Out of the box, Claude Code treats every repository the same. The difference between autocomplete and a coworker is configuration: layered memory, deterministic hooks, skills, MCP servers, and worktrees. Here’s how to build each layer — and how we applied it to a large .NET codebase.
No new model. Five orchestration features. And a roomful of engineers raising their hands when asked who had shipped a pull request that week written entirely by AI.
Event sourcing has always been a tough sell — powerful, but too much work for most teams. AI coding assistants change the cost side of that equation.
Andrej Karpathy dropped a GitHub Gist that got 5,000+ stars in days. Not a framework. Not a library. An idea file. Here’s what the LLM Wiki pattern is, why it’s different from RAG, and what it means for developers who use AI agents daily.
Opus 4.6 is now the default model in Claude Code. With 1M tokens of context and an 80.8% SWE-bench score, it’s the biggest single-generation jump yet. Here’s what changes for .NET developers.
I write less code than ever. And yet I’m more productive. The question is no longer ‘how do I implement this?’ but ‘what should be built here and why?’
Claude Code is powerful on its own. But when you split the work across specialized sub-agents — a test writer, a reviewer, a documentation agent — it becomes a team.
A developer pastes a connection string into ChatGPT. Another copies customer data to test something. We’ve all been close. Here’s how to think about what’s safe to share and what isn’t.
Claude Code knows your code. But it doesn’t know your build server, your deployment pipeline, or your inbox. MCP changes that.
Everyone has that one service class that’s grown too large. I used Claude Code to split an 800-line monolith into clean components — in under an hour.