OpenAI Agent Builder: Create AI agents

Lisa Ernst · 10.10.2025 · Technology · 5 min

The OpenAI Agent Builder enables rapid development of reliable agents that go beyond pure chat functions and autonomously take on tasks. This visual interface, part of the AgentKit ecosystem, enables assembling, versioning, and embedding of agents into your own applications.

Quelle: Custom rendering

Introduction to OpenAI Agent Builder

Agents are systems that autonomously carry out tasks on behalf of users. This includes planning steps, using tools and handing over to humans when needed. The OpenAI Agent Builder is a visual workspace to create such agents. It enables drag-and-drop connections of models, tools (e.g., web search, file search, code), guardrails (safety rules) and decision logic. Together with the AgentKit-Ökosystem, , which includes the Agent Builder, the Connector Registry and ChatKit, allows an agent to be developed end-to-end from idea to embedding in your own app.

ChatKit is an UI toolkit to embed the finished agent as a chat experience in websites or apps. The platform offers integrated tools such as web search, file search, image generation, code interpreter and computer-use as well as connectors to common business systems.

How it works and current developments

OpenAI introduced in März 2025 erste Bausteine für Agenten and outlined its vision of "agents as systems that autonomously perform tasks". In the Oktober 2025 folgte AgentKit, , a comprehensive set consisting of the Agent Builder (visual workflows), the Connector Registry (central management of data and tool access) and ChatKit (embedding of chat UIs). In addition, evals for measurability and optimization are included. The Die Produktseite emphasizes that agents can be built either visually with the Agent Builder or code-centered with the Agents SDK, based on the Responses API. The page also describes customer experiences that demonstrate faster iterations and shorter UI implementation times, and lists the built-in tools.

The Agent Builder is a visual interface with versioning, preview runs and guardrails integration. The platform provides integrated tools such as web search, file search, image generation, code interpreter and computer-use. Embedding is done via ChatKit. A Ein Praxisleitfaden von OpenAI describes agents as systems that autonomously carry out tasks on behalf of users, and covers fundamentals, patterns and security aspects.

Strategic significance and benefits

The approach of the Agent Builder aims to solve the challenges in developing agents. Many teams get bogged down in orchestration, tool integration, evaluation, and UI construction. The Der Agent Builder integrates these components and makes them repeatable. Strategically, this reduces the hurdle between prototype and production. By visually designing workflows and direct measurement in evals, companies can learn faster and identify risks early. For companies, controlling data access and tool usage over the Für Unternehmen ist die Kontrolle von Datenzugriffen und Tool-Nutzung über die Registry und Guardrails is important to minimize operational risks in multi-agent scenarios. The technical backbone, consisting of Agents SDK, tools, File Search and Function Calling, also enables deeper integrations for complex use cases.

Quelle: accesspath.com

The OpenAI Agent Builder enables visual configuration of AI agent workflows.

Customer quotes on OpenAI's pages emphasize shortened iterations and faster deployment, illustrating product value. However, they should be understood as experiences of individual companies. Entwickler:innen begrüßen die visuelle Transparenz, stellen aber Fragen zur Handhabung von Secrets und Environment-Variablen sowie zu Governance-Details, was die Relevanz von Betriebsfragen unterstreicht (Community-Diskussion, Community-Diskussion).

It should be noted that the Agent Builder is not just another chat UI. Er orchestriert Workflows und Tools, während ChatKit which is responsible for UI embedding.

Practical application and best practices

For the development of an agent that not only answers but acts, the following roadmap is recommended:

1. Clarify use case: Define which steps the agent autonomously completes and where tools or approvals are needed. The Der Praxisleitfaden offers criteria and patterns.
2. Start in the Agent Builder: Create an empty workflow or a template, define goals, inputs and expected outputs in the Agent Builder.
3. Connect tools: Enable Web search, File search, Code, Computer-use or own functions. Check permissions and connectors ( OpenAI Agent Platform, File Search, Function Calling).
4. Set guardrails: Define what is allowed (e.g., PII filtering, jailbreak protection), and document exceptions ( Agent Builder Safety).
5. Evaluate: Set up datasets and trace grading, evaluate answers, tool calls and side effects. Iterate systematically ( Trace Grading).
6. Embed: Integrate with ChatKit a chat UI into your app, link the workflow ID and attach telemetry.
7. Production: Follow best practices for scaling, cost control, monitoring and security ( Production Best Practices).

Quelle: newspiner.com

A roadmap illustrates the steps from ideation to optimization in AI Agent Building.

Open questions concern the most reliable models and tool combinations as well as their costs in specific domains that require own evals ( Trace Grading). Governance, secrets and compliance across teams and workspaces must be clarified, with the Connector Registry and documented processes help, but details are organization-specific. It also must be defined what limits the agent in live operation (e.g., approval steps). OpenAIs Sicherheitsleitfaden sketches risk types and countermeasures, but concrete policies must be defined by you.

The OpenAI Agent Builder bundles the essentials: visually design workflows, connect tools securely, measure and improve behavior – and bring the result directly into products ( OpenAI Agent Platform). What remains essential is diligence: a clear use case, clean guardrails and realistic evals are essential. Thus a graph becomes a reliable agent that takes over work, rather than creating new problems ( Praxisleitfaden, Production Best Practices).