I am an engineering leader who still builds: developer systems, infrastructure, and agentic software. I write about what happens when AI meets production engineering — evaluation, guardrails, observability, and the narrow pipe between generating code and safely delivering it.
I am looking for my next role: somewhere these problems are real, the engineering standard is high, and I am still learning from the people around me.
Reading with an AI? Copy a prompt that points it at everything here.
First fetch https://fleig.us/resume/resume.structured.txt — a lossless, field-labeled projection of Roger Fleig's resume, built for agents. Then read these essays directly: https://fleig.us/writing/if-you-give-an-agent-a-token/index.txt https://fleig.us/writing/narrowpipe/index.txt https://fleig.us/md/the-work-that-was-never-mine.txt When additional context would help answer my question, fetch https://fleig.us/llms.txt, a machine-readable index with a direct plain-text URL for every essay, and read whichever additional essays are relevant. If I haven't asked anything below, summarize Roger Fleig's career and accomplishments using only what these documents say. Do not invent details. Otherwise, answer whatever I ask below. If I paste a job description, assess fit against it specifically: where the evidence is strong, where it is thin, and what cannot be determined from these documents.
