Uber’s AI/ML Platform Team is relying on Cadence as part of their new Agent Executor Service, facilitating durable agentic workflow orchestration at scale.
Large Language Models (LLMs) have evolved from simple text prediction to autonomous agents capable of orchestrating complex tools. However, a critical gap exists in the current ecosystem: durable orchestration. Most agent SDKs are stateless by design, making them fragile in production environments where network partitions, long-running tasks, and system failures are inevitable.

In this session, we explore a cloud-native architectural pattern to solve the “stateless agent” problem by using Cadence as a robust durability layer for agent orchestration. We will move beyond the “hello world” agent and demonstrate how to build production-ready systems that require:

- Fault tolerance: Resuming complex reasoning chains after a process crash.
- Auditability: Maintaining a permanent, replayable record of agent decisions and tool executions.
- Long-running state: Managing agents that operate over days or weeks rather than seconds.

We will provide a technical deep dive into integrating Cadence with popular frameworks like OpenAI, Google ADK, and Claude. We will also show how Cadence fits into the broader AI ecosystem, including Cadence AI Skills and AI-native coding tools like Claude Code, Cursor, Codex, and Hermes Agent, so developers can write their first Cadence-aware agent workflow in minutes.

Attendees will walk away with a blueprint for durable agent orchestration: implementing automatic checkpointing and retries, recovering from failures instead of restarting, and ensuring their AI agents are as reliable as their microservices.