The AI-Ready Developer Environment — Local Setup, Reproducibility, and Docker

Modern AI development adds a new layer of complexity to the development environment: agent harnesses, agent-specific developer tooling, MCP servers, external services, credentials, and more. And every team has different requirements. How do you give developers and agents the tools they need while keeping environments consistent, reproducible, and secure?

In this hands-on session, you’ll start with Docker Sandboxes and then go deeper into customizing and sharing sandbox-based development environments. You’ll create sbx kits to tailor the tools and configuration available inside a sandbox, connect to external services—including those that require secure credential injection—and package those customizations for reuse.

You’ll then use sbxenv, which brings a Docker Compose-like experience to sandboxes, to define an entire development environment as configuration. By the end, you’ll have an environment that can be shared with your team and started with a single command—giving every developer and agent a consistent, ready-to-use workspace.