Letting AI coding agent run autonomously with access to your network, your secrets, and your entire machine is risky. One rogue call is all it takes. One way to help protect yourself is to use microVM isolation to control the environment and what the agent can access. Docker Sandboxes is one such solution. I’ll walk you through setting it up and exploring some of its file system, network management, and monitoring capabilities.

Ever set up a Copilot skill that worked perfectly – except when the model decided not to load it? Skills are optional by design; the model picks them up or it doesn’t. When you need context present every single time without exception, that’s a gap skills simply can’t fill. And that’s what hooks are for. I’ll walk through how to wire up a hook that fires automatically on every single prompt, injecting exactly the right context before the model sees your request – and when a session-level hook makes more sense instead.

Ever written a Copilot skill that started clean – then became a sprawling mess of conditionals as you define how to work with different versions of some product? You’re not alone. I’ll show you how a tiny wrapper script can detect your environment and hand Copilot only the instructions that actually apply, keeping your skills small and your model focused. I’ll also unpack the supply-chain security question this technique forces you to take seriously.

Ever wondered exactly how much a single Copilot chat request actually costs? VS Code already logs the precise breakdown for every model call … if you know where to find it. In this post, I crack open one real log entry and walk through the math step by step so you can read your own usage data with confidence.