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OpenAI is rolling out a new suite of APIs and tools designed to help developers and enterprises build AI-powered agents more efficiently atop some of the very same technology powering its own first-party AI agents Deep Research (which scours the internet independently to develop richly researched, well organized and cited reports) and Operator (its tool for controlling a web browser cursor autonomously based on a user’s text instructions and performing actions like finding sports tickets or making reservations).
Now, with access to the building blocks behind these powerful first-party OpenAI agents, developers can build their own third-party rivals or more domain-specialized products and services specific to their use case and audience.
OpenAI’s recent advancements in reasoning, multimodal processing, and safety mechanisms have laid the groundwork for these capabilities, especially its “o” family of reasoning models (o1 and o3).
“It’s hard to overstate how critical reasoning models are for enabling AI agents,” said Olivier Godement, head of product for OpenAI’s platform, in a video call with VentureBeat. “One of the biggest limitations before was handling long-horizon tasks like planning.”
But the company says developers haven’t yet had the tools necessary to easily built them into production-ready applications for enterprises and their customers — until now.
To address these hurdles, OpenAI is introducing several new offerings: the Responses API, built-in tools for web and file search, a computer use tool, and the open-source Agents SDK. While the Responses API lets developers build agents atop its tech, the Agents SDK can help them link agents to other web tools and processes, performing “workflows” that do what the user or business wants, autonomously.
These tools aim to streamline the development of AI agents by reducing the need for extensive prompt engineering and custom orchestration logic. They should also make it an attractive proposition to continue building atop OpenAI’s platform even in the face of rising competition from Chinese players like Manus, Alibaba’s Qwen, DeepSeek, and homegrown rivals such as Anthropic and Google.
While those other players do offer developer tools or products, the continual evolution of OpenAI’s developer platform makes it a hard proposition to beat as a “one stop shop” for those looking to leverage the latest AI advances in a clean, easy-to-use, fast and affordable way.
In a move certain to send the AI blogosphere and social media space aflutter, OpenAI is getting back into open source in a big way with the release of its Agents SDK, a toolkit designed to help developers manage, coordinate, and optimize agent workflows — even building agents powered by other, non-OpenAI models such as those by competitors Anthropic and Google, or open source models from DeepSeek, Qwen, Mistral, and Meta’s Llama family.
“The Agent SDK is open-source, allowing enterprises to mix and match different models,” Godement said. “We don’t want to force anyone to use only OpenAI models.”
The SDK offers key features such as:
• Configurable Agents – AI models with predefined instructions and tool access.
• Intelligent Handoffs – Mechanisms to transfer tasks between agents based on context.
• Built-in Guardrails – Safety measures for input validation and content moderation.
• Tracing and Observability – Tools for debugging and optimizing agent performance.
“With the Agents SDK, developers can track exactly what an agent is doing—what tasks it spawns, what data it gathers, and how it generates responses,” said Nikunj Handa, PM on OpenAI’s API team, in the same video call with VentureBeat.
What the new Responses API offers
At the center of this update is the Responses API, which combines features of OpenAI’s Chat Completions API with the tool-use functionality of the Assistants API, the latter of which will be deprecated in mid 2026, according to the company.
This integration allows developers to leverage multiple built-in tools within a single API call, making it easier to build applications that require complex, multi-step interactions.
The Responses API initially supports three built-in tools:
• Web Search – Provides real-time, cited answers by fetching information from the web.
• File Search – Retrieves relevant information from large document repositories using metadata filtering and optimized query processing.
• Computer Use Tool – Enables AI agents to perform actions on a computer, such as browsing, data entry, and navigating software interfaces.
“With the Responses API, developers get more visibility into what the model is doing—what tools it’s calling, why it’s calling them, and what decisions it’s making before and after those calls,” said Handa.
With these capabilities, OpenAI envisions the Responses API serving as a foundation for agentic applications, eliminating the need for multiple external integrations. The API is available to all developers starting today, with usage billed at OpenAI’s standard token and tool rates.
Additionally, OpenAI notes that while the Chat Completions API will continue to receive updates, the Responses API is considered its superset. Developers who need built-in tools or multi-step model interactions should use Responses API for new integrations.
OpenAI is also making its web search, file search, and computer use tools available directly through the Responses API. These tools enable AI agents to access real-world information, retrieve context from documents, and interact with digital environments more effectively.
Web Search offers developers realtime information with citations
The web search tool allows developers to integrate real-time search capabilities into their applications, making it useful for research assistants, shopping guides, and content aggregation tools. It provides sources for its responses, ensuring users can verify the accuracy of the information.
“The first thing we’re launching is built-in tools, like web search, which allows models to access real-time information,” said Handa. “It’s the same tool that powers ChatGPT’s Search, and now we’re bringing it to the API.”
OpenAI also confirmed that web search results in the API will include clear citations, allowing users to click through to original sources. Developers can implement web search as part of a broader retrieval system that includes proprietary data sources.
File search: intelligent document retrieval on private clouds
With the file search tool, AI agents can quickly retrieve relevant information from large document collections. This tool supports multiple file formats and includes features like query optimization, metadata filtering, and custom ranking for more precise results.
“The third tool we’re launching is file search, which makes it easy for developers to take all their data, store it in our system, and extract the right information with high accuracy,” Handa explained.
The file search tool is priced at $2.50 per thousand queries, with storage fees of $0.10 per GB per day (the first GB is free).
Developers may now also access Computer Use, the tech powering OpenAI’s Operator
The computer use tool extends agent capabilities beyond simple text-based tasks by allowing AI to interact with computer interfaces.
Powered by OpenAI’s computer-using-agent (CUA) model, this tool translates AI-generated actions into executable commands, enabling automation of tasks like data entry and web navigation.
“We’re also launching a computer-use tool, allowing models to interact with graphical user interfaces when there’s no existing API for a task,” Handa noted.
The computer use tool is currently available as a research preview for select developers in usage tiers 3-5. Pricing is set at $3 per million input tokens and $12 per million output tokens.
What it means for enterprise leaders
For IT team leaders, CTOs, and mid-level managers looking to optimize workflows, OpenAI’s new tools provide a clear path toward automating and scaling AI-driven processes without requiring extensive custom development.
The built-in web search and file search capabilities allow enterprises to quickly integrate AI-powered information retrieval into their existing systems, while the computer use tool enables automated interactions with legacy applications that lack API access.
The open-source Agents SDK further empowers organizations to coordinate AI-driven workflows across teams, making it easier to deploy agents that improve efficiency in areas such as customer support, document processing, and market research.
With enterprise security and observability built into these tools, decision-makers can adopt AI solutions with greater transparency and control, ensuring compliance and performance monitoring at scale.
What’s next?
OpenAI sees these new releases as the first step in building a comprehensive platform for AI agents. The company plans to roll out additional tools and integrations in the coming months to help developers deploy, evaluate, and scale agentic applications more effectively.
“We think the coming months are going to be critical for deploying more and more agents at scale,” said Godement. “We’ve already done this with first-party agents like Deep Research, but OpenAI isn’t going to build every agent—that’s why we have a developer platform.”
OpenAI also stated that it will continue improving safety features for agentic applications, including safeguards for prompt injections and unauthorized data access.
Developers interested in building with the new tools can explore OpenAI’s documentation and API playground to get started today.
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