Building a Linear-Driven Agent Loop with Claude Code
How I built a bash-based agent loop that pulls work from Linear, implements features, runs code review, and opens pull requests autonomously.
Hi, my name is
I help experienced engineers and teams ship better software with AI, smarter workflows, and real-world decision-making.
Currently a Senior Software Engineer at August Health, where I build clinical software that helps senior living operators deliver better resident care. Previously CTO at Buoy Software, where I grew the team from zero to 50+ and shipped FDA-cleared medical device software.
I advise founders and teams on architecture, AI integration, and engineering execution. 15+ years building production systems has taught me that trade-offs matter more than best practices — and I enjoy helping teams navigate those decisions.
If you're building in healthcare, SaaS, or applied AI, I'd love to hear about it.
Writings
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.
LLMs don't have access to the current date, causing issues in time-based analysis. Here's how to fix date and time handling in production LLM systems with explicit context.
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.
Three design principles for context-efficient MCP servers: filter at source, pre-aggregate data, work creatively. Real reductions: 746k→262 tokens.