Full Platform Release
Use this for releases that go from SOW to production dashboards and trained users. All 15 artifact types are in scope.
Workflow
/wire:new # release_type: full_platform
# Phase 1: Requirements
/wire:requirements-generate <release-folder>
/wire:requirements-validate <release-folder>
/wire:requirements-review <release-folder>
# Phase 2: Design
/wire:conceptual_model-generate <release-folder>
/wire:conceptual_model-validate <release-folder>
/wire:conceptual_model-review <release-folder>
/wire:pipeline_design-generate <release-folder>
/wire:pipeline_design-validate <release-folder>
/wire:pipeline_design-review <release-folder>
/wire:data_model-generate <release-folder>
/wire:data_model-validate <release-folder>
/wire:data_model-review <release-folder>
/wire:mockups-generate <release-folder>
/wire:mockups-review <release-folder>
# Phase 3: Development
/wire:pipeline-generate <release-folder>
/wire:pipeline-validate <release-folder>
/wire:pipeline-review <release-folder>
/wire:dbt-generate <release-folder>
/wire:dbt-validate <release-folder>
/wire:utils-run-dbt <release-folder>
/wire:dbt-review <release-folder>
/wire:orchestration-generate <release-folder> # choose Dagster or dbt Cloud
/wire:orchestration-validate <release-folder>
/wire:orchestration-review <release-folder>
/wire:semantic_layer-generate <release-folder>
/wire:semantic_layer-validate <release-folder>
/wire:semantic_layer-review <release-folder>
/wire:dashboards-generate <release-folder>
/wire:dashboards-validate <release-folder>
/wire:dashboards-review <release-folder>
# Phase 4: Testing
/wire:data_quality-generate <release-folder>
/wire:data_quality-validate <release-folder>
/wire:data_quality-review <release-folder>
/wire:uat-generate <release-folder>
/wire:uat-review <release-folder>
# Phase 5: Deployment
/wire:deployment-generate <release-folder>
/wire:deployment-validate <release-folder>
/wire:deployment-review <release-folder>
/wire:utils-deploy-to-dev <release-folder>
/wire:utils-deploy-to-prod <release-folder>
# Phase 6: Enablement
/wire:training-generate <release-folder>
/wire:training-validate <release-folder>
/wire:training-review <release-folder>
/wire:documentation-generate <release-folder>
/wire:documentation-validate <release-folder>
/wire:documentation-review <release-folder>
/wire:archive <release-folder>
A worked example of a Full Platform engagement — using a fictional client scenario with realistic command output, agent delegation, and reviewer decisions — is available in the Tutorial: Full Platform.
Phase 1: Requirements (Day 1)
After /wire:new completes, copy the SOW PDF and any source materials into the release's requirements/ directory. Ensure engagement/sow.md and engagement/context.md are populated.
/wire:requirements-generate reads the SOW and engagement context, extracts structured requirements (functional, non-functional, data, technical, user), maps each SOW deliverable to the framework artifacts that will produce it, and writes requirements/requirements_specification.md.
Ready criteria: requirements artifact is review: approved.
Phase 2: Design (Days 2–4)
The design phase follows a defined sequence. The conceptual model gates everything else.
Step 1: Conceptual entity model
/wire:conceptual_model-generate produces a business-level entity model: an inventory of domain entities, a Mermaid erDiagram (entity names and relationships, no columns), and a relationship narrative.
Review audience: business stakeholders, not just the technical team. Approving entities here constrains everything that follows.
Step 2: Pipeline design + data flow diagram
/wire:pipeline_design-generate produces the full pipeline architecture document — source system analysis, replication scenarios with cost analysis, scheduling, error handling, design decisions requiring client input — plus an embedded Data Flow Diagram (DFD).
Step 3: Data model specification + physical ERD
/wire:data_model-generate produces the complete dbt-layer data model specification — source definitions, staging models, integration models, warehouse models with surrogate keys and FK paths, seed files — plus an embedded Physical ERD.
This is the most important review gate in the full-platform workflow. Approving a model with incorrect grain, wrong join keys, or missing entities is expensive to fix after dbt code is generated.
Step 4: Dashboard mockups
/wire:mockups-generate produces dashboard wireframes. Review with end users, not the technical stakeholder.
Ready criteria: all four design artifacts are review: approved.
Phase 3: Development (Days 5–8)
/wire:dbt-generate generates all dbt models from the approved data model specification. The generation embeds comprehensive analytics engineering conventions: field naming rules (_pk, _fk, _ts, is_/has_ prefixes), field ordering, SQL style rules, and multi-source framework support. Includes YAML documentation files and automated tests (not_null + unique on every PK, relationships on every FK — typically 40–50 tests for a mid-sized engagement).
/wire:orchestration-generate prompts you to choose between Dagster (Python-native, assets-first) and dbt Cloud (managed scheduling).
/wire:semantic_layer-generate generates LookML views, explores, measures, and dimension definitions from the approved dbt models.
Ready criteria: all four development artifacts are review: approved and dbt tests passing.
Phase 4: Testing (Days 9–10)
/wire:data_quality-generate generates additional data quality tests beyond the embedded dbt tests: freshness checks, row count reconciliation, cross-system validation, custom business rules.
/wire:uat-generate generates a UAT plan mapped to the functional requirements. Do not proceed to deployment without UAT sign-off.
Phase 5: Deployment (Day 11)
/wire:deployment-generate generates the deployment runbook, CI/CD pipeline configuration, monitoring and alerting setup, and rollback procedures.
Phase 6: Enablement (Days 12–13)
/wire:training-generate generates two training packages:
- Data team enablement: technical session plan (2 hours)
- End user training: dashboard usage session (90 minutes)
Utility commands available at any phase
/wire:utils-run-dbt— Runs the generated dbt models in dbt Cloud or locally/wire:utils-deploy-to-dev— Deploys to the development environment/wire:utils-deploy-to-prod— Deploys to the production environment/wire:utils-meeting-context— Retrieves Fathom meeting transcripts for context/wire:utils-jira-sync— Syncs artifact status to Jira issues/wire:utils-atlassian-search— Searches Confluence for documentation
Tip: Run
/wire:playbook-generate <release-folder>after requirements are approved to get a visual end-to-end plan for this release.