About

I work on the reliability layer between AI agents, workflows, and human operators. My focus is AI workflow reliability: the practical systems work that makes AI products observable, debuggable, and trustworthy in production.

I help founders and teams understand why AI workflows fail, how to trace those failures, and how to operate systems with better feedback loops. The work spans agent observability, workflow debugging, human-in-the-loop operations, and reliable AI infrastructure.

This site is where I publish reliability essays, failure analyses, case studies, and reports about the demo-to-production gap in AI systems.