Every AI demo builds a flashy app from an empty folder. Your job is managing a system that's been in production for a decade that nobody fully understands - and the AI confidently invents an endpoint that doesn't exist.
Let's close that gap. You'll see how to point AI at the real, existing code you already own, whatever your stack: feeding it actual context instead of clever prompt tricks, encoding your team's standards as reusable Skills, handing real work to agents, and grounding the model so it's accurate about your systems and willing to tell you you're wrong instead of agreeing with everything you say. Includes a live demo that ends with the moment the AI stops being a yes-man and pushes back.
Takeaways:
- Give AI your project's real context so it stops hallucinating about your systems
- When to encode team standards as reusable Skills, and when it's not worth it
- Which tasks in your existing codebase are safe to hand to an agent, and which aren't
- Ground a model and cut hallucinations on your own code, not a toy dataset