> ## Documentation Index
> Fetch the complete documentation index at: https://docs.praison.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Sequential Workflow

> Chain agents one after another like an assembly line

# Sequential Workflow

Pass work from one agent to the next, like an **assembly line**.

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph LR
    Input([📝 Request]) --> A1[🔍 Researcher]
    A1 --> A2[📊 Analyst]
    A2 --> A3[✍️ Writer]
    A3 --> A4[📋 Editor]
    A4 --> Output([✅ Result])
    
    classDef io fill:#8B0000,stroke:#7C90A0,color:#fff
    classDef agent fill:#189AB4,stroke:#7C90A0,color:#fff
    
    class Input,Output io
    class A1,A2,A3,A4 agent
```

***

## How Context Flows

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
sequenceDiagram
    participant You
    participant Researcher
    participant Analyst
    participant Writer

    You->>Researcher: "Write about AI trends"
    Researcher->>Analyst: Research findings
    Analyst->>Writer: Key insights
    Writer->>You: Final article
```

Each agent receives the **previous output** automatically.

***

## When to Use

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph LR
    subgraph "✅ Use Sequential"
        A[Step depends on previous]
        B[Order matters]
        C[Quality review chain]
    end
    
    subgraph "❌ Use Parallel"
        D[Independent tasks]
        E[Speed critical]
    end
    
    classDef good fill:#10B981,stroke:#7C90A0,color:#fff
    classDef bad fill:#EF4444,stroke:#7C90A0,color:#fff
    
    class A,B,C good
    class D,E bad
```

***

## Code

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents import Agent, AgentFlow

researcher = Agent(name="Researcher", instructions="Research topics")
analyst = Agent(name="Analyst", instructions="Analyze research findings")
writer = Agent(name="Writer", instructions="Write based on analysis")

# Sequential: researcher → analyst → writer
flow = AgentFlow(steps=[researcher, analyst, writer])
result = flow.start("AI trends in 2024")
```

***

## Example: Blog Post Pipeline

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph LR
    Topic([📝 Topic]) --> R[🔍 Research]
    R --> A[📊 Analyze]
    A --> W[✍️ Write]
    W --> E[📋 Edit]
    E --> Post([✅ Published])
    
    classDef io fill:#8B0000,stroke:#7C90A0,color:#fff
    classDef step fill:#189AB4,stroke:#7C90A0,color:#fff
    
    class Topic,Post io
    class R,A,W,E step
```

| Step | Agent      | Receives | Outputs       |
| ---- | ---------- | -------- | ------------- |
| 1    | Researcher | Topic    | Facts, data   |
| 2    | Analyst    | Facts    | Key insights  |
| 3    | Writer     | Insights | Draft article |
| 4    | Editor     | Draft    | Polished post |

***

## With Callbacks

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents import AgentFlow, WorkflowHooksConfig

flow = AgentFlow(
    steps=[researcher, analyst, writer],
    hooks=WorkflowHooksConfig(
        on_step_complete=lambda name, r: print(f"✅ {name} done")
    )
)
```

***

## Related

<CardGroup cols={2}>
  <Card title="Parallel" icon="arrows-split-up-and-left" href="/docs/guides/workflows/parallel">
    All at once (faster)
  </Card>

  <Card title="Routing" icon="route" href="/docs/guides/workflows/routing">
    Send to specialists
  </Card>
</CardGroup>