Orchestrating Agents at Scale

Quick Overview

OpenAI introduced AgentKit at DevDay 2025, a complete set of building blocks designed to help developers rapidly build, deploy, and optimize AI agent workflows, as demonstrated by James Hills and Rohan with a complex

Key Points: AgentKit was introduced at OpenAI DevDay 2025, providing building blocks for creating, deploying, and optimizing AI agent workflows. James Hills demonstrated AgentKit's Agent Builder, a visual flow editor allowing users to connect nodes like 'File Search' and 'MCP Tool' without writing extensive code. A live demonstration involved creating an agent workflow to resolve a 'low fuel economy' issue for a truck maintenance company called 'Truck Brothers', which required accessing maintenance manuals and parts lists. Rohan showed how the system handles complex logic, including external tool calls like a GraphQL query via the 'MCP Tool' node, and integrates guardrails for safety and correctness checks (e.g., Hallucination detection). The optimization feature allows users to iterate quickly on agent performance, demonstrated by improving the 'Correctness' score in the Synthesis Agent grader from 40% to 80% by updating the prompt. AgentKit supports self-hosting models via the ChatKit protocol, allowing users to run agents on their own infrastructure rather than solely on OpenAI's cloud. The session concluded by showcasing the ease of exporting the entire workflow as code (TypeScript or Python) using the OpenAI Agents SDK.

![Screenshot at 00:05: The title slide for the session, displaying "OpenAI DevDay \[2025\]" followed by the presentation title "Orchestrating Agents at Scale", sets the context for the announcement of new agent development tools.](https://ss.rapidrecap.app/screens/KplSDxYv9xU/00-00-05.png)

Context: The presentation, delivered by James Hills and Rohan from OpenAI's Forward Deployed Engineering team during OpenAI DevDay 2025, focused on the launch of AgentKit. AgentKit is presented as a solution to simplify the engineering process of creating production-ready, reliable AI agents that can perform multi-step reasoning and interact with external tools and data sources.