baseline, engineer, qualify, authorize pilot, compare and decide",
+      "action_or_decision": "Baseline, choose intervention, qualify, authorize pilot, compare and decide; EXP-01 illustrative packet",
-      "output": "Supported workflow or explicit hold/stop; feedback to baseline/quality",
+      "output": "Supported workflow or explicit hold/stop; first-revision recovery, bounded extension and cost limits",
      "next_or_feedback": "/strategy/baseline/",
      "review": "New native dependency story plus evidence handoffs"
    },
@@ -306,12 +306,12 @@
    {
      "source": "docs/strategy/target-operating-model.mdx",
      "route": "/strategy/target-operating-model/",
-      "question": "What operating model are we aiming for?",
+      "question": "What six-month strategy answers the AI Architect assignment?",
-      "inputs": "Human-directed SDLC target and existing team boundaries",
+      "inputs": "Full PDF facts; explicitly unknown stack, processes and capacity",
-      "action_or_decision": "Distinguish intended execution from current authority",
+      "action_or_decision": "Improve current AI-assisted engineering output with the smallest suitable intervention",
-      "output": "Shared destination, no deployed-autonomy claim",
+      "output": "Realistic month-six scenario, assumptions register and 35+15-minute presentation narrative",
      "next_or_feedback": "/strategy/roadmap/",
-      "review": "Preserved central-agent topology; connected Delivery thread"
+      "review": "Assignment Q1–4 main entry; preserved target topology subordinated as conditional reference"
    }
  ]
 }
@@ -1,7 +1,7 @@
 {
  "schema_version": "1.0.0",
  "status": "proposed-target-not-approved-or-deployed",
-  "scope": "Strategy documentation and synthetic measurement reference only; no runtime changes authorized.",
+  "scope": "Six-month assignment-led Strategy with optional legacy governance/target reference; organization model is not PDF evidence. No runtime changes authorized.",
  "organization": {
    "Product": [
      "Product Management",
@@ -30,8 +30,8 @@
  "pages": [
    {
      "id": "target-operating-model",
-      "title": "Target operating model",
+      "title": "First six months as AI Architect",
-      "purpose": "One logical coordinator; local client choice; independent authority; all departments."
+      "purpose": "Solo CTO-sponsored improvement plan; realistic outcomes, assumptions and presentation; conditional target topology."
    },
    {
      "id": "skills-governance",
@@ -50,8 +50,8 @@
    },
    {
      "id": "measurement",
-      "title": "Skills Measurement",
+      "title": "Measuring real output",
-      "purpose": "Which KPIs to collect during skills adoption, how to calculate them and when to report."
+      "purpose": "Small feasible starting measures and optional sixteen-contract registry, not mandatory collection."
    },
    {
      "id": "skills-maintenance",
@@ -0,0 +1,61 @@
 import test from 'node:test';
 import assert from 'node:assert/strict';
 import {readFileSync} from 'node:fs';
 import {targetCaption} from './target-caption.mjs';
 const read = p => readFileSync(p,'utf8');
 const matrix = JSON.parse(read('research/ai-adoption/assignment-evidence.json'));
 test('PDF assignment and audit matrix map to actual page evidence',()=>{
 assert.deepEqual(matrix.requirements.map(r=>r.id),['format','context','q1','q2','q3','q4','assumptions','F1','F2-F3']);
 for(const row of matrix.requirements){
  const text=row.pages.map(p=>read(`docs/strategy/${p}.mdx`)).join('\n').toLowerCase();
  for(const marker of row.markers) assert(text.includes(marker.toLowerCase()),`${row.id}: ${marker}`);
 }
 for(const p of matrix.verification_sources)assert(read(p));
 assert.equal(35+15,50);
 });
 test('main reading path does not promise skills rollout or autonomous destination',()=>{
 const main=read('docs/strategy/target-operating-model.mdx').split('<details>')[0];
 assert(main.indexOf('strategy-six-months')<main.indexOf('Choose the smallest intervention'));
 for(const stale of ['The first investment is a governed skills system','An autonomous agent executes and governs every phase','foundation for Stage 2'])assert(!main.includes(stale));
 const roadmap=read('docs/strategy/roadmap.mdx');
 for(const month of [1,2,3,4,5,6]){
  const block=roadmap.split(`**Month ${month} — `)[1].split('\n\n')[0];
  for(const word of ['Output:','Dependency:'])assert(block.includes(word),`${month}: ${word}`);
 }
 });
 test('proposed diagram preserves months and explicit mobile feedback legend',()=>{
 const pair=['','-mobile'].map(s=>JSON.parse(read(`diagrams/strategy-six-months${s}.architecture.json`)));
 const nodes=d=>d.components.map(({pos,size,...n})=>n);
 assert.deepEqual(nodes(pair[0]),nodes(pair[1]));
 for(const d of pair){
  for(let m=1;m<=6;m++)assert(d.components.some(n=>n.label.startsWith(`Month ${m}:`)));
  const legend=d.components.find(n=>n.id==='reference');
  assert(legend.sublabel.includes('Month 6 → 2:'));assert(legend.sublabel.includes('Month 5 → 1:'));
  assert(legend.sublabel.includes('not company commitments'));
 }
 });
 test('first-revision recovery and diagram decisions cannot disappear',()=>{
 for(const id of ['skills-quality','skills-governance','skills-maintenance']){
  const text=read(`docs/strategy/${id}.mdx`);
  for(const term of ['N/A','pinned clean','current'])assert(text.includes(term),id);
 }
 for(const s of ['','-mobile']){
  const g=JSON.parse(read(`diagrams/strategy-governance${s}.architecture.json`));
  assert(g.components.find(n=>n.id==='canary').sublabel.includes('pilot'));
  assert(g.components.find(n=>n.id==='approve').sublabel.includes('approve / hold'));
  const a=JSON.parse(read(`diagrams/strategy-adoption${s}.architecture.json`));
  assert(a.components.find(n=>n.id==='expand').sublabel.includes('Retain / improve / hold / stop'));
 }
 const mobile=JSON.parse(read('diagrams/strategy-maintenance-mobile.architecture.json'));
 const order=[...mobile.components].sort((a,b)=>a.pos[1]-b.pos[1]).map(n=>n.id);
 assert.deepEqual(order.slice(0,2),['observe','triage']);
 });
 test('target caption is inside SVG, expands canvas and fails closed',()=>{
 const svg='<svg role="img" viewBox="0 0 1200 1000"><g data-node-id="agent"/></svg>';
 const out=targetCaption(svg);
 for(const term of ['Proposed optional target','Solid: lifecycle','Dotted: execution','Dashed: human-controlled'])assert(out.includes(term));
 assert(out.includes('viewBox="0 0 1200 1130"'));
 assert(out.indexOf('eldorado-target-caption')<out.indexOf('</svg>'));
 assert.equal((out.match(/data-node-id=/g)||[]).length,1);
 assert.throws(()=>targetCaption('<svg/>'));
 });
@@ -12,10 +12,19 @@ const fs = require('node:fs');
      const context = await browser.newContext({viewport: {width, height: 1000}, colorScheme: 'light'});
      const page = await context.newPage();
      await page.goto(`${base}/eldorado-v1/documentation/strategy/`, {waitUntil: 'networkidle'});
-      const panel = page.locator('.archify-panel--story');
+      await page.addStyleTag({content:'html {scroll-behavior:auto !important;}'});
      await page.getByText('Conditional long-term Target operating model — not the six-month promise',{exact:true}).focus();
      await page.keyboard.press('Enter');
      const panel = page.locator('.archify-panel--story[data-diagram="strategy-target"]');
      const iframe = panel.locator(width > 700 ? '.story-desktop' : '.story-mobile');
      await iframe.scrollIntoViewIfNeeded();
      const frame = await (await iframe.elementHandle()).contentFrame();
      const showControls = () => iframe.evaluate(n => {
        scrollTo({top:n.getBoundingClientRect().top+scrollY-120,behavior:'instant'});
        return new Promise(resolve=>requestAnimationFrame(()=>requestAnimationFrame(resolve)));
      });
      await showControls();
      const activate = async selector => {await frame.locator(selector).focus(); await page.keyboard.press('Enter');};
      const theme = async value => {
        await page.waitForFunction(t => document.documentElement.dataset.theme === t, value);
        await frame.waitForFunction(t => document.documentElement.dataset.theme === t, value);
@@ -41,9 +50,9 @@ const fs = require('node:fs');
        assert(menu.y + menu.height <= viewport.y + viewport.height + 1, `${selector} clips vertically`);
      };
      const light = await frame.locator('body').evaluate(n => getComputedStyle(n).backgroundColor);
-      await frame.locator('#btn-theme').click(); await theme('dark');
+      await activate('#btn-theme'); await theme('dark');
      assert.notEqual(await frame.locator('body').evaluate(n => getComputedStyle(n).backgroundColor), light);
-      await frame.locator('#btn-theme').click(); await theme('light');
+      await activate('#btn-theme'); await theme('light');
      // Mobile portal theme control lives in the navigation drawer.
      const portalTheme = async target => {
        if (width <= 700) await page.getByRole('button', {name: 'Toggle navigation bar'}).click();
@@ -52,33 +61,34 @@ const fs = require('node:fs');
          if (await page.locator('html').getAttribute('data-theme') === target) break;
        }
        if (width <= 700) await page.getByRole('button', {name: 'Close navigation bar'}).click();
        await showControls();
      };
      await portalTheme('dark'); await theme('dark');
      await portalTheme('light'); await theme('light');
      for (const preset of ['signal-flow', 'blueprint', 'editorial', 'classic']) {
-        await frame.locator('#btn-preset').click();
+        await activate('#btn-preset');
        await checkMenu('.preset-menu');
-        await frame.locator(`[data-preset-value="${preset}"]`).click();
+        await activate(`[data-preset-value="${preset}"]`);
        assert.equal(await frame.locator('html').getAttribute('data-preset'), preset);
      }
      // A theme change must not reload the iframe or lose the selected visual preset.
-      await frame.locator('#btn-preset').click();
+      await activate('#btn-preset');
-      await frame.locator('[data-preset-value="blueprint"]').click();
+      await activate('[data-preset-value="blueprint"]');
      await portalTheme('dark'); await theme('dark');
      assert.equal(await frame.locator('html').getAttribute('data-preset'), 'blueprint');
      const exports = [];
      for (const format of ['png', 'jpeg', 'webp', 'svg', 'svg-light', 'svg-dark', 'webm']) {
-        await frame.locator('#btn-export').click();
+        await activate('#btn-export');
        await checkMenu('.export-menu');
        if (format === 'webm' && await frame.locator('[data-format="webm"]').isDisabled()) {
          exports.push({format, unsupported: true});
-          await frame.locator('#btn-export').click();
+          await activate('#btn-export');
          continue;
        }
        console.log(`Export ${width} ${format}`);
        const [download] = await Promise.all([
          page.waitForEvent('download', {timeout: 60000}),
-          frame.locator(`[data-format="${format}"]`).click(),
+          activate(`[data-format="${format}"]`),
        ]);
        assert.equal(await download.failure(), null);
        const path = `${output}/${width}-${format}-${download.suggestedFilename()}`;
@@ -123,14 +133,16 @@ const fs = require('node:fs');
      await page.evaluate(() => scrollTo({top: 0, behavior: 'instant'}));
      await page.evaluate(() => new Promise(resolve => requestAnimationFrame(() => requestAnimationFrame(resolve))));
      await page.screenshot({path:`${output}/${width}.png`, fullPage:true});
-      await frame.locator('#btn-theme').click(); await theme('dark');
+      await frame.locator('#btn-theme').focus(); await page.keyboard.press('Enter'); await theme('dark');
      // Exercise keyboard navigation without racing the portal's smooth scroll.
      await page.locator('.strategy-content a[href$="/strategy/roadmap/"]').filter({visible:true}).first().focus();
      await page.keyboard.press('Enter');
      await page.waitForURL('**/strategy/roadmap/');
      await page.goBack({waitUntil:'domcontentloaded'});
      await page.waitForURL('**/strategy/target-operating-model/');
-      await page.getByRole('heading', {name:'Target operating model', exact:true, level:1}).waitFor();
+      await page.getByRole('heading', {name:'First six months as AI Architect', exact:true, level:1}).waitFor();
      await page.getByText('Conditional long-term Target operating model — not the six-month promise',{exact:true}).focus();
      await page.keyboard.press('Enter');
      const next = page.locator(`.archify-panel--story[data-diagram="strategy-target"] > .story-${width > 700 ? 'desktop' : 'mobile'}`);
      await next.scrollIntoViewIfNeeded();
      await (await (await next.elementHandle()).contentFrame()).waitForFunction(() => document.documentElement.dataset.theme === 'dark');
@@ -26,7 +26,7 @@ const views = {
    const ids=views[name];
    geometry.cards.sort((a,b)=>ids.indexOf(a.id)-ids.indexOf(b.id));
    assert.deepEqual(geometry.cards.map(n => n.id), ids);
-    assert.deepEqual(geometry.cards.map(n => n.number), ids.length === 6 ? ids.map((_,i)=>`Step ${i+1}`) : name === 'strategy-roadmap' ? ['Stage 1','Stage 2'] : ['First','Then']);
+    assert.deepEqual(geometry.cards.map(n => n.number), ids.length === 6 ? ids.map((_,i)=>`Step ${i+1}`) : name === 'strategy-roadmap' ? ['Proposed M1–4','Proposed M5–6'] : ['First','If justified']);
    assert.equal(geometry.edges.length,ids.length===6?6:1);
    if(ids.length===6) assert(geometry.edges.some(e=>e.id==='repeat'));
    for(const edge of geometry.edges) assert(edge.box.left>=0 && edge.box.right<=geometry.width+1 && edge.box.top>=0 && edge.box.bottom<=geometry.height+1, `clipped edge ${name} ${edge.id}`);
@@ -60,7 +60,9 @@ const views = {
          for(const theme of ['light','dark']) {
            const frameTop=await iframe.evaluate(n=>n.getBoundingClientRect().top+scrollY);
            await page.evaluate(y=>scrollTo({top:y-120,behavior:'instant'}),frameTop);
-            if(await frame.locator('html').getAttribute('data-theme')!==theme) await frame.locator('#btn-theme').click();
+            if(await frame.locator('html').getAttribute('data-theme')!==theme) {
              await frame.locator('#btn-theme').focus(); await page.keyboard.press('Enter');
            }
            await page.waitForFunction(t=>document.documentElement.dataset.theme===t,theme);
            const inline=await inspect(frame,name,width<1100);
            await frame.locator('#btn-preset').focus();await page.keyboard.press('Enter');
@@ -61,14 +61,14 @@ const fs = require('node:fs');
      assert.equal(response.status(), 200);
      assert.equal(await page.locator('h1').innerText(), 'Roadmap');
      const headings = page.locator('.strategy-content > h2');
-      assert.deepEqual((await headings.allTextContents()).map(s => s.replace(/\u200b/g, '')), ['Two stages toward Target','Stage 1: Delivery first','Improve within each phase','Delivery in practice']);
+      assert.deepEqual((await headings.allTextContents()).map(s => s.replace(/\u200b/g, '')), ['Six months, two investment decisions','Delivery first, replication only if earned','Keep one learning loop','Solo capacity and influence']);
      const text = await page.locator('.strategy-content').innerText();
      for (const marker of ['Humans direct, guide and review throughout', 'Delivery keeps improving', 'system-logic source', 'baseline', 'Target operating model']) assert(text.includes(marker), marker);
      assert(!text.includes('Supporting gate evidence and hold conditions\n\nThese are'));
      if (width < 700) await page.getByRole('button', {name:'Toggle navigation bar'}).click();
      const menu = page.locator('.theme-doc-sidebar-menu .menu__link').filter({visible:true});
      await menu.first().waitFor({state:'visible'});
-      assert.deepEqual((await menu.allTextContents()).slice(0,2), ['Target','Roadmap']);
+      assert.deepEqual((await menu.allTextContents()).slice(0,2), ['Six-month strategy','Roadmap']);
      if (width < 700) await page.getByRole('button', {name:'Close navigation bar'}).click();
      const panel = page.locator('.archify-panel--story').first();
      const iframe = panel.locator(width > 700 ? '.story-desktop' : '.story-mobile');
@@ -125,7 +125,7 @@ const fs = require('node:fs');
      const [download] = await Promise.all([page.waitForEvent('download'), frame.locator('[data-format="svg"]').click()]);
      assert.equal(await download.failure(), null);
      await download.saveAs(`${output}/${width}.svg`);
-      assert(fs.readFileSync(`${output}/${width}.svg`, 'utf8').includes('Adopt skills'));
+      assert(fs.readFileSync(`${output}/${width}.svg`, 'utf8').includes('Learn and test'));
      assert(fs.readFileSync(`${output}/${width}.svg`, 'utf8').includes('eldorado-roadmap-typography'));
      for (const id of ['skills','autonomy']) {
        await frame.locator(`svg[role="img"] [data-node-id="${id}"]`).screenshot({path:`${output}/${width}-${id}-card.png`});
@@ -23,17 +23,19 @@ const fs = require('node:fs');
        if (width < 700) await page.getByRole('button', {name:'Toggle navigation bar'}).click();
        const menu = page.locator('.theme-doc-sidebar-menu .menu__link').filter({visible:true});
        await menu.first().waitFor({state:'visible'});
-        assert.deepEqual(await menu.allTextContents(), ['Target', 'Roadmap', 'Stage - 01 - Skills Adoption', 'Stage - 02 - Autonomous Agent']);
+        assert.deepEqual(await menu.allTextContents(), ['Six-month strategy', 'Roadmap', 'One bounded experiment', 'Beyond six months']);
        assert((await menu.nth(0).getAttribute('href')).endsWith('/strategy/target-operating-model/'));
        assert((await menu.nth(1).getAttribute('href')).endsWith('/strategy/roadmap/'));
-        assert.equal(await menu.filter({hasText:/^Target$/}).count(), 1);
+        assert.equal(await menu.filter({hasText:/^Six-month strategy$/}).count(), 1);
        await page.screenshot({path:`${output}/${width}-${route ? 'target' : 'landing'}-navigation.png`,fullPage:true,animations:'disabled'});
        await menu.nth(1).click();
        await page.waitForURL('**/strategy/roadmap/');
        await page.getByRole('heading', {level:1,name:'Roadmap',exact:true}).waitFor();
        await page.goBack({waitUntil:'domcontentloaded'});
        await page.waitForURL('**/strategy/target-operating-model/');
-        const iframe = page.locator(`.archify-panel--story > .story-${width > 700 ? 'desktop' : 'mobile'}`);
+        await page.getByText('Conditional long-term Target operating model — not the six-month promise',{exact:true}).focus();
        await page.keyboard.press('Enter');
        const iframe = page.locator(`[data-diagram="strategy-target"] > .story-${width > 700 ? 'desktop' : 'mobile'}`);
        await iframe.scrollIntoViewIfNeeded();
        const frame = await (await iframe.elementHandle()).contentFrame();
        await frame.locator('svg[role="img"]').waitFor();
@@ -77,8 +79,9 @@ const fs = require('node:fs');
        }
        assert(metrics.labels.every(n=>n.px>=14), JSON.stringify(metrics.labels));
        assert.deepEqual(metrics.overflow, []);
-        await frame.locator('#btn-export').click();
+        await frame.locator('#btn-export').focus(); await page.keyboard.press('Enter');
-        const [download] = await Promise.all([page.waitForEvent('download'), frame.locator('[data-format="svg"]').click()]);
+        await frame.locator('[data-format="svg"]').focus();
        const [download] = await Promise.all([page.waitForEvent('download'), page.keyboard.press('Enter')]);
        assert.equal(await download.failure(), null);
        const exportPath = `${output}/${width}-${route ? 'target' : 'landing'}.svg`;
        await download.saveAs(exportPath);
@@ -46,7 +46,7 @@ const fs = require('node:fs');
        await page.waitForURL(`${base}/eldorado-v1/documentation/strategy/measurement/supported-bundle-coverage/`);
        await page.getByRole('heading', {level:1, name:'Supported bundle coverage', exact:true}).waitFor();
        assert((await page.locator('article').innerText()).includes('Supported bundle coverage'));
-        assert.equal(await page.locator('.breadcrumbs a').filter({hasText:'Stage - 01 - Skills Adoption'}).getAttribute('href'), '/eldorado-v1/documentation/strategy/stage-01-skills-adoption/');
+        assert.equal(await page.locator('.breadcrumbs a').filter({hasText:'One bounded experiment'}).getAttribute('href'), '/eldorado-v1/documentation/strategy/stage-01-skills-adoption/');
        assert((await page.locator('.breadcrumbs').innerText()).includes('Measurement'));
        await open();
        await menu.getByRole('link', {name:'Supported bundle coverage', exact:true}).waitFor({state:'visible'});
@@ -15,8 +15,8 @@ const fs = require('node:fs');
      page.on('pageerror', error => errors.push(error.message));
      const response = await page.goto(`${base}/eldorado-v1/documentation/strategy/measurement/`, {waitUntil:'networkidle'});
      assert.equal(response.status(), 200);
-      assert.equal(await page.locator('h1').innerText(), 'Skills Measurement');
+      assert.equal(await page.locator('h1').innerText(), 'Measuring real output');
-      assert((await page.title()).startsWith('Skills Measurement |'));
+      assert((await page.title()).startsWith('Measuring real output |'));
      assert.equal(await page.locator('.strategy-content details').count(), 1);
      assert.equal(await page.locator('.strategy-content details[open]').count(), 0);
      assert((await page.locator('.strategy-content details summary').innerText()).includes('Implementation status'));
@@ -28,7 +28,7 @@ const fs = require('node:fs');
      const menu = page.locator('.theme-doc-sidebar-menu .menu__link').filter({visible:true});
      await menu.first().waitFor({state:'visible'});
      const metrics = JSON.parse(fs.readFileSync('research/ai-adoption/measurement-migration.json','utf8')).metrics;
-      assert.deepEqual(await menu.allTextContents(), ['Target','Roadmap','Stage - 01 - Skills Adoption','Measurement',...metrics.map(m => m.title),'Collection and safeguards','Run the synthetic measurement example','Baseline','Governance','Quality','Adoption','Maintenance','Stage - 02 - Autonomous Agent']);
+      assert.deepEqual(await menu.allTextContents(), ['Six-month strategy','Roadmap','One bounded experiment','Measurement',...metrics.map(m => m.title),'Collection and safeguards','Run the synthetic measurement example','Baseline','Governance','Quality','Adoption','Maintenance','Beyond six months']);
      if (width < 700) await page.getByRole('button', {name:'Close navigation bar'}).click();
      const panel = page.locator('.archify-panel--story');
      const iframe = panel.locator(width > 700 ? '.story-desktop' : '.story-mobile');
@@ -6,10 +6,10 @@ const assert=require('node:assert/strict');
 const out=`.cache/skills-${process.argv[3]||'candidate'}`;fs.mkdirSync(out,{recursive:true});
 const browser=await chromium.launch({executablePath:process.env.PLAYWRIGHT_CHROMIUM_EXECUTABLE,args:['--no-sandbox']}); const results=[];
 try {
- for(const topic of ['measurement','baseline','governance','quality','adoption','maintenance','stage01','stage02']) for(const width of [1440,1024,390,320]) {
+ for(const topic of ['six-months','measurement','baseline','governance','quality','adoption','maintenance','stage01','stage02']) for(const width of [1440,1024,390,320]) {
  console.log(`Checking ${topic} at ${width}px`);
  const page=await browser.newPage({viewport:{width,height:900},colorScheme:'light'});const errors=[];page.on('pageerror',e=>errors.push(e.message));
-  const route=topic==='stage01'?'stage-01-skills-adoption':topic==='stage02'?'stage-02-autonomous-agent':['measurement','baseline'].includes(topic)?topic:`skills-${topic}`;
+  const route=topic==='six-months'?'target-operating-model':topic==='stage01'?'stage-01-skills-adoption':topic==='stage02'?'stage-02-autonomous-agent':['measurement','baseline'].includes(topic)?topic:`skills-${topic}`;
  assert.equal((await page.goto(`${base}/eldorado-v1/documentation/strategy/${route}/`,{waitUntil:'networkidle'})).status(),200);
  const panel=page.locator('.archify-panel--skills');assert.equal(await panel.count(),1);
  const iframe=panel.locator(width>1100?'.story-desktop':'.story-mobile');await iframe.scrollIntoViewIfNeeded();
@@ -6,14 +6,14 @@ const fs = require('node:fs');
  const output = `.cache/strategy-navigation-${process.argv[3] || 'local'}`;
  fs.mkdirSync(output, {recursive:true});
  const prefix = '/eldorado-v1/documentation/strategy/';
-  const first = 'Stage - 01 - Skills Adoption';
+  const first = 'One bounded experiment';
-  const second = 'Stage - 02 - Autonomous Agent';
+  const second = 'Beyond six months';
  const topics = ['Measurement','Baseline','Governance','Quality','Adoption','Maintenance'];
  const metrics = JSON.parse(fs.readFileSync('research/ai-adoption/measurement-migration.json','utf8')).metrics;
  const childIds = [...metrics.map(m => m.docId),'measurement/collection-and-safeguards','measurement/synthetic-example'];
  const childTitles = [...metrics.map(m => m.title),'Collection and safeguards','Run the synthetic measurement example'];
  const ids = ['target-operating-model','roadmap','stage-01-skills-adoption','measurement',...childIds,'baseline','skills-governance','skills-quality','skills-adoption','skills-maintenance','stage-02-autonomous-agent'];
-  const titles = ['Target','Roadmap',first,'Skills Measurement',...childTitles,'Baseline','Skills governance','Skills quality','Skills adoption','Skills maintenance',second];
+  const titles = ['First six months as AI Architect','Roadmap',first,'Measuring real output',...childTitles,'Baseline','Skills governance','Skills quality','Skills adoption','Skills maintenance',second];
  const browser = await chromium.launch({headless:true, executablePath:process.env.PLAYWRIGHT_CHROMIUM_EXECUTABLE, args:['--no-sandbox']});
  const results = [];
  try {
@@ -35,24 +35,24 @@ const fs = require('node:fs');
        assert.equal((await page.goto(`${base}${prefix}roadmap/`, {waitUntil:'networkidle'})).status(), 200);
        let menu = await openMenu();
        const visibleLabels = () => menu.locator('.menu__link').filter({visible:true}).allTextContents();
-        assert.deepEqual(await visibleLabels(), ['Target','Roadmap',first,second]);
+        assert.deepEqual(await visibleLabels(), ['Six-month strategy','Roadmap',first,second]);
        const category = menu.locator('.theme-doc-sidebar-item-category').filter({has:page.getByRole('link', {name:first, exact:true})});
        const caret = category.locator(':scope > .menu__list-item-collapsible > button.menu__caret');
        await caret.click();
        await category.getByRole('link', {name:'Governance', exact:true}).waitFor({state:'visible'});
-        assert.deepEqual(await visibleLabels(), ['Target','Roadmap',first,...topics,second]);
+        assert.deepEqual(await visibleLabels(), ['Six-month strategy','Roadmap',first,...topics,second]);
        assert.deepEqual(await category.locator('ul .menu__link').filter({visible:true}).allTextContents(), topics);
        const measurement = category.locator('.theme-doc-sidebar-item-category').filter({has:page.getByRole('link', {name:'Measurement', exact:true})});
        const reference = measurement.locator(':scope > .menu__list-item-collapsible > button.menu__caret');
        await reference.focus();
        await page.keyboard.press('Enter');
        await category.getByRole('link', {name:'Validated task success', exact:true}).waitFor({state:'visible'});
-        assert.deepEqual(await visibleLabels(), ['Target','Roadmap',first,topics[0],...childTitles,...topics.slice(1),second]);
+        assert.deepEqual(await visibleLabels(), ['Six-month strategy','Roadmap',first,topics[0],...childTitles,...topics.slice(1),second]);
        await reference.click();
        await page.screenshot({path:`${output}/${width}-expanded.png`, animations:'disabled'});
        await caret.click();
        await category.getByRole('link', {name:'Governance', exact:true}).waitFor({state:'hidden'});
-        assert.deepEqual(await visibleLabels(), ['Target','Roadmap',first,second]);
+        assert.deepEqual(await visibleLabels(), ['Six-month strategy','Roadmap',first,second]);
        await menu.getByRole('link', {name:first, exact:true}).click();
        await page.waitForURL(`${base}${prefix}stage-01-skills-adoption/`);
        await page.getByRole('heading', {level:1, name:first, exact:true}).waitFor();
@@ -64,8 +64,7 @@ const fs = require('node:fs');
          assert.equal((await page.goto(`${base}${prefix}${id}/`, {waitUntil:'networkidle'})).status(), 200);
          assert.equal(new URL(page.url()).pathname, `${prefix}${id}/`);
          // Target has a longer canonical page heading but keeps its short navigation label.
-          if (index) assert.equal(await page.locator('h1').innerText(), titles[index]);
+          assert.equal(await page.locator('h1').innerText(), titles[index]);
          else assert((await page.locator('h1').innerText()).includes('Target'));
          const prev = page.locator('.pagination-nav__link--prev');
          const next = page.locator('.pagination-nav__link--next');
          if (index) assert.equal(await prev.getAttribute('href'), `${prefix}${id === 'baseline' ? 'measurement' : ids[index-1]}/`);
@@ -76,7 +75,7 @@ const fs = require('node:fs');
            assert.equal(await page.locator('.breadcrumbs a').filter({hasText:first}).getAttribute('href'), `${prefix}stage-01-skills-adoption/`);
            menu = await openMenu();
            const expectedTopics = id === 'measurement' || id.startsWith('measurement/') ? [topics[0],...childTitles,...topics.slice(1)] : topics;
-            assert.deepEqual(await visibleLabels(), ['Target','Roadmap',first,...expectedTopics,second]);
+            assert.deepEqual(await visibleLabels(), ['Six-month strategy','Roadmap',first,...expectedTopics,second]);
            if (id.startsWith('measurement/')) assert.equal(await page.locator('.breadcrumbs a').filter({hasText:'Measurement'}).getAttribute('href'), `${prefix}measurement/`);
            await closeMenu();
          }
@@ -24,7 +24,7 @@ const fs=require('node:fs');
   assert.equal(geometry.nodes.length,(source.components||source.nodes).length,id);
   for(const n of geometry.nodes) assert(n.x>=0 && n.y>=0 && n.right<=geometry.width+1 && n.bottom<=geometry.height+1,`${id} ${width} clipped ${JSON.stringify(n)} / ${geometry.height}`);
   const data=await page.locator('.strategy-content').evaluate(el=>({words:el.innerText.trim().split(/\s+/).length,overflow:document.documentElement.scrollWidth>innerWidth,openDetails:el.querySelectorAll('details[open]').length}));
-   assert(data.words<=(id==='measurement'?1600:id==='roadmap'?600:550),id);assert(!data.overflow,id);assert.equal(data.openDetails,0,id);
+   assert(data.words<=(id==='measurement'?1900:id==='roadmap'?1150:['index','target-operating-model'].includes(id)?850:750),id);assert(!data.overflow,id);assert.equal(data.openDetails,0,id);
   await page.evaluate(()=>scrollTo({top:0,behavior:'instant'}));await page.screenshot({path:`.cache/story-${label}/${width}-${id}.png`,fullPage:true});
   const opener=panel.getByRole('button',{name:/^Expand /});await opener.click();
   const close=panel.getByRole('button',{name:'Close full-screen diagram',exact:true});await close.waitFor({state:'visible'});
@@ -131,6 +131,9 @@ function inspectTypography({mobile}) {
    for (const width of [1440,390,320]) {
      const page = await browser.newPage({viewport:{width,height:1000}});
      await page.goto(`${base}/eldorado-v1/documentation/strategy/target-operating-model/`,{waitUntil:'networkidle'});
      await page.addStyleTag({content:'html {scroll-behavior:auto !important;}'});
      await page.getByText('Conditional long-term Target operating model — not the six-month promise',{exact:true}).focus();
      await page.keyboard.press('Enter');
      const panel = page.locator('[data-diagram="strategy-target"]');
      const iframe = panel.locator(`:scope > .story-${width > 700 ? 'desktop' : 'mobile'}`);
      await iframe.scrollIntoViewIfNeeded();
@@ -141,10 +144,11 @@ function inspectTypography({mobile}) {
      await page.screenshot({path:`${output}/${width}-inline.png`,fullPage:true});
      const exported = [];
      for (const theme of ['light','dark']) {
-        if (await frame.locator('html').getAttribute('data-theme') !== theme) await frame.locator('#btn-theme').click();
+        if (await frame.locator('html').getAttribute('data-theme') !== theme) {await frame.locator('#btn-theme').focus(); await page.keyboard.press('Enter');}
        await frame.waitForFunction(t => document.documentElement.dataset.theme === t, theme);
-        await frame.locator('#btn-export').click();
+        await frame.locator('#btn-export').focus(); await page.keyboard.press('Enter');
-        const [download] = await Promise.all([page.waitForEvent('download'),frame.locator('[data-format="svg"]').click()]);
+        await frame.locator('[data-format="svg"]').focus();
        const [download] = await Promise.all([page.waitForEvent('download'),page.keyboard.press('Enter')]);
        assert.equal(await download.failure(),null);
        const path = `${output}/${width}-${theme}.svg`;
        await download.saveAs(path);
@@ -157,6 +161,10 @@ function inspectTypography({mobile}) {
        const typography = await standalone.evaluate(inspectTypography,{mobile:width < 700});
        assert.deepEqual(geometry.errors,[]);
        assert.deepEqual(typography.errors,[]);
        assert(await standalone.locator('#eldorado-target-caption').evaluate(g=>{
          const v=g.ownerSVGElement.viewBox.baseVal;
          return [...g.querySelectorAll('text')].every(t=>{const b=t.getBBox();return b.x>=v.x&&b.y>=v.y&&b.x+b.width<=v.x+v.width&&b.y+b.height<=v.y+v.height;});
        }), 'Standalone proposed caption must fit the complete canvas');
        const background = await standalone.locator('rect.c-bg-rect').evaluate(n => getComputedStyle(n).fill);
        if (exported.length) assert.notEqual(background,exported[0].background,'standalone theme must change');
        // CDP captures SVG documents without Playwright's HTML-body screenshot wait.
@@ -167,7 +175,7 @@ function inspectTypography({mobile}) {
        exported.push({theme,background,geometry,typography});
        await standalone.close();
      }
-      await panel.getByRole('button',{name:/^Expand /}).click();
+      await panel.getByRole('button',{name:/^Expand /}).focus(); await page.keyboard.press('Enter');
      const full = await (await panel.locator('dialog iframe').elementHandle()).contentFrame();
      await full.locator('svg[role="img"]').waitFor();
      // The existing fullscreen viewer always opens the radial desktop source.
@@ -4,6 +4,7 @@ import {execFileSync} from 'node:child_process';
 import {skillsViewer, isSkillsStory} from './skills-viewer.mjs';
 import {roadmapViewer} from './roadmap-viewer.mjs';
 import {targetRouting} from './target-routing.mjs';
 import {targetCaption} from './target-caption.mjs';
 import {createHash} from 'node:crypto';
 const cli = 'vendor/archify/bin/archify.mjs';
 const types = new Set(['architecture','workflow','sequence','dataflow','lifecycle']);
@@ -43,6 +44,7 @@ for (const file of readdirSync('diagrams').sort()) {
  // Verify the upstream artifact first, then add the scoped portal integration.
  let viewer = readFileSync(output, 'utf8');
  if (name === 'strategy-target') viewer = targetRouting(viewer);
  if (/^strategy-target(-mobile)?$/.test(name)) viewer = targetCaption(viewer);
  // Upstream intentionally disables preset selection in gallery embeds. Enable
  // only those two guards; fail closed if a future vendor update changes them.
  const start = viewer.indexOf('Archify.preset = (function () {');
@@ -30,7 +30,7 @@ export function roadmapViewer(html, spec) {
      return `<text x="${x+24}" y="${y+top}" font-size="${size}" class="${cls}" ${attrs}>${lines.map((line,i) => `<tspan x="${x+24}" dy="${i ? 34 : 0}">${escape(line)}</tspan>`).join('')}</text>`;
    };
    if (!node.sublabel || node.tag || /Output:|Exit:|\n/.test(node.sublabel)) throw new Error(`Roadmap content contract drift: ${node.id}`);
-    const number = spec.nodes.length === 6 ? `Step ${index+1}` : spec.nodes[0].id === 'skills' ? `Stage ${index+1}` : index === 0 ? 'First' : 'Then';
+    const number = spec.nodes.length === 6 ? `Step ${index+1}` : spec.nodes[0].id === 'skills' ? ['Proposed M1–4','Proposed M5–6'][index] : index === 0 ? 'First' : 'If justified';
    const content = text(number, 40, 26, 't-primary', 'data-stage-number="" font-weight="700"')
      + text(node.label, 88, 30, 't-primary', 'data-node-label="" font-weight="700"')
      + text(node.sublabel, 160, 26, 't-muted');
@@ -12,8 +12,8 @@ test('Roadmap has three visual levels and preserves human direction and Delivery
  const page = read('docs/strategy/roadmap.mdx');
  const visible = page.split('<details>')[0];
  assert.deepEqual([...visible.matchAll(/<ArchifyDiagram name="([^"]+)"/g)].map(m => m[1]), Object.keys(views));
-  assert.deepEqual([...visible.matchAll(/^## (.+)$/gm)].map(m => m[1]), ['Two stages toward Target', 'Stage 1: Delivery first', 'Improve within each phase', 'Delivery in practice']);
+  assert.deepEqual([...visible.matchAll(/^## (.+)$/gm)].map(m => m[1]), ['Six months, two investment decisions', 'Delivery first, replication only if earned', 'Keep one learning loop', 'Solo capacity and influence']);
-  for (const marker of ['Humans direct, guide and review throughout', 'standardizes skills', 'foundation for Stage 2', 'future Autonomous Agent', 'not deployed autonomy', 'order is not yet decided', 'Delivery keeps improving', 'not as six global roadmap stages', 'what skills exist, how they relate, when they are used and how they work together', 'codebase structure', 'existing principles', 'system-logic source', 'tests', 'builds and packaging', 'deployments', 'practices, tooling, controls and problems', 'metrics/KPIs and a baseline', 'friction and feedback', './measurement/index.mdx', './target-operating-model.mdx']) assert(visible.includes(marker), marker);
+  for (const marker of ['Humans direct, guide and review throughout', 'current', 'AI-assisted practice', 'One active live pilot at a time', 'Month 1', 'Month 2', 'Month 3', 'Month 4', 'Month 5', 'Month 6', 'Delivery keeps improving', 'what skills exist, how they relate, when they are used and how they work together', 'codebase structure', 'existing principles', 'system-logic source', 'tests', 'builds and packaging', 'deployments', 'retain/change/hold/stop', './measurement/index.mdx', './target-operating-model.mdx']) assert(visible.includes(marker), marker);
  for (const marker of ['revocation','exact-artifact approvals','idempotency','human takeover','sensitive decisions','security findings','reproducible baseline']) assert(page.includes(marker), marker);
  assert(!/## [1-5]\.|Prepare foundations|Sustain and improve/.test(page));
 });
@@ -4,19 +4,19 @@ import {readFileSync} from 'node:fs';
 const read = p => readFileSync(p, 'utf8');
 const stages = ['Scope', 'Architecture', 'UI/UX', 'Planning', 'Delivery', 'UAT', 'Security', 'Releases'];
-test('Strategy opens at the canonical autonomous lifecycle', () => {
+test('Strategy opens at the assignment and retains autonomy only as a conditional reference', () => {
  assert.match(read('sidebars/strategy.ts'), /strategySidebar:\s*\[\s*'target-operating-model',\s*'roadmap'/);
-  assert.match(read('docs/strategy/target-operating-model.mdx'), /^sidebar_label: Target$/m);
+  assert.match(read('docs/strategy/target-operating-model.mdx'), /^sidebar_label: Six-month strategy$/m);
  for (const id of ['target-operating-model']) {
    const page = read(`docs/strategy/${id}.mdx`);
    const primary = page.split('<details>')[0];
-    assert(primary.includes('name="strategy-target"'));
+    assert(primary.includes('name="strategy-six-months"'));
-    assert(primary.includes('autonomous agent'));
+    assert(!primary.includes('name="strategy-target"'));
-    assert(primary.includes('direct, guide and review'));
+    assert(page.includes('Conditional long-term Target operating model'));
-    assert(primary.includes('Scope → Architecture → UI/UX → Planning → Delivery → UAT → Security → Releases → Scope'));
+    assert(page.includes('Scope → Architecture → UI/UX → Planning → Delivery → UAT → Security → Releases → Scope'));
-    assert(primary.includes('human-controlled AI Agent'));
+    assert(page.includes('human-controlled AI Agent'));
    assert(!/code[ -]agent/i.test(page));
-    assert(primary.includes('TO-BE'));
+    assert(primary.includes('Proposed strategy'));
    assert(!/only routes|People authorize|independent gates protect release/.test(primary));
  }
 });
@@ -6,7 +6,7 @@ const read = path => readFileSync(path, 'utf8');
 test('Skills Measurement is a visible optional registry, separate from workflow application', () => {
  const page = read('docs/strategy/measurement/index.mdx');
-  assert.match(page, /title: Skills Measurement\nsidebar_label: Measurement/);
+  assert.match(page, /title: Measuring real output\nsidebar_label: Measurement/);
  for (const heading of ['Establish the baseline', 'Measure the pilot', 'Extend collection as adoption grows', 'Keep the collection running']) assert(!page.includes(heading), heading);
  assert(page.includes('Registry inclusion does not require a metric to be used, collected or baselined'));
  assert(page.includes('../baseline.mdx'));
@@ -41,7 +41,7 @@ test('domain contracts retain human authority, honest measures and Delivery-firs
 const text=t=>JSON.stringify(JSON.parse(read(`diagrams/strategy-${t}.architecture.json`)));
 assert(text('governance').includes('Author is not sole approver'));
 assert(text('quality').includes('Critical effect blocks'));
- assert(text('adoption').includes('Delivery first')&&text('adoption').includes('Later order undecided'));
+ assert(text('adoption').includes('Delivery first')&&text('adoption').includes('Retain / improve / hold / stop'));
 assert(text('adoption').includes('No quotas or rankings'));
 for(const marker of ['Workflow effectiveness','Skills effectiveness & health','Quality: artifact fitness + safety','No mandatory collection','Before / after is not causality','Candidate / approved regression'])assert(text('measurement').includes(marker),marker);
 assert(text('maintenance').includes('No automatic reinstatement'));
@@ -1,9 +1,9 @@
 // Native editable geometry and edges; scoped editorial typography for Stage 01.
-export const isSkillsStory = name => /^strategy-(governance|quality|adoption|measurement|baseline|maintenance|stage01|stage02)(-mobile)?$/.test(name);
+export const isSkillsStory = name => /^strategy-(governance|quality|adoption|measurement|baseline|maintenance|stage01|stage02|six-months)(-mobile)?$/.test(name);
 const escape = text => text.replaceAll('&', '&amp;').replaceAll('<', '&lt;').replaceAll('>', '&gt;').replaceAll('"', '&quot;');
 export function skillsViewer(html, spec) {
  if (spec.diagram_type !== 'architecture' || !spec.components.length) throw new Error('Skills story contract drift');
-  const stageMobile = /strategy-stage0[12]-mobile\//.test(spec.meta.output);
+  const stageMobile = /strategy-(stage0[12]|six-months)-mobile\//.test(spec.meta.output);
  const detailSize = stageMobile ? 38 : spec.meta.output.includes('-mobile/') ? 34 : 32;
  for (const node of spec.components) {
    const pattern = new RegExp(`<g\\b[^>]*data-node-id="${node.id}"[^>]*>[\\s\\S]*?<text data-node-label=[\\s\\S]*?</g>`);
@@ -11,7 +11,7 @@ test('Strategy has Target, Roadmap, a linked Skills Adoption category and Autono
  runInNewContext(compiled, sandbox);
  const sidebar = JSON.parse(JSON.stringify(sandbox.exports.default.strategySidebar));
  assert.deepEqual(sidebar, ['target-operating-model', 'roadmap', {
-    type:'category', label:'Stage - 01 - Skills Adoption',
+    type:'category', label:'One bounded experiment',
    link:{type:'doc', id:'stage-01-skills-adoption'}, collapsed:true,
    items:[
      {type:'category', label:'Measurement', collapsed:true, link:{type:'doc', id:'measurement/index'}, items:[
@@ -26,7 +26,7 @@ test('Strategy has Target, Roadmap, a linked Skills Adoption category and Autono
    ],
  }, 'stage-02-autonomous-agent']);
-  assert.match(read('docs/strategy/target-operating-model.mdx'), /^sidebar_label: Target$/m);
+  assert.match(read('docs/strategy/target-operating-model.mdx'), /^sidebar_label: Six-month strategy$/m);
  assert.match(read('docusaurus.config.ts'), /type: 'docSidebar', docsPluginId: 'strategy', sidebarId: 'strategySidebar', label: 'Strategy'/);
 });
@@ -34,8 +34,8 @@ test('stage overviews explain the foundation and future without replacing topic
  const first = read('docs/strategy/stage-01-skills-adoption.mdx');
  const second = read('docs/strategy/stage-02-autonomous-agent.mdx');
  for (const [id, title, page] of [
-    ['stage-01-skills-adoption', 'Stage - 01 - Skills Adoption', first],
+    ['stage-01-skills-adoption', 'One bounded experiment', first],
-    ['stage-02-autonomous-agent', 'Stage - 02 - Autonomous Agent', second],
+    ['stage-02-autonomous-agent', 'Beyond six months', second],
  ]) {
    assert(page.includes(`id: ${id}\ntitle: ${title}`));
    for (const link of ['./roadmap.mdx', './target-operating-model.mdx']) assert(page.includes(link));
@@ -43,7 +43,7 @@ test('stage overviews explain the foundation and future without replacing topic
  for (const id of ['measurement/index','baseline','skills-governance','skills-quality','skills-adoption','skills-maintenance']) assert(first.includes(`./${id}.mdx`));
  for (const marker of ['human + AI Agent','Delivery first','order is not yet decided','KPIs','baseline','topology','feedback','new current situation']) assert(first.includes(marker), marker);
  for (const marker of ['future','proven skills','measurements','working practices','direction and review','not deployed autonomy','approved KPI thresholds']) assert(second.includes(marker), marker);
-  assert.match(read('docs/strategy/measurement/index.mdx'), /^title: Skills Measurement\nsidebar_label: Measurement$/m);
+  assert.match(read('docs/strategy/measurement/index.mdx'), /^title: Measuring real output\nsidebar_label: Measurement$/m);
 });
 test('old Strategy entry redirects to Target instead of maintaining a second document', () => {
@@ -18,7 +18,8 @@ test('every strategy page leads with a compact diagram story and closes its refe
    assert(/\*\*(Next|Continue the loop):\*\*/.test(narrative), id);
    assert(!narrative.includes('| ---'), id);
    const words = narrative.replace(/<[^>]*>/g, '').trim().split(/\s+/).length;
-    assert(words <= (id === 'measurement' ? 1600 : id === 'roadmap' ? 600 : 500), `${id}: ${words} default narrative words`);
+    const budget = id === 'measurement' ? 1900 : id === 'roadmap' ? 1150 : id === 'target-operating-model' ? 850 : 750;
    assert(words <= budget, `${id}: ${words} default narrative words`);
  }
 });
@@ -36,7 +37,7 @@ test('mobile story diagrams preserve the same nodes and directed relationships',
    const desktop = JSON.parse(read(`diagrams/${name}.architecture.json`));
    const mobile = JSON.parse(read(`diagrams/${name}-mobile.architecture.json`));
    assert(desktop.components.length >= 5, name);
-    const semantic = d => ({nodes:d.components.map(({pos,size,...n})=>n),edges:d.connections.map(({fromSide,toSide,route,via,labelAt,...e})=>e)});
+    const semantic = d => ({nodes:d.components.map(({pos,size,...n})=>n),edges:d.connections.map(({fromSide,toSide,route,via,labelAt,label,...e})=>e)});
    assert.deepEqual(semantic(desktop), semantic(mobile), name);
    assert(desktop.connections.every(e => (e.label || e.id.startsWith('govern-') || /^strategy-(governance|quality|adoption|measurement|maintenance)$/.test(name)) && e.from !== e.to), name);
    assert.equal(desktop.meta.legend.mode, 'hidden');
@@ -0,0 +1,16 @@
 // Caption the retained optional target without changing its native topology.
 // Text lives inside the SVG so standalone exports retain proposal/line semantics.
 export function targetCaption(html) {
  const roots = [...html.matchAll(/<svg\b[^>]*role="img"[^>]*>/g)];
  if (roots.length !== 1) throw new Error('Target caption SVG contract drift');
  const root = roots[0][0];
  const match = /viewBox="([\d. -]+)"/.exec(root);
  if (!match) throw new Error('Target caption requires viewBox');
  const [x,y,w,h] = match[1].trim().split(/\s+/).map(Number);
  const size = Math.min(26, w / 30);
  const lines = ['Proposed optional target — not a six-month commitment',
    'Solid: lifecycle · Dotted: execution / governance', 'Dashed: human-controlled contributions'];
  const extra = size * 5;
  const caption = `<g id="eldorado-target-caption" aria-label="Proposed target legend">${lines.map((line,i) => `<text x="${x+20}" y="${y+h+size*(1.2+i*1.3)}" font-family="Arial, sans-serif" font-size="${size}" style="font-size:${size}px!important" class="t-primary">${line}</text>`).join('')}</g>`;
  return html.replace(root, root.replace(match[0], `viewBox="${x} ${y} ${w} ${h+extra}"`) + caption);
 }
@@ -27,9 +27,9 @@ if (process.argv.includes('--build')) {
  assert(redirect.includes('/eldorado-v1/documentation/strategy/target-operating-model/'));
  assert(redirect.includes('window.location.href') && redirect.includes('http-equiv="refresh"') && !redirect.includes('archify-panel'), 'Landing must redirect, not duplicate Target');
  const strategyPages = [...model.pages,
-    {id:'stage-01-skills-adoption', title:'Stage - 01 - Skills Adoption'},
+    {id:'stage-01-skills-adoption', title:'One bounded experiment'},
    {id:'baseline', title:'Baseline'},
-    {id:'stage-02-autonomous-agent', title:'Stage - 02 - Autonomous Agent'},
+    {id:'stage-02-autonomous-agent', title:'Beyond six months'},
  ];
  for (const {id, title} of strategyPages) {
    const route = `strategy/${id === 'index' ? '' : `${id}/`}index.html`;
@@ -5,7 +5,7 @@ export default {
    'roadmap',
    {
      type: 'category',
-      label: 'Stage - 01 - Skills Adoption',
+      label: 'One bounded experiment',
      link: {type: 'doc', id: 'stage-01-skills-adoption'},
      collapsed: true,
      items: [
@@ -12,7 +12,7 @@ export default function ArchifyDiagram({name, title, compact = false, story = fa
  const headingId = useId();
  const [expanded, setExpanded] = useState(false);
  const [narrowRoadmap, setNarrowRoadmap] = useState(false);
-  const skillsStory = /^strategy-(governance|quality|adoption|measurement|baseline|maintenance|stage01|stage02)$/.test(name);
+  const skillsStory = /^strategy-(governance|quality|adoption|measurement|baseline|maintenance|stage01|stage02|six-months)$/.test(name);
  useEffect(() => {
    if (!name.startsWith('strategy-roadmap') && !skillsStory) return;
    const media = window.matchMedia(skillsStory ? '(max-width: 1100px)' : '(max-width: 999px)');
@@ -115,7 +115,8 @@ a:focus-visible, button:focus-visible {outline: 3px solid #b88719; outline-offse
 .archify-panel--story[data-diagram^="strategy-roadmap"] > .story-desktop {aspect-ratio: auto; height: 300px;}
 .archify-panel--story[data-diagram="strategy-roadmap-loop"] {--roadmap-height: 1840px;}
 .archify-panel--story[data-diagram="strategy-roadmap-loop"] > .story-desktop {height: 460px;}
-.archify-panel--story[data-diagram="strategy-target"] > iframe {aspect-ratio: 1620 / 1430;}
+.archify-panel--story[data-diagram="strategy-target"] > iframe {aspect-ratio: 1225 / 1151;}
 .strategy-content > details:has([data-diagram="strategy-target"]) {padding-inline: 0;}
 .strategy-content > details {margin: .65rem 0; border: 1px solid var(--line); padding: .8rem 1rem; background: var(--surface);}
 .strategy-content summary {cursor: pointer; font-weight: 700;}