If you’ve ever reviewed a Git diff after regenerating an API client, you know the struggle – dozens of timestamp lines changing across every file, burying the actual work you care about. What if Git could quietly ignore those lines without ever touching the files themselves? There’s a built-in Git feature designed exactly for this, and it only takes two configuration steps to unlock. Let me show you how to keep your diffs clean and focused.

Ever spent time carefully documenting your project’s folder structure in a copilot-instructions.md file? You’re not alone – it’s one of the most common things developers add. But here’s the thing: VS Code’s Copilot extension already injects a workspace tree into every conversation automatically. And when that tree gets truncated, the LLM has tools to explore further on its own. In this post, I’ll show you what’s happening under the hood so you can spend those instruction tokens on things that genuinely matter.

Every conversation with AI starts from scratch – no memory of yesterday’s debugging session, your team’s naming conventions, or the architectural decision you patiently explained three times last week. Agentic memory changes that. It gives AI assistants the ability to accumulate knowledge over time, turning them from stateless tools into collaborators that genuinely improve. In this post, I’ll walk you through the different types of memory and show you how VS Code and GitHub Copilot put these ideas into practice today.

Have you ever tried to ask the AI to create multiple subagents? Or seen an agent that explicitly requests multiple subagents do the same task? The mechanics behind that pattern are more interesting than they appear. In this post, I’ll show you why this pattern works so well – from cleaner context and richer coverage to stronger critique loops – so you can decide when it is worth using in your own workflow.