Introduction to Graflow: The Orchestration Engine for Production-Grade Agentic Workflows

As AI systems evolve from single models to always-running fleets of agents, orchestration—not model quality—becomes the primary bottleneck.
Many existing frameworks tightly couple workflow control flow with agent internals, resulting in complex, fragile graphs that are difficult to debug and operate in production.
Graflow addresses this by adopting a “Fat Node” architecture, where each node is a self-contained agent, cleanly separating orchestration from reasoning logic.
Designed for real-world systems, Graflow combines a Pythonic DSL with a state-machine runtime, supports Redis-backed distributed execution, and provides checkpoints, HITL, and type-safe state sharing.
Planned for an Apache 2.0 release in January 2026, Graflow targets engineers building scalable, observable, production-ready agentic systems.

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Transcript

5. The fundamental issue is a design flaw: frameworks that represent an agent's internal reasoning loop as part of the external workflow inevitably lead to complexity and internal bloat.