Workflow-Based Orchestration Layer for Long-Running AI Agent Sessions

To support complex autonomous tasks like model optimization and software engineering, we redesigned our AI infrastructure by shifting from stateless, request-response paradigms toward a model of managed, long-running execution. Structurally, this involved moving away from ad-hoc scripts toward a unified agentic harness where every session is treated as a durable, managed workflow. We implemented a decoupled sidecar architecture that effectively insulates core infrastructure from the unpredictable execution paths of autonomous agents, ensuring that identity, security, and network egress are managed through a hardened proxy rather than the agent itself

Attendees will walk away knowing how to architect a secure execution harness for autonomous agents, implement asynchronous human intervention models, and manage the lifecycle of persistent agentic sessions in high-scale production environments.