As the tasks given to an AI system grow more involved, a single generalist agent can become less effective than several specialised agents working together, each concentrating on one part of the overall problem.
Specialisation applied to agents
One agent specialised in reading attached documents, another in working out a quote, another in communicating with the customer: each optimised for its own task, together they often produce more reliable results than one agent trying to handle everything on a single generic configuration.
How the coordination works
An "orchestrator" agent can take the initial request, break it into sub-tasks, and delegate each to whichever specialist suits it, then gather the partial results into a coherent answer. This architecture calls for careful design of how intermediate results pass from one agent to the next.
The trade-off to weigh
Several coordinated agents increase the system's complexity and the number of places where communication between them can go wrong. For simple tasks a single well-designed agent often remains the more reliable choice; multi-agent orchestration pays when the complexity genuinely justifies the split.