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GuidesJanuary 30, 2026

How to Orchestrate 5 Agents on a Single Project

By Viktor Broegger

Running one AI agent on a project is straightforward. Running five simultaneously without them stepping on each other? That requires structure.

Here's how we've seen teams successfully coordinate multiple agents on large projects using AgentTask.

The coordination problem

Without coordination, multiple agents will:

  • Pick up the same task and do duplicate work
  • Make conflicting changes to the same files
  • Break dependencies by starting tasks before prerequisites are done
  • Flood the project with overlapping status updates

Task dependencies and the tasks_next MCP tool solve all of these problems.

Setting up dependencies

When you create tasks, define which tasks block others:

Task 1: Design database schema
Task 2: Build API endpoints (depends on Task 1)
Task 3: Write frontend components (depends on Task 2)
Task 4: Write tests (depends on Task 2)
Task 5: Deploy to staging (depends on Tasks 3 and 4)

Each agent calls tasks_next to get the highest-priority unblocked task. The system guarantees no two agents receive the same task.

The pattern: claim, work, complete

Every agent follows the same loop:

  1. Call tasks_next to get an available task
  2. Set status to in_progress to claim it
  3. Do the work (write code, run tests, deploy)
  4. Set status to done when finished
  5. Repeat from step 1

This is simple, but it works because the dependency graph ensures correct ordering and the status system prevents collisions.

Practical tips

Use sessions to group related work. If you have a "Backend API" session and a "Frontend UI" session, you can assign different agents to different sessions. Each agent only picks up tasks from its session.

Set the assigned_agent field when you want a specific agent to handle a task. The tasks_next endpoint respects agent assignments and won't hand an assigned task to a different agent.

Keep tasks small. A task that takes an agent 30 minutes is better than one that takes 3 hours. Smaller tasks mean faster feedback loops and fewer merge conflicts.

Use labels for coordination. Label tasks as backend, frontend, testing, or devops to make it clear which agent type should pick them up.

Real-world example

One of our design partners runs a build pipeline with 5 concurrent Claude Code agents on a single AgentTask project. Their setup:

  • Agent 1-2: Backend implementation (assigned to backend session)
  • Agent 3: Frontend implementation (assigned to frontend session)
  • Agent 4: Testing agent (picks up tasks labeled testing)
  • Agent 5: DevOps agent (handles deployment and infrastructure tasks)

They report 4x throughput compared to running a single agent sequentially, with zero task collisions since adopting the dependency-based coordination model.

The key insight: you don't need a complex orchestration layer. Clear task dependencies and a simple claim-work-complete loop give you reliable multi-agent coordination out of the box.

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