Where AI Shines (and Where You Still Need a Human Touch)An AI-Enhanced Daily Workflow (That Compounds over Time)Plan and Design with AI (Brainstorm, Then Draft an Architecture Decision Record)From Requirements to Backlog: Turning Product Requirements Documents into Work ItemsImplement with a “Tests First, Then Code” PatternCode Review: AI as an Amplifier, Not a GatekeeperAfter the Code: Docs, Observability, and CommunicationFictional Example: Sam’s AI-Powered WorkdayFeeding the AI Context: Getting Repository Awareness RightSecurity First: Build AI into Your Secure Development LifecyclePrivacy, Licensing, and Compliance: Guardrails You Can’t SkipDon’t Feed the AI Sensitive DataWatch Out for Licensing and Attribution IssuesStay Aware of AI-Related Regulations Where You OperateAlign with Risk Management Frameworks (They’re Helpful, Really!)AI Agents: What They Can Do and How to Keep Them TamedMeasuring Impact: How to Quantify AI’s Effect Like an EngineerAdoption and Behavior MetricsQuality and Throughput MetricsPrompt Patterns That Actually Work (Templates to Reuse)Rolling AI Out to Your Team: A 90-Day PlanDays 0–30: Establish Foundations and GuardrailsDays 31–60: Scale Up and Train the TeamDays 61–90: Optimize and Decide on Next StepsA Checklist for Leaders: Evaluating AI Tools and PlatformsBridging to What You Already Know (Connecting the Dots with Previous Chapters)Building Consensus with Evidence: How to Have Effective Discussions About AI Adoption