Agentic Data Stack Release

The Agentic Data Stack release type (release_type: agentic_data_stack) is an overlay for an existing data platform — it assumes a warehouse, a dbt project, and a BI tool are already in place. The deliverable is a governed self-service analytics capability: an AI that answers business questions accurately and stays accurate as the data platform evolves.

This is not a platform build. If a client's warehouse and dbt project don't yet exist, start with full_platform or pipeline_only first.

When to use it

A client already has a data platform and wants an AI that can answer business questions reliably
The data team has tried a self-service SQL agent and accuracy is below 70%
The engagement goal is to reduce analyst time spent answering ad-hoc data questions

Phase overview

Phase	Duration	Artifacts
Audit	1–2 weeks	dataset_audit, metric_audit, query_audit
Design	1 week	governance_design, semantic_layer_design
Build	2 weeks	canonical_models, lookml_views (Looker only), semantic_layer, knowledge_skill, agent_config
Validation	1 week	eval_suite, adversarial_config
Launch	3–5 days	launch_gate, enablement

Command sequence

# Phase 1 — Audit (run all three in parallel)
/wire:ads-audit-all YYYYMMDD_client_agentic_data_stack

# Or run individually:
/wire:ads_dataset-audit-generate YYYYMMDD_client_agentic_data_stack
/wire:ads_metric-audit-generate YYYYMMDD_client_agentic_data_stack
/wire:ads_query-audit-generate YYYYMMDD_client_agentic_data_stack

# Validate and review each audit
/wire:ads_dataset-audit-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_dataset-audit-review YYYYMMDD_client_agentic_data_stack
/wire:ads_metric-audit-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_metric-audit-review YYYYMMDD_client_agentic_data_stack
/wire:ads_query-audit-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_query-audit-review YYYYMMDD_client_agentic_data_stack

# Phase 2 — Design
/wire:ads_governance-design-generate YYYYMMDD_client_agentic_data_stack
/wire:ads_governance-design-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_governance-design-review YYYYMMDD_client_agentic_data_stack
/wire:ads_semantic-layer-design-generate YYYYMMDD_client_agentic_data_stack
/wire:ads_semantic-layer-design-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_semantic-layer-design-review YYYYMMDD_client_agentic_data_stack

# Phase 3 — Build
/wire:ads_canonical-models-generate YYYYMMDD_client_agentic_data_stack
/wire:ads_canonical-models-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_canonical-models-review YYYYMMDD_client_agentic_data_stack

# LookML views — Looker projects only
/wire:ads_lookml-views-generate YYYYMMDD_client_agentic_data_stack
/wire:ads_lookml-views-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_lookml-views-review YYYYMMDD_client_agentic_data_stack

/wire:ads_semantic-layer-generate YYYYMMDD_client_agentic_data_stack
/wire:ads_semantic-layer-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_semantic-layer-review YYYYMMDD_client_agentic_data_stack
/wire:ads_knowledge-skill-generate YYYYMMDD_client_agentic_data_stack
/wire:ads_knowledge-skill-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_knowledge-skill-review YYYYMMDD_client_agentic_data_stack
/wire:ads_agent-config-generate YYYYMMDD_client_agentic_data_stack
/wire:ads_agent-config-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_agent-config-review YYYYMMDD_client_agentic_data_stack

# Phase 4 — Validation
/wire:ads_eval-suite-generate YYYYMMDD_client_agentic_data_stack
/wire:ads_eval-suite-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_eval-suite-review YYYYMMDD_client_agentic_data_stack
/wire:ads_adversarial-config-generate YYYYMMDD_client_agentic_data_stack
/wire:ads_adversarial-config-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_adversarial-config-review YYYYMMDD_client_agentic_data_stack

# Phase 5 — Launch
/wire:ads_launch-gate-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_launch-gate-review YYYYMMDD_client_agentic_data_stack
/wire:ads_analytics-enablement-generate YYYYMMDD_client_agentic_data_stack
/wire:ads_analytics-enablement-validate YYYYMMDD_client_agentic_data_stack
/wire:ads_analytics-enablement-review YYYYMMDD_client_agentic_data_stack

Tutorial available

A worked example of a Agentic Data Stack engagement — using a fictional client scenario with realistic command output, agent delegation, and reviewer decisions — is available in the Tutorial: Agentic Data Stack.

The eval suite and launch gate

The eval suite is the most important artifact in the release. It produces:

Per-domain YAML question-answer pairs (minimum 10 per domain)
A CI runner script that checks accuracy against every schema change
Per-domain accuracy thresholds (default 90%)

A domain that falls below its threshold is blocked until the specific failing questions are fixed. Anthropic documented accuracy falling from 95% to 65% within a month without active maintenance. The eval suite and its CI integration are the mechanism that prevents this.

Knowledge skill colocation

The /wire:ads_knowledge-skill-generate command writes DOMAIN_REFERENCE.md files into the client's dbt project alongside their mart models:

models/marts/
  orders/
    fct_orders.sql
    fct_orders.yml
    DOMAIN_REFERENCE.md   ← generated and maintained here
  customers/
    dim_customers.sql
    dim_customers.yml
    DOMAIN_REFERENCE.md

A CI check template is included that flags when a model PR doesn't update the collocated reference file.

What the release delivers

At engagement end, the client has:

A governance-clean dbt project with canonical models
An extended semantic layer covering the most common analytical questions
Per-domain knowledge skill files in their dbt repo, with CI maintenance checks
An installable Wire skill (agentic-data-stack-SKILL.md) their data team runs in Claude Code
A per-domain eval suite wired into CI with accuracy baselines
User training documentation and a data team maintenance guide

When to use it​

Phase overview​

Command sequence​

The eval suite and launch gate​

Knowledge skill colocation​

What the release delivers​