RUNTIME: A Computational Architecture for Governed, Stateful, and Reliable Multi-Agent Systems

As AI agents move from tools to autonomous participants in business processes, who's accountable when something goes wrong?Runtime proposes a computational architecture for governing AI agents that act with real autonomy - making decisions, holding state, and coordinating with other agents and humans over time. Rather than treating governance as a policy afterthought, the book builds it into the architecture itself: every agent operates under a defined authorization profile, traces back to a responsible human authority, and leaves an auditable record of what it did and why.Across eight chapters, the book develops a full computational model - Runtime Objects, governed execution and state evolution, multi-agent coordination, and observability and failure containment - before addressing how this architecture integrates into real enterprise systems, including vendor-provided AI layers. The result is a framework for building multi-agent systems that are not just capable, but reliable, auditable, and accountable by design.Written for architects, engineers, and technical leaders building or overseeing AI agent systems, Runtime argues that as agents take on more autonomous responsibility, governance can't be bolted on afterward - it has to be part of the runtime itself.