What I'm up to

My main focus right now is AI-powered code analysis tooling. I shipped claude-audit, a CLI that analyzes your entire codebase for security vulnerabilities using a multi-agent architecture with specialized domain agents. It's on npm, has 6 stars and growing.

Working on llm-ocr, converting PDFs to clean markdown using vision LLMs instead of traditional OCR. The results are surprisingly good for documents with mixed layouts.

Also building this very site. Designed to be machine-readable by AI models while still being a good experience for humans. Check /llms.txt.

How LLMs can be better tools for developers rather than replacements. The gap between AI hype and practical utility is still enormous. Most AI features in products today feel bolted on. I want to figure out the patterns that make AI genuinely useful.

Interested in ideas that can genuinely impact people. The technology is the easy part. The hard part is finding problems that matter, and building tools that real users actually keep coming back to.

Developer experience as a design discipline. Good DX isn't just documentation. It's the API surface, error messages, sensible defaults, and respecting the developer's time.

End-to-end product pipelines. The journey from PRD to production: architecture decisions, deployment, observability, the boring bits that decide whether a product survives or not.

AI tooling and the future of coding.The space moves weekly. I spend real time catching up on new models, agent patterns, and IDE workflows, so I don't fall behind the curve.

Professional standards and engineering practices. Code review discipline, testing strategy, documentation. The habits that separate side projects from real products you can hand to someone else.