Teams often treat AI autonomy as an all-or-nothing choice. Either Copilot suggests a few lines, or an agent receives permission to edit files, run commands, and make decisions across the project. Neither extreme fits every task.

In this focused session, I’ll introduce a simple autonomy dial based on blast radius, reversibility, and risk. We’ll turn it up for scaffolding, boilerplate, and repetitive changes, then dial it back for security, authentication, financial logic, and unclear requirements.

You’ll see how smaller scopes, explicit stop conditions, validation checkpoints, and human approval let teams gain speed without handing critical decisions to the model.

Takeaways
- Match autonomy to the task’s blast radius.
- Use checkpoints for critical code paths.
- Keep humans responsible for approval and merge.