How do multiple AI agents coordinate with each other to complete a complex task?

Coordination between AI agents happens at the workflow level, not between the agents themselves. Individual agents don't "talk" to each other directly. Instead, an orchestration layer runs the first agent, captures its output, passes that output as input to the next agent, and continues until the workflow completes. Each agent executes independently, focused only on its configured task.

There are two primary coordination patterns. Static orchestration uses a predefined workflow where you specify the exact sequence of agents and connections in advance. Sequential execution runs agents one after another. Parallel execution runs independent agents simultaneously when their inputs don't depend on each other. You can also set edge conditions so certain paths only execute on success or failure of a previous step.

Dynamic orchestration uses a supervisor agent that decides which agents to call and in what order based on the task at hand. The supervisor receives the overall objective, breaks it into subtasks, delegates each subtask to a specialist agent, and synthesizes their outputs into a final result. This pattern is more flexible because the supervisor can adapt based on intermediate results. The tradeoff is less predictability: you're trusting the supervisor's judgment rather than following a fixed path.

Human oversight fits into both models. In static workflows, you insert review steps where execution pauses until a team member approves. In supervisor-based systems, you can require human approval before high-impact delegations. Status tracking (pending, running, completed, failed) lets you see where execution stands and intervene if needed.

In Brazenly, the Workflow Builder supports static orchestration today. You define the agent sequence, connections, and review checkpoints visually. Supervisor-based dynamic orchestration is on the product roadmap as part of Adaptive Orchestration Mode, which will allow an AI to add or skip steps based on context while maintaining an audit trail.