Multi-Agent Collaboration

Agent Delegation

One agent plans, others execute. The Orchestrator breaks complex tasks into subtasks and delegates them to specialized agents — automatically.

Live Demo

Watch agents collaborate

The Orchestrator delegates tasks to specialized agents in sequence, collecting results and producing a final output.

Agent Delegation
U
Write a research report on AI agents
O
Orchestrator
Waiting...
R
Researcher
Standby
W
Writer
Standby
R
Reviewer
Standby

How It Works

Plan, delegate, collect

Step 1

Create a Plan

The Orchestrator analyzes the user's request and creates a task plan with dependencies between subtasks.

O
Step 2

Delegate Tasks

Each subtask is assigned to the best agent for the job. Agents work in parallel when tasks are independent.

Step 3

Collect Results

The Orchestrator collects all results, synthesizes them into a final response, and returns it to the user.

Benefits

Why delegation matters

Specialization

Each agent focuses on what it does best. A researcher researches, a writer writes — no jack-of-all-trades.

Parallel Execution

Independent tasks run simultaneously. The task planner builds a dependency graph and parallelizes wherever possible.

Error Recovery

If an agent fails, the 3-level error system kicks in — retry, self-fix, or escalate to a discussion room.

Dynamic Planning

The Orchestrator adapts the plan based on results. If a subtask reveals new requirements, it adjusts on the fly.

Architecture

Delegation flow

The Orchestrator coordinates everything. Agents communicate through a message bus, and tasks flow through a dependency graph.

User RequestOrchestratorResearcherWriterReviewerResults collected and synthesized into final response

Let agents work together

Build multi-agent systems where each agent does what it does best.