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Agno Workflows enable you to build deterministic, controlled agentic flows by orchestrating agents, teams, and functions through a series of defined steps. Unlike free-form agent interactions, workflows provide structured automation with predictable execution patterns, making them ideal for production systems that require reliable, repeatable processes. Each step in a workflow handles a specific part of a larger task, with output automatically flowing from one step to the next, creating a smooth pipeline from start to finish. Think of it like an assembly line: each step specializes in one thing, and together they accomplish complex tasks that would be hard for a single agent or team to handle. Workflows flow diagram

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Your First Workflow

Here’s a simple workflow that takes a topic, researches it, and writes an article: 
from agno.agent import Agent
from agno.workflow import Workflow
from agno.tools.duckduckgo import DuckDuckGoTools

# Define agents with specific roles
researcher = Agent(
    name="Researcher",
    instructions="Find relevant information about the topic",
    tools=[DuckDuckGoTools()]
)

writer = Agent(
    name="Writer",
    instructions="Write a clear, engaging article based on the research"
)

# Chain them together in a workflow
content_workflow = Workflow(
    name="Content Creation",
    steps=[researcher, writer]
)

# Run the workflow
content_workflow.print_response("Write an article about climate change solutions", stream=True)
That’s it! The workflow automatically:
  1. Passes your input to the researcher
  2. Takes the research results and feeds them to the writer
  3. Returns the final article

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Why should you use Workflows?

Workflows provide deterministic control over your agentic systems, enabling you to build reliable automation that executes consistently every time. They’re essential when you need: Deterministic Execution
  • Predictable step-by-step processing with defined inputs and outputs
  • Consistent results across multiple runs
  • Clear audit trails for production systems
Complex Orchestration
  • Multi-agent coordination with controlled handoffs
  • Parallel processing and conditional branching
  • Loop structures for iterative tasks
Workflows excel at deterministic agent automation, while Teams are designed for dynamic agentic coordination. Use workflows when you need predictable, repeatable processes; use teams when you need flexible, collaborative problem-solving.

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What Can Be a Step?

Each step in your workflow can be:
  • An Agent - Individual AI executors with specific capabilities and instructions
  • A Team - Coordinated groups of agents working together on complex problems
  • A Function - Custom Python functions for specialized processing logic
Your agents and teams retain their individual characteristics and capabilities, but now operate within a structured framework that ensures:
  • Predictable execution: Steps run in defined order with controlled inputs/outputs
  • Repeatable results: Same inputs produce consistent outputs across runs
  • Clear data flow: Output from each step explicitly becomes input for the next
  • Controlled state: Session management and state persistence between steps
  • Reliable error handling: Built-in retry mechanisms and error recovery

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Controlling Workflows

Once comfortable with basic workflows, you can add:
  • Conditional Logic - Different paths based on results
  • Parallel Execution - Run multiple steps at the same time
  • Loops - Repeat steps until a condition is met
  • Conversational Workflows - When users interact directly with your workflow (rather than calling it programmatically), you can make it conversational by adding a WorkflowAgent. This enables natural chat-like interactions where the workflow intelligently decides whether to answer from previous results or execute new workflow runs. Learn more in the Conversational Workflows guide.

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Guides

View Complete Example

See the full example with agents, teams, and functions working together

Conversational Workflows

Enable chat-like interactions with your workflows for direct user engagement

Use in AgentOS

Run your workflows through the AgentOS chat interface