Decagon Product Foundations

Top takeaways from this module: 

• Entry conditions tell agent when to select an AOP
• Content blocks provide conditional logic for the agent to follow precisely
• References let the AI agent take action or pull from external information

Enabling an AI agent to take action, like processing refunds, updating account details, or troubleshooting issues, requires structured workflows. That’s where Agent Operating Procedures (AOPs) come in. They’re the playbooks that allow Decagon agents to resolve complex, multi-turn conversations reliably at scale.

An AOP is a step-by-step set of natural language instructions backed by code. This design combines human-like adaptability with the control needed for production systems. Decagon built AOPs on three principles: they’re fast to create and iterate on, flexible yet durable, and equipped with guardrails to keep sensitive operations safe.

Creating an AOP starts with a descriptive name and entry conditions, the triggers that tell the agent when to use that workflow. From there, Duet can generate a first draft from plain English or an existing standard operating procedure, saving time and letting teams iterate quickly. Each workflow is built from natural language, supported by content blocks for conditional logic. 

AOPs become even more powerful when extended with tools and metadata. Tools are custom logic like API calls, data lookups, or calculations that the AI agent can run in real time. Metadata provides extra context, such as location, role, or product tier, allowing workflows to adapt based on customer profile. Together, they connect the agent to live systems and personalize responses.

In summary, AOPs give CX teams both control and flexibility: structured enough to be reliable, but open enough for natural, conversational AI.