It is a risky approach with expensive consequences, where any material gains in productivity can be wiped out by one well-intentioned `sudo rm -rf`at worst, and undermined by long-term pain at best in the form of security risks, technical debt, unmaintainable code, as well as source code and token leaks.

Just like a human developer, AI requires the right tools and clear context to contribute in a meaningful way. It needs a safe place to experiment, fail, try again, and get closer to a useful result. It needs a reproducible workspace that enforces quotas, limits access to sensitive information, and can be audited.

This session will teach you how to build the infrastructure for your team to collaborate productively, securely, and safely with AI coding agents. You will learn from examples drawn from Anthropic and Coder's own experiments with AI agents - where the technology excels (spoilers: documentation, quick prototyping) and where they still struggle. You will walk away with practical next steps on how to reap the benefits of this rapidly changing technology without sacrificing security and reliability.