Write an enterprise architecture decision record
In this article (4 sections)
An architecture diagram shows what exists; a decision record explains why. That history matters when assumptions change, a reviewer challenges the trade-off or a successor is tempted to repeat a rejected option.
Build the decision artifact
Keep one decision per record. State the concrete context and forces, status, chosen option, considered alternatives, positive and negative consequences, supporting evidence, owner, date and review trigger. Link to tests and measurements rather than copying them into prose that will go stale.
The enterprise delivery lab makes this reasoning executable with synthetic data:
from enterprise_cases import architecture_decision_case
result = architecture_decision_case()
assert result["complete"] is True
assert result["alternatives"] == 2
assert result["tradeoff_recorded"] is True
assert result["adr"]["status"] == "accepted"ADR-014 chooses persisted state-transition events for a multi-day approval workflow. It names two alternatives, a benefit, a cost and a volume threshold that reopens the choice. accepted means the synthetic team decided; it does not mean the architecture is permanently correct.
Test the failure path
Records fail when they are retrospective justification, contain only the winning option or never change status. Write them while the decision is open, invite the affected operators and security owners, and supersede rather than silently editing history.
Save evidence that another reviewer can inspect:
- numbered ADR with owner and status
- links to benchmark and failure tests
- review comments from affected owners
- supersession or review trigger
This exercise aligns with the enterprise delivery, secure integration, operations and leadership work in the FDE for Professionals course. The course link describes the pathway; this local draft and its synthetic verifier do not claim that a client deployment, security approval or production result occurred.
Practice task
Write a one-page record for deterministic workflow versus autonomous agent. Include the strongest rejected alternative and a measurable condition that reopens the decision.
Continue learning
This article is part of the Enterprise AI delivery and architecture sequence. Use the neighbouring tasks when you need the prerequisite or the next application.
- Review the prerequisite or neighbouring task in Separate reusable product features from client customization.
- Continue with Plan a controlled rollout across business units.
Reference: Architecture Decision Records reference.
Pankit Kumar has 10 years in Data Science & AI, building and shipping production systems in regulated pharma and clinical environments. He is a freelance trainer at Boston Institute of Analytics, AnalytixLabs and Scaler, and has taught this material to thousands of working professionals.
This article is part of our FDE for Professionals programme — 16 weeks (proposed). An accelerated advanced pathway for IT professionals ready to own enterprise AI delivery.
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