Workflows

Ten orchestrated BPMN workflows chain the catalog's agents into end-to-end delivery pipelines — from scoping an AI product to running a project post-mortem. Each workflow is a versioned definition executed and quality-gated by the Agentic Runtime: every step is an agent, every handoff carries context forward, and eval-gates decide whether the chain proceeds.

How a workflow is defined

Each workflow file carries a YAML identity card, an ASCII BPMN flow diagram, per-agent step sheets, and a final deliverable checklist. Core agents run the backbone; optional agents attach on context (GDPR, SAFe, business case, organizational change). In high-stakes runs, an optional independent counter-review gate (AI Methodology Auditor) can be inserted before the final report — it challenges methodological rigor, it never redoes the domain work. Each identity card also carries a recommended model for the run; the operator keeps the final say on which model actually executes the chain.

The ten workflows

ID	Workflow	Domain	Agents	Duration	Status
WF-001	AI Product Scoping	Agile & Product	4–10	45–90 min	✅ Live — 3 / 3
WF-002	SAFe Agile Delivery	Agile & Product	6–8	60–120 min	✅ Live — 5 / 5
WF-003	AI Application Launch	Dev & Engineering	7–12	90–180 min	✅ Live — 7 / 7
WF-004	AI Consulting Engagement	Management & Consulting	6–9	60–90 min	Available
WF-005	Strategic Intelligence & Growth	Management & Consulting	3–6	30–60 min	Available
WF-006	Pre-sales / Commercial Proposal	Management & Consulting	6–9	75–120 min	Available
WF-007	Mission Onboarding — Day 1–5	Management & Consulting	4–6	45–75 min	Available
WF-008	AI Act / GDPR Compliance Audit	Compliance & Governance	7–11	90–150 min	Available
WF-009	IT / AI Recruitment	HR & Talent	4–7	60–90 min	Available
WF-010	Project Post-mortem	Management & Consulting	4–8	45–75 min	Available

Three backbones are proven live, end to end (details below). The other seven are defined and available, not yet run live.

Gallery

WF-001 — AI Product Scoping

Agile & Product · 4–10 agents · 45–90 min

Problem — A client brief lands, or a product idea needs shaping, but there is no prioritized backlog and no acceptance criteria to build against.
Capability — Chains four core agents — Business Analyst → UX Designer → Product Owner (Scrum) → QA Agile — turning a raw brief into a MoSCoW-prioritized initial backlog with Gherkin acceptance criteria.
Proof — ✅ Proven live, end to end: 3 / 3 steps passed against catalog v3.27.0. See the run →

WF-002 — SAFe Agile Delivery

Agile & Product · 6–8 agents · 60–120 min

Problem — A PI Planning is starting, or an ART sprint kicks off, and the team needs aligned PI objectives, a prioritized program backlog, and reporting the executive committee will trust.
Capability — Chains six core agents — Product Manager SAFe → Release Train Engineer → Product Owner SAFe → Scrum Master → QA Agile → AI Project Manager — producing WSJF-prioritized PI objectives, a sprint plan, and an executive-committee dashboard.
Proof — ✅ Proven live, end to end: 5 / 5 steps passed against catalog v3.27.0. See the run →

WF-003 — AI Application Launch

Dev & Engineering · 7–12 agents · 90–180 min

Problem — A business case is validated and the green light is given, but going from idea to a deployed, secured AI application spans architecture, code, CI/CD, and a security audit.
Capability — The densest pipeline in the catalog: Financial Analyst → Prompt Engineer → AI Architect → AI Python Developer → QA Agile → DevOps / Cloud → AI Security — delivering a deployed app, an operational CI/CD pipeline, and a passed OWASP LLM security audit.
Proof — ✅ Proven live, end to end: 7 / 7 steps passed against catalog v3.27.0. See the run →

WF-004 — AI Consulting Engagement

Management & Consulting · 6–9 agents · 60–90 min

Problem — An AI consulting engagement is signed, and the client expects a maturity diagnostic, a costed roadmap, a training plan, and an executive-ready deliverable — not just an opinion.
Capability — Chains six core agents — AI Consultant → Financial Analyst → CDO / Chief AI Officer → Change Manager → AI Trainer → AI Content Writer — producing a maturity audit, a 12–24 month roadmap with AI OKRs, an ADKAR adoption plan, and an executive summary.
Proof — Defined and available (v1.1); not yet run live.

WF-005 — Strategic Intelligence & Growth

Management & Consulting · 3–6 agents · 30–60 min

Problem — A weekly cadence or a detected market signal needs to become a qualified synthesis and publishable thought-leadership content, fast and at controlled cost.
Capability — Chains three core agents — Strategic Intelligence → AI Growth / Marketing → AI Content Writer — turning raw signals into a qualified intelligence radar, an SEO content plan, and posts ready to publish.
Proof — Defined and available (v1.1); not yet run live.

WF-006 — Pre-sales / Commercial Proposal

Management & Consulting · 6–9 agents · 75–120 min

Problem — An RFP arrives, and winning it means a GO/NO-GO decision plus a full technical-commercial proposal: scope, architecture, schedule, person-day costing, price, and prospect ROI.
Capability — Chains six core agents — AI Consultant → Business Analyst → AI Architect → AI Project Manager → Financial Analyst → AI Content Writer — producing a qualification verdict, a target architecture, a costed schedule, and the final commercial proposal.
Proof — Defined and available (v1.0); not yet run live.

WF-007 — Mission Onboarding — Day 1–5

Management & Consulting · 4–6 agents · 45–75 min

Problem — A new engagement starts, and the first days set the tone: a kickoff plan, a Day-1 kit, a mapped client context, and the right relationships must exist by Day 5.
Capability — Chains four core agents — AI Project Manager → Business Analyst → Change Manager → AI Content Writer — producing a kickoff plan with a provisional RACI, a client context sheet, a stakeholder engagement plan, and a Day-1 report.
Proof — Defined and available (v1.0); not yet run live.

Compliance & Governance · 7–11 agents · 90–150 min

Problem — An AI system must be audited under regulatory pressure — a CNIL / AI Office inspection or M&A due diligence — where a mis-qualified risk tier exposes the organization to penalties.
Capability — Chains seven core agents — AI Legal → AI Architect → AI Security → Data Engineer → CDO → Change Manager → AI Content Writer — producing an obligations matrix (AI Act + GDPR + NIS2), a risk mapping, a prioritized remediation plan, and target governance. An optional AI Methodology Auditor gate can challenge the audit's rigor before finalization.
Proof — Defined and available (v1.0); not yet run live.

WF-009 — IT / AI Recruitment

HR & Talent · 4–7 agents · 60–90 min

Problem — An IT / AI hiring need is identified, and filling it means a precise profile, a defensible technical assessment, an anti-fraud sourcing pass, and a publishable offer.
Capability — Chains four core agents — Business Analyst → AI Consultant → AI HR → AI Content Writer — producing a need sheet with must/nice criteria, a technical assessment grid, a scored shortlist with deepfake/CV fraud checks, and a publishable job ad.
Proof — Defined and available (v1.0); not yet run live.

WF-010 — Project Post-mortem

Management & Consulting · 4–8 agents · 45–75 min

Problem — A project closes or a major incident hits, and the lessons risk evaporating without a structured root-cause analysis and a shared improvement plan.
Capability — Chains four core agents — AI Project Manager → QA Agile → Change Manager → AI Content Writer — producing a timeline with a 5-Whys analysis, a quality and technical-debt review, a team review, and a lessons-learned report. An optional AI Methodology Auditor gate can challenge the root-cause reasoning before the improvement plan is set.
Proof — Defined and available (v1.0); not yet run live.

Proven live

Three workflows have been run end to end by the runtime — real runs, not mock-ups — with every step passing its eval-gate against catalog v3.27.0:

Workflow	Steps	Result
WF-001 — AI Product Scoping	3	3 / 3 passed
WF-002 — SAFe Agile Delivery	5	5 / 5 passed
WF-003 — AI Application Launch	7	7 / 7 passed

Per-step verdicts and the verbatim run JSON are on the live proofs page.

Workflows orchestrate the catalog's 38 agents and run on the Agentic Runtime. Certifications named in each workflow describe a simulated persona's knowledge frame, not credentials held by the author, the software, or the model — see the catalog disclaimer.