Building sophisticated, intelligent systems requires clear understanding of how the components interact. Welcome to the Canonical Reference for Agentic Flows (reference.do), the essential guide for navigating the .do platform and unlocking the full potential of Agentic Workflows and Services-as-Software.
This isn't just another dry documentation portal; reference.do is your comprehensive technical companion, designed to provide the foundational knowledge you need to build, understand, and leverage the power of agentic intelligence on the .do platform.
Think of reference.do as the definitive blueprint for the .do ecosystem. Here's a glimpse into the critical information you'll have at your fingertips:
The heart of any integration lies in understanding the API. Our reference provides exhaustive documentation for every API endpoint on the .do platform. You'll find:
Whether you're building a custom integration or extending existing functionality, the API documentation is your first stop.
Understanding the data structures is crucial for working effectively with any platform. The reference.do provides deep dives into the underlying data models used by .do, including:
By understanding these models, you can build robust and efficient applications that seamlessly integrate with the .do platform.
Learning by doing is highly effective. The reference.do is packed with practical code examples across various programming languages. These examples illustrate:
These examples serve as valuable starting points and inspiration for your own implementations.
In the rapidly evolving world of agentic systems, having a single, authoritative source of truth is paramount. reference.do is designed to be that source. It represents the most accurate and up-to-date technical documentation for the .do platform, ensuring you're always working with the latest specifications and best practices.
If you're new to these concepts, here's a quick overview:
The .do platform provides the infrastructure to build and manage these powerful constructs, and reference.do is your guide to harnessing their capabilities.
To illustrate the clarity of the documentation, here's a snippet demonstrating the data model for agent workflow output:
interface AgentStepOutput {
status: 'success' | 'failure';
output: any; // The output of the agent step can be anything
agentId: string; // The ID of the agent that executed this step
}
interface AgentWorkflowOutput {
status: 'completed' | 'failed';
steps: AgentStepOutput[];
finalOutput: any; // The final output of the entire workflow
}
This simple, yet clear, interface definition helps you understand the structure of the data you'll receive when a workflow completes.
To help you get started, we've compiled answers to some common questions:
Q: What is the purpose of the reference documentation?
A: The reference provides canonical documentation for all aspects of the .do platform, including API specifications, data models, and best practices for building Agentic Workflows and Services-as-Software.
Q: What kind of information is included in the API documentation?
A: You can find detailed information on API endpoints, request/response formats, data schemas, and code examples for interacting with the .do platform.
Q: Does the reference cover data models used on the platform?
A: Yes, the reference includes documentation on the underlying data models used within the .do platform, such as the structure of Agents, Workflows, and Services.
Q: Are there examples of building Agentic Workflows and Services-as-Software?
A: You can find guides and examples demonstrating how to implement common Agentic Workflows and build Services-as-Software using the provided APIs and SDKs.
Whether you're a developer building the next generation of agentic applications or a business analyst seeking to understand the capabilities of the .do platform, the Canonical Reference for Agentic Flows (reference.do) is an invaluable resource. Dive in, explore the documentation, and start building something amazing.
Visit reference.do today and unlock the power of agentic intelligence!