Architecture

How Centaur Works

Four layers. Human vision in. Working software out. Governed at every stage.

ORCHESTRATION

The Chief of Staff layer. Terence coordinates agents, maintains persistent memory, monitors the factory, and escalates to the human when it matters. Everything flows through here — task routing, governance gates, progress tracking.

TerencePeteMayaAna

DELIVERY TEAM

The engineering layer. Nic builds to spec, Ralph gates quality, Scott provides daily intelligence, Quill handles content, Livy owns visual design. Every stage has a named agent accountable for it. Nothing advances without sign-off.

NicRalphScottQuillLivy

GOVERNANCE RAIL

Runs alongside every stage. Mission Control gives real-time visibility across every agent, project, and pipeline. The Governance Feed logs every commit, decision, and handoff. Anomaly detection flags stalls, quality regressions, and cost spikes before they become problems.

Mission ControlGovernance FeedAnomaly DetectionAudit Trail

COUNCIL

Multi-model peer review. Before significant work ships, the Council — GPT, Gemini, and Claude — cross-validate the approach. AI peer review as a standard practice, not an afterthought. PASS, REVISE, or BLOCK.

GPTGeminiClaude

Spec-Driven Development

The Spec is the Contract

Every build starts with a validated spec. The spec is the interface between Maya (Architect) and Nic (Engineer). Nothing gets built without it — and nothing ships without Ralph's gate.

The spec ID is embedded in every record, creating end-to-end traceability from source intent to deployed output. Change the spec, re-run, get an updated build. Reproducible, auditable, diff-friendly.

Sample BronzeSpec (Blueprint)

{
  "spec_id": "bronze_species_plus_v1",
  "source_api": "https://api.speciesplus.net/api/v1/taxon_concepts",
  "target_schema": "agents_and_pencils_dev.bronze",
  "target_table": "species_plus_taxa",
  "columns": [
    { "source_path": "id", "target_name": "taxon_concept_id", "data_type": "INT" },
    { "source_path": "full_name", "target_name": "scientific_name", "data_type": "STRING" },
    { "source_path": "higher_taxa", "target_name": "higher_taxa", "data_type": "STRING" }
  ],
  "incremental_strategy": "append",
  "quality_mode": "warn"
}

Built Using Centaur

Blueprint & Schemata

Blueprint and Schemata are separate products — data platform accelerators built using Centaur. They are proof the model works. Both can be delivered as standalone engagements or alongside a Centaur project.

Blueprint (Databricks) and Schemata (Fabric) platform architecture
ComponentBlueprint (Databricks)Schemata (Fabric)
Bronze ingestionDLT notebooks + AutoLoaderPySpark notebooks + Data Factory
Silver transformsDLT with ExpectationsMLVs with CHECK CONSTRAINT
Gold modellingDLT with ExpectationsMLVs + PySpark MERGE
Quality enforcement@dlt.expect (warn/drop/fail)CONSTRAINT CHECK (drop/fail)
DeploymentDABs YAMLfabric-cicd Python library
BI endpointSQL WarehouseDirectLake (zero-copy)
CI/CDGitHub → Databricks syncGitHub/ADO → Fabric sync