As AI coding tools spread through your engineering org, your dashboards show a "productivity boom" right up until incidents spike, rollbacks climb, and architectural consistency quietly falls apart. This is engineering quality collapse disguised as productivity, and it's becoming the default failure mode of AI-assisted development at scale.

This strategy and methodology session introduces a vendor-neutral, 5-layer operating model (Access & Governance, Context Architecture, Quality Gates, Measurement & ROI, and Rollout Strategy) that treats AI-assisted engineering as a true asset. You'll hear about defining decision rights, risk tiers, and non-negotiable controls so teams can move faster and preserve correctness, maintainability, and operational trust.

You'll walk away with a concrete model you can adapt to your org before "AI productivity" shows up as instability in production.