Developer-Productivity

AI agents produce better output when the codebase is ready for them. Here are the four dimensions of codebase readiness that account for most of the gap.

AI agents are stateless by default. Here's how memory systems actually work, covering the storage patterns, lifecycle triggers, and architecture behind agents that remember you.

How I built a bash-based agent loop that pulls work from Linear, implements features, runs code review, and opens pull requests autonomously.

MCPs give Claude capabilities. Skills teach Claude workflows. Here's the mental model I use to decide which one I need.

How Claude Code's context window works: what consumes tokens (MCP servers, tools, messages), why it matters, and how to manage context effectively.

After 8 months with Claude Code, here's my complete workflow. Learn how I combine Linear, MCP servers, and Obsidian for AI-assisted development that works.