Feb 24
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AI can write code and suggest architectures — but enterprise delivery requires more than intelligence. It requires governance: control, auditability, approvals, and rollback. In this demo, I show an AI-assisted Azure delivery workflow where AI moves from “talking” to “delivering” — inside enterprise rules. What you’ll see: I enter requirements as plain text (one command) An Orchestrator coordinates three AI agents: discovery-agent: captures the real tenant state (evidence) planner-agent: turns intent + facts into a delivery plan executor-agent: generates repo-ready IaC and pipeline YAML The system creates a new branch and commits the generated files Delivery runs through Git + Azure DevOps: PR → CI validation + What-If → approval gate → CD deployment I approve or reject the gate after CI — that decision controls whether CD proceeds Key takeaway: AI accelerates discovery, planning, and delivery preparation — while production remains protected by the same DevOps controls enterprise teams already trust. If you’re a Solutions Architect or cloud delivery lead, this pattern shows how to use AI to speed up delivery without compromising governance.