When building a multi-agent system, you soon hit an architectural choice: should an agent execute one specific task, or own an entire domain? The difference appears small at first, but it shapes the behaviour of the entire system. Here are the two ends of that spectrum.

The one-step worker

The simplest kind of agent is a one-step worker: it performs an action, returns the result, and steps aside. It reads a record, executes a search, or computes a value. This worker holds no state over time. It requires no context about what preceded it or what follows. It takes an input, returns an output, and halts. This pattern is excellent for independent, stateless tasks.

The domain-owning specialist

Many tasks, however, are not a single action. They are a flow that unfolds across multiple interactions. Here, you need a different kind of agent: one that owns a domain, holds state across interactions, manages transitions, and decides for itself when the flow is complete. This agent is no longer a simple executor; it is a specialist.

Consider the human equivalent: a one-step worker is a lab technician you instruct to run a test and return a result. A specialist is the physician holding the patient’s file: they understand the history, decide the next clinical step, and take responsibility for the entire diagnostic path.

Where the difference shows in practice

The key difference lies in the ownership of state and logic. A one-step worker sees only its immediate task definition, requiring no context about the past or future. A specialist owns the complete lifecycle of a flow: it reads the prior state, determines the next step according to domain rules, updates the state, and knows exactly when its work concludes. No external planner dictates its steps; that routing knowledge lives inside the specialist.

This boundary yields a secondary benefit. Because the specialist is concerned exclusively with its own domain logic, it requires no knowledge of other agents, overall system routing, or global state. The system handles coordination and ordering; the specialist handles its own work. This separation makes the agent simpler and the overall system more stable.

When to use which

The choice between the two depends entirely on the nature of the task. If a task is independent and statelessβ€”one action, one resultβ€”the one-step worker is structurally superior. Adding state and a lifecycle here only introduces needless complexity. However, if a task unfolds across several interactions, where each decision depends on the previous outcome, a specialist must own that flow.

A common anti-pattern is building an entire multi-agent system from one-step workers, forcing the flow logic into the coordination layer where it does not belong. When a domain requires a multi-step flow, let a specialist own it. This architectural boundary is often the difference between a system that scales gracefully and one that becomes more fragile with every new capability.