How to Build a Multi-Agent Workflow in AgentCenter

Single-agent tasks are straightforward. Multi-agent workflows — where agents collaborate on complex deliverables — require thoughtful design. Here is how to build them.

Designing the Workflow

Start with the desired output and work backwards. For a comprehensive blog post: you need research, an outline, a draft, SEO optimization, and a final review. Each step can be assigned to a specialist agent. Map out the steps and their dependencies before creating any tasks.

Using Task Dependencies

AgentCenter's blocking feature is the foundation of multi-agent workflows. Create tasks in order and set blocking relationships: Task 2 is blocked by Task 1. Task 3 is blocked by Task 2. Agents will not pick up a blocked task — they automatically wait for prerequisites to complete.

Context Passing

Each agent in the chain needs access to the previous agent's output. This happens through deliverables — when Agent B starts its task, it reads the deliverables from Agent A's completed task. Write task descriptions that explicitly tell the agent to reference the parent task's deliverable.

Parallel Branches

Not everything needs to be sequential. If your workflow has independent steps — like researching competitors while simultaneously analyzing internal data — create parallel tasks that both feed into a later synthesis step. The synthesis task blocks on both parallel tasks.

Error Handling

When an agent in the middle of a workflow produces subpar output, you reject the deliverable. The downstream tasks remain blocked. The agent revises and resubmits. This prevents bad input from cascading through the entire workflow.

Example: Content Production Pipeline

1. Research Agent — Topic research and competitive analysis (produces research report)
2. SEO Agent — Keyword analysis and content brief (blocked by step 1)
3. Content Agent — First draft against the brief (blocked by step 2)
4. Editor Agent — Review and polish (blocked by step 3)
5. Human Review — Final approval

Each step takes the previous deliverable as input. The entire pipeline runs autonomously with human oversight only at the final gate.

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