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Architecture Intent

Strategic Vision

  • What we are building: A composable, lightweight operating architecture for enterprise architecture practice that converts proven operational models into reusable, governed workflows across intake, evidence handling, analysis, decision support, and delivery enablement.
  • Why it exists: To scale architectural capacity and consistency while eliminating avoidable toil, preserving full traceability from business intent to delivery evidence, and protecting human architectural judgement and accountability.

Project Context

primary_context: ea4all-automation aw_count: 3 alignment_findings: 2

Current State Alignment

The system is partially aligned. While empirical evidence coverage is complete (100%) and SDD validation CI controls are active, architecture delivery exhibits governance and structural gaps: execution currently relies on global platform ADRs without local ADR records (ALIGN-001), runtime capabilities lack an authoritative inventory.yaml baseline (ALIGN-002), and the codebase remains a monolithic entrypoint awaiting modular pipeline decomposition (ALIGN-003).

Focus Areas / Roadmap

  • {'phase': 'Immediate Foundation', 'objective': 'Establish Local Governance Baseline and Capability Inventory', 'actions': ['Instantiate local ADR repository and author ADRs governing runtime boundaries and evidence intake.', 'Generate authoritative inventory.yaml tracking core modules and entrypoints pursuant to ADR-038.']}
  • {'phase': 'Architectural Refinement', 'objective': 'Decompose Monolithic Core into Composable Pipeline Modules', 'actions': ["Refactor 'ea4all-automation-main-comp' into explicit intake, classification, and synthesis components.", 'Implement deterministic intermediate artifact models to decouple evidence ingestion from narrative rendering.']}
  • {'phase': 'Capability Expansion', 'objective': 'Deploy Evidence-Rich Intake Experiments and Governance Gates', 'actions': ['Introduce automated artifact consistency validators and structured gap diagnostics.', 'Incorporate human-in-the-loop review hooks into pipeline orchestration workflows.']}

Gaps & Tensions (Risks)

  • Governance Deficit: Evolution map schedules [READY] items, but lack of local ADR persistence breaches single-source-of-truth standards (ALIGN-001).
  • Capability Traceability: ADR-038 adoption mandates a project-level inventory.yaml, which is currently absent, inhibiting automated delta verification (ALIGN-002).
  • Structural Monolith vs. Pipeline Vision: Codebase implementation is centralized in 'ea4all-automation-main-comp', conflicting with the intended discrete multi-stage pipeline (ALIGN-003).
  • Global vs. Local Authority: Reliance on inherited global CAS ADRs obscures project-specific trade-offs and runtime boundaries.

Principles

  • {'name': 'Delivery Problem First', 'statement': 'Start with a concrete delivery challenge rather than a technology opportunity; build the smallest useful solution and validate it in production.'}
  • {'name': 'Evidence Before Narrative', 'statement': 'Ground all synthesis in verifiable source evidence and structured intermediate models; narrative must align with inspectable evidence.'}
  • {'name': 'Explicit Uncertainty', 'statement': 'Expose assumptions, gaps, and confidence scores openly; never manufacture artificial certainty from incomplete data sets.'}
  • {'name': 'AI as Augmentation', 'statement': 'Employ AI for synthesis, interpretation, and leverage, strictly retaining mandatory human review for consequential architectural judgement.'}
  • {'name': 'Guardrails Over Gatekeeping', 'statement': 'Provide actionable, automated feedback and clear behavioral guardrails rather than opaque, obstructive procedural gates.'}
  • {'name': 'Decision Traceability', 'statement': 'Ensure all material choices are traceable from business intent and raw evidence through to execution consequences and delivery outcomes.'}

Emergent Heuristics

automation_qualification: Automate a delivery task deterministically if its execution is repeatable, its schema is bounded, and its output is verifiable without semantic ambiguity. ai_leverage_boundary: Deploy generative interpretation solely where unstructured ambiguity requires semantic synthesis, routing the raw outputs into structured intermediate representations prior to publication. governance_instantiation: Promote global platform architectural decisions into local project ADRs whenever implementation requires container-specific interface or workflow definitions.