Workshop 2 - When code is cheap, governance is the hard part
The Challenge Code generation is close to free now. Review, sign-off, and audit are not, and that gap lands squarely on engineering leaders. In this session, I'll show you where AI-generated changes actually fail before production, and how automated checks and audit trails hold humans and AI to the same standard without slowing releases. What You'll Do & Take Away Hands-on from minute five, you will take a repository, ask an AI agent to change it, and close the loop. You'll put your standards where the agent reads them by wiring a live rules check into the agent's own turn over MCP, making it fix its own violations before the code reaches you. By the end, you leave with a working repository, the configuration, and a reusable skill running on the AI coding tool of your choice. Who Should Attend Anyone who writes code with an AI tool, and anyone who has to sign it off. What to Bring & How to Prepare Primary Setup: Bring a laptop with a browser and a free GitHub account. The repository opens directly in GitHub Codespaces, so there is nothing to install, and a free AI coding account is enough for every task. Power Users: If you already use Claude Code, Cursor, Codex, Windsurf, Replit, or another MCP client, feel free to bring that instead. No Laptop? No Problem: Every step is demonstrated live on screen, and pairing with the person next to you works fine. The repository stays public so you can redo everything afterwards on your own time.