Michal Shatz has spent years shipping regulated, high-stakes software — applications that unlock cars and move live insurance payments — and the security and compliance work that comes with it. She is the author of the SOSA™ white paper, Supervised Orchestrated Secured Agents: A Methodology for Production-Grade Autonomous AI Operations (March 2026) — the governance methodology her company runs on, in which human-in-the-loop checkpoints are first-class primitives, every agent is isolated with scoped credentials inside zero-trust boundaries, and every action lands in an immutable audit trail. She has been building reasoning agents since 1999, when she modelled a lawyer's reasoning in a Hebrew Prolog-style language at a Weizmann Institute programme for Israel's Ministry of Education — more than two decades before the current wave.
Today she is the founder of OpsAgents AI, where she designs the agent architecture rather than prompting it. She is a certified Claude Developer and Claude Architect, and her team is going through the same certification on a training platform the company built for it. Her position: the question that decides an enterprise AI deployment is not "is it accurate" — it is "who is accountable when it acts."