Agile + AI

Agile in the Age of AI Beginner What changes in agile when AI writes much of the code, and what stays exactly the same. AI-Assisted vs AI-Native Teams Beginner Using AI to speed up the old way of working, or redesigning the way of working around AI? The difference, and how to tell which you are. AI Pair Programming Beginner Working with an AI coding assistant as a pairing partner: what it's good at, where it misleads, and how to keep the human in charge. Agentic Development Teams Practitioner Teams where AI agents take on whole tasks, such as fixing a bug or writing a feature, under human direction and review. Human-in-the-Loop Review Beginner Keeping a human responsible for checking and approving AI-generated work before it ships. Spec-Driven Development Practitioner Writing clear, testable specifications first and letting AI generate code from them, so the spec becomes the main artifact. User Stories for AI Agents Practitioner How to write backlog items an AI agent can execute well, without losing the conversation that makes stories work. Estimation and Velocity with AI Practitioner When AI does much of the building, effort-based estimates and velocity lose meaning. What to measure instead. Eval-Driven Development Practitioner Building AI-powered features by defining evaluations first: test sets that measure whether the AI's output is good enough. AI in Scrum Events Beginner Practical ways AI can support Sprint Planning, the Daily Scrum, Review and Retrospective, and where it shouldn't replace people. AI Code Review Practitioner Using AI to review code and reviewing AI-written code: two different jobs, both needing human judgment. AI and Technical Debt Practitioner AI can create technical debt faster than ever, or help pay it down faster than ever. Which one depends on your habits. AI in Testing Practitioner Using AI to write and run tests, and the new question it raises: who checks that the tests are right? AI in Product Discovery Practitioner Using AI to speed up research synthesis and prototyping, without replacing real contact with users. Building AI Features with Agile Practitioner How agile practices adapt when the feature itself is powered by AI: uncertainty, evals and continuous monitoring. AI and the Definition of Done Beginner Updating your Definition of Done so AI-generated work meets the same bar as everything else. How AI Changes Agile Roles Beginner What shifts for Product Owners, Scrum Masters, Developers and testers when AI joins the team. AI Governance for Agile Teams Practitioner Lightweight rules for using AI safely in agile teams: data, security, accountability and transparency. AI Adoption Anti-Patterns Practitioner Common ways teams get AI adoption wrong, and what to do instead. AI and Developer Skills Practitioner How AI changes what developers need to learn, and how teams keep growing real expertise, especially in juniors.