Graph-Based Orchestration

Modeling an agent workflow as a directed graph — nodes are steps (an LLM call, a tool call, a decision) and edges are the transitions between them — over an explicit shared state object that every node reads and writes. Execution is a walk through the graph with branches, loops, and conditional edges the developer specifies, rather than a sequence the model improvises. This is the model behind LangGraph and Google ADK's workflow agents, and it's what makes an agent's control flow deterministic, visualizable, and precisely interruptible — you can point at the exact edge where a Human-in-the-Loop (HITL) approval fires. The trade-off versus Role-Based Agents is up-front verbosity: you author the flow instead of describing agents and trusting a coordinator. Choose it when the workflow is complex, must be auditable, and 'the model decides the path' is a liability rather than a feature.