Summary
Matthew Heidemann is a Senior Principal Product Manager specializing in AI agents for observability, with 12+ years of experience turning messy telemetry into actionable insights across enterprise stacks like Dynatrace, New Relic, and Splunk. He blends a deep engineering background with product leadership, having built core data platforms such as Lightstep’s UQL and MetricDB and open-sourced Cloud Foundry’s Metric Store. At ServiceNow he drives tool-calling strategy, MCP integrations, and rigorous agent eval/quality work to make agents reliable for NOC operators and business-impact analysis. He has repeatedly shipped 0→1 logging and observability products and improved developer workflows—for example cutting mean-time-to-first-trace from 10 minutes to 30 seconds via trace exploration improvements. Matthew focuses on the intersection of observability and AI infrastructure—agent traces, evals, tooling, and the production-grade data plane that enables them. Based in Denver, he pairs practical production experience with a curiosity for agent design and evaluation that few product leaders in this space possess.
12 years of coding experience
16 years of employment as a software developer
Bachelor of Science (B.S.) Computer and Information Systems, Bachelor of Science (B.S.) Computer and Information Systems at Arizona State University
Deep Learning NanoDegree Artificial Intelligence, Deep Learning NanoDegree Artificial Intelligence at Udacity
English