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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. Workflows flow diagram

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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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Deterministic Step Execution

Workflows execute as a controlled sequence of steps, where each step produces deterministic outputs that feed into the next step. This creates predictable data flows and consistent results, unlike free-form agent conversations. Step Types
  • Agents: Individual AI executors with specific capabilities and instructions
  • Teams: Coordinated groups of agents working together on complex problems
  • Functions: Custom Python functions for specialized processing logic
Deterministic Benefits 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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Guides

View Complete Example

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

Use in AgentOS

Run your workflows through the AgentOS chat interface
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