ALAgent Lab

Mixed topology pattern

Hybrid Multi-Agent System

A parallel research phase feeds a sequential decision phase — parallel where it can, ordered where it must.

Best for research-then-decide workflows

How it works

The Hybrid Multi-Agent System pattern

Real workflows are rarely all parallel or all sequential. Here, independent research runs concurrently, then its combined output flows through an ordered chain of agents that each depend on the step before.

  1. 1

    Parallel research

    Market Research and Cost Research run at the same time.

  2. 2

    Strategy

    Reads both research outputs and sets direction.

  3. 3

    Financial

    Turns the strategy into numbers and a break-even.

  4. 4

    Aggregator

    Combines strategy and financials into the plan.

Why it matters

You get the speed of parallelism for the parts that are independent and the reliability of a pipeline for the parts that must happen in order. Most production agent systems end up looking like this.


Playground

Run the hybrid multi-agent system

Simulated
Try:

Your Goal

Input

The objective for the plan

Market Research

Agent

Sizes demand and the competitive gap

Cost Research

Agent

Estimates set-up and running costs

Strategy Agent

Agent

Sets direction from both research outputs

Financial Agent

Agent

Turns the strategy into numbers

Aggregator

Aggregator

Combines strategy and financials into the plan