Archives for 2026

For years, my git worktree setup was modest: two worktrees for active development, and one more for code reviews. Three worktrees, tops. It worked. I never questioned it.

Then AI coding agents arrived — tools that write code, run tests, and iterate autonomously — and suddenly three worktrees felt like a bottleneck. Each agent needs its own isolated workspace. Each task deserves its own branch, its own directory, its own terminal. The question shifted from "how many worktrees can I manage?" to "how many can I run in parallel?"

A few years ago, I wrote about how ReSharper's Search with Pattern feature helped me refactor a massive C# codebase in minutes. The technique was powerful, but creating those custom search and replace patterns meant using ReSharper to define them. Alternatively, you could hand-craft XML in DotSettings files—tedious work that required memorizing the exact structure, generating GUIDs, and configuring placeholder properties correctly.

Recently, I explored how Agent Skills are becoming an open standard that works across different AI coding assistants like GitHub Copilot, Cursor, and JetBrains Junie. This got me thinking: what if I could combine these two powerful developer tools? What if an Agent Skill could automate the tedious part of creating ReSharper and Rider patterns?

This post shows how I built exactly that—a practical Agent Skill that generates properly formatted DotSettings XML for custom search and replace patterns in Rider and ReSharper, just by describing what you want in natural language to your AI coding assistant.

.NET 11 Preview 1 ships a groundbreaking feature: Runtime Async. Instead of relying solely on the C# compiler to rewrite async/await methods into state machines, the .NET runtime itself now understands async methods as a first-class concept. This article explores what Runtime Async is, why it matters, what changed in Preview 1, and how you can experiment with it today.

When Anthropic introduced Agent Skills for Claude, it appeared to be another proprietary AI customization feature. Today, we're witnessing something far more significant: an open standard reshaping how people across roles—developers, designers, product managers, and operations—work with AI assistants. AI coding agents' adoption of Agent Skills has transformed this technology from an interesting experiment into an essential developer tool.

If you've been using custom instructions or wondering how to make your AI assistant truly understand your project's workflows, Agent Skills provides a compelling solution.