AI has made writing software dramatically cheaper and faster. But faster code doesn't automatically mean better engineering or happier developers.

As AI takes care of more of the mechanical work, the real challenges are shifting toward context, complexity, decision-making, and cognitive load. The ability to generate more code can easily turn into the pressure to do more, learn more, and ship more.

In this session, we'll explore:

- How to use AI to amplify engineering judgment, rather than simply generating more code.
- How endless AI-generated code, experiments, and iterations can create complexity debt.
- Why AI-assisted development can increase cognitive load instead of reducing it.
- Practical ways to design an AI-assisted development workflow that keeps humans focused, effective, and sane.

By the end of this session, you'll have:

- A better understanding of the hidden costs of AI-assisted development.
- Practical strategies for managing AI-generated complexity and context.
- A sustainable approach to using AI that prioritizes impact over output.

The goal isn't to write more code. The goal is to build better software without burning ourselves out in the process.