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Agent Operating Procedures (AOPs) are pre-configured AI workflows that automate complex tasks through intelligent, repeatable processes. Think of AOPs as your AI-powered standard operating procedures that can perform research, analysis, content generation, and decision-making tasks with minimal human intervention.
AOPs can be executed via the Python SDK for seamless integration into your existing workflows!
  • Overview
  • Working with AOPs
  • Use Cases
  • Developer Resources

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What are AOPs?

AOPs represent a revolutionary approach to workflow automation, combining the flexibility of AI with the reliability of structured processes. Each AOP contains:
  • Intelligent Prompts: Carefully crafted instructions that guide AI behavior
  • Dynamic Parameters: Configurable inputs that adapt the AOP to different scenarios
  • Tool Integration: Access to Athena’s comprehensive toolkit for various tasks
  • Execution Modes: Multiple ways to run AOPs based on your needs

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Key Features

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Dynamic Parameter System

AOPs use a powerful parameter system that makes them highly adaptable:

Text Inputs

Simple text parameters for names, descriptions, and custom instructions
Example: [[company_name|type=text]]

Asset Selection

Select specific assets like documents, databases, or presentations
Example: [[documents|type=assetSelector|filterType=document]]

Option Selection

Choose from predefined options for consistent results
Example: [[priority|type=textOptions|options=High,Medium,Low]]

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Multiple Execution Modes

AOPs offer flexibility in how they’re executed:
  • API Mode: Direct execution with immediate results
  • Async API Mode: Background processing for long-running tasks
  • Chat Integration: Interactive execution with conversational feedback
  • SDK Integration: Programmatic execution via Python SDK
AOPs represent the future of intelligent automation, combining the power of AI with the reliability of structured processes to transform how you approach complex tasks and workflows.