Build an Enterprise Architecture AI Agent with Postman & OpenAI

Quick Overview

The video demonstrates how to build an Enterprise Architecture AI Agent using Postman and OpenAI's Agent Builder, configuring the workflow to first check input for sensitive information, then use the Postman MCP tool to retrieve all available API services, and finally use a custom guardrail to compare the proposed architecture against approved organizational best practices stored in a vector store to ensure compliance before outputting the final design.

Key Points: The AI Agent workflow begins with a 'check for sensitive info' guardrail to prevent leakage of secrets like API keys or passwords from the input prompt. The second step uses the 'postmangetAPIs' agent, which calls the Postman MCP tool 'getCollections' to retrieve all available API services within the agent's configured workspace. The agent is then instructed to loop through the collection IDs and use the 'postmangetCollection' tool to find endpoints matching the developer's input requirements. A 'Compare against approved architecture' agent uses a custom prompt check guardrail linked to an 'Approved Architectures' vector store containing best practices (like the 'reactbestpractices.md' file). The custom guardrail instructs the agent to act as a security infrastructure support person, looking for sensitive data, and to flag any proposed API usage that does not adhere to the approved architecture documents. The final agent step outputs the high-level architecture, confirming that all proposed components (React, S3 hosting, EC2/Servers, RDS/Databases) align with the organization's approved infrastructure standards. The entire process showcases using Postman tools within an OpenAI Agent workflow to automate enterprise architecture compliance checks against defined best practices.

Context: The video, presented by Quinton Wall (Head of Developer Relations at Postman), provides a tutorial on integrating Postman's capabilities with OpenAI's Agent Builder to create a custom AI agent. This agent is designed to act as an Enterprise Architecture reviewer, automatically validating developer-submitted application ideas against a set of predefined, organizationally-approved infrastructure and coding best practices stored securely in a vector database.