You’ll learn where AI helps most (planning, building, testing, reviewing) and how to keep the team in control.

You’ll learn a simple “context + constraints + examples” pattern that reliably generates dev-ready results.

You’ll learn how to have AI draft acceptance criteria and test ideas that your team can verify and refine.

You’ll learn how to use AI to propose tests first, keep them meaningful, and avoid “tests that test nothing.”

You’ll learn how to constrain AI output to your architecture, conventions, and security requirements.

You’ll learn review prompts that catch bugs, clarify intent, and enforce standards—without bikeshedding.

You’ll learn how to generate realistic test data and isolate failures faster with structured debugging prompts.

You’ll learn lightweight policies for privacy, security, attribution, and “what AI can/can’t decide.”