About Me

I’ve spent 30 years figuring out how large organizations deliver software without breaking things. CI/CD pipelines, progressive deployments, GitOps, DORA metrics, team enablement across five companies and roles from systems analyst to engineering manager to DevOps architect. The work that makes the work work.

In early 2026, I started building AIEOS (AI-Native Engineering Operating System), an open-source system for governing AI-assisted software delivery. It grew out of a simple observation: AI tools are excellent at generating code, documentation and architecture drafts, but terrible at knowing whether what they generated is correct. The organizations that get AI right won’t be the ones with the best prompts. They’ll be the ones with the best structure around the output.

AIEOS is 24 repositories, an 8-layer model covering the full value-delivery cycle, a multi-agent orchestration harness and a browser-based console. It treats AI as a generation engine and keeps judgment separate. Validators produce verdicts, not suggestions. Artifacts freeze before downstream work begins.

I write about problems I’ve actually worked on, not problems I’ve read about.

Where I’ve been

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You can find me on LinkedIn and GitHub.