Workflows

Understanding workflow patterns for multi-agent systems

Pick a workflow pattern and connect agents so they share context across steps.

from praisonaiagents import Agent, AgentFlow

researcher = Agent(name="Researcher", instructions="Research topics.")
writer = Agent(name="Writer", instructions="Write clear summaries.")
flow = AgentFlow(steps=[researcher, writer])
flow.start("Explain workflow patterns in one paragraph.")

The user chooses a pattern, configures agents, and submits a task that flows through the team.

Quick Start

1. Simple Usage

   Chain two agents so the second builds on the first.

   from praisonaiagents import Agent, AgentFlow
   
   researcher = Agent(name="Researcher", instructions="Research topics.")
   writer = Agent(name="Writer", instructions="Write clear summaries.")
   flow = AgentFlow(steps=[researcher, writer])
   flow.start("Explain workflow patterns in one paragraph.")
   
2. With Configuration

   Run independent agents together with the top-level parallel primitive.

   from praisonaiagents import Agent, AgentFlow, parallel
   
   ai = Agent(name="AI", instructions="Research AI trends")
   ml = Agent(name="ML", instructions="Research ML trends")
   summary = Agent(name="Summary", instructions="Combine research")
   flow = AgentFlow(steps=[parallel([ai, ml]), summary])
   flow.start("Research latest developments")
   

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How It Works

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Workflows

Workflows define how multiple agents work together to complete a task. Just like a team of people in an office, agents can collaborate in different ways depending on the task.

What is a Workflow?

Think of a workflow as a recipe that tells your agents:

• Who does what
• In what order
• How they share information

The Four Main Patterns

🔀 Routing

“Send to the right expert”

Like a receptionist directing calls to the right department.

⚡ Parallel

“Everyone works at once”

Like a team researching different topics simultaneously.

➡️ Sequential

“One step at a time”

Like passing a document from person to person for review.

👔 Orchestrator

“Manager delegates work”

Like a project manager assigning tasks to team members.

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Which Pattern Should I Use?

I want to…	Use this pattern
Send requests to different specialists	Routing
Do multiple independent things at once	Parallel
Process step-by-step (A → B → C)	Sequential
Let an AI decide how to break down work	Orchestrator

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Real-World Examples

Example 1: Customer Support Bot

A customer asks: “Why is my order delayed?”

Pattern	How it works
Routing	Classify the question → Send to Shipping Agent
Sequential	Lookup Order → Check Status → Write Response

Example 2: Research Report

You ask: “Create a report on AI trends”

Pattern	How it works
Parallel	Research AI + Research ML + Research NLP (all at once)
Sequential	Research → Analyze → Write → Edit (step by step)
Orchestrator	Manager assigns: “You research, you analyze, you write”

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Two Ways to Build Workflows

PraisonAI offers two approaches:

Approach	Class	Best for
Deterministic Pipelines	AgentFlow	You define exactly what happens
Dynamic Delegation	AgentTeam + hierarchical	AI manager decides

Start simple: Use Sequential for your first workflow, then explore other patterns as needed.

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Best Practices

Match the pattern to the task shape

Independent subtasks fit parallel; ordered steps fit sequential; expert routing fits routing. Choosing the shape first keeps flows simple.

Use AgentFlow for deterministic pipelines

AgentFlow(steps=[...]) runs exactly the steps you list. Reach for AgentTeam + hierarchical only when you want an AI manager to decide.

Import primitives from the top level

from praisonaiagents import parallel (and when, loop) uses the friendly re-exports, so samples stay short and portable.

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Next Steps

Sequential Workflow

Start with the simplest pattern

Full Reference

Technical API documentation