Openai recently released a set of new developer tools aimed at making it easy to create AI agents that can autonomously perform complex tasks. The update, announced last week, introduces the Responses API for web search, file search, computer control, the open source agent SDK and built-in tools designed to streamline the way AI systems interact with real information and applications.
Openai describes these agents as “a system that accomplishes tasks independently on behalf of users.” This means that you can perform multi-step processes with minimal human guidance, such as topic research and database updates. The company’s goal is to lower the barriers to deploying powerful AI-driven assistants and expand accessibility to advanced AI capabilities.
Response API: Simplify agent interactions
At the heart of Openai’s announcement is the new Responses API, which acts as a unified interface for building AI agents. This API combines the conversation capabilities of Openai’s chat completion API with the tooling capabilities of the previous Assistant API. In reality, this allows a single API call to handle complex, multi-step tasks that can involve calls to various tools and knowledge sources.
Openai says the Response API was built to simplify agent development by reducing the need for custom code and reducing the need for quick tweaks. “The answer API is designed for developers who want to easily combine OpenAI models and built-in tools into their apps without the complexity of integrating multiple APIs or external vendors.” The company explained in a blog post about the announcement. Previously, developers often had to coordinate multiple API calls and create elaborate prompts to make AI agents do something useful. With the new API, for example, agents will have conversations with users, keep lookup information via web search, and write summary all within one workflow.
In particular, the Responses API is available to all developers at no additional cost beyond the standard usage fee. It is also backwards compatible. Openai has confirmed that it will continue to support the popular chat completion API for simple use cases, but the older assistant API will be phased out in mid-2026 as its functionality is folded into the answer API.
Open Source Agent SDK streamlines workflow orchestration
The launch also includes the Agents SDK, a toolkit for managing the workflows of one or more interacting AI agents. In a notable move, Openai has made the SDK open source, allowing developers and businesses to inspect their code and even integrate non-Openai models into agent systems. This flexibility means that businesses can use Openai’s GPT-4 to coordinate agents that can be used with another agent, all within the same framework, with different AI models.
The Agent SDK focuses on orchestrating workflows. Essentially, it tracks what the agent is doing and how it hands over the task. It provides built-in mechanisms for:
- Configurable agents: Configures an AI agent with predefined roles or instructions for a particular task.
- Intelligent Handoff: Passing tasks between multiple agents or processes based on context (for example, one agent collects data and then analyzes another).
- Guardrails for safety: To prevent unnecessary output, use input validation and content moderation tools to ensure that the agent stays within a specific boundary.
- Traces and Observability: Tools that monitor and debug agent actions step by step help developers understand decision-making and improve performance.
According to Openai, the toolkit can simplify complex use cases such as customer support bots, multi-step research assistants, content generation workflows, code review agents, and sales research automation. By open-sourcing SDKs, Openai encourages community contribution and recruitment in enterprise settings where transparency and the capabilities of self-hosted components are often important. Early adopters, including companies like Coinbase and Box, have already experimented with Agent SDKs to build AI-powered research and data extraction tools.
Built-in tools enhance AI capabilities
To make the AI agent work immediately, OpenAI’s Response API comes with three built-in tools that connect AI to external data and actions. These tools not only expand what agents can do and generate text.
The built-in tools available at startup are:
- Web search: AI agents can perform real-time web searches and get the latest information with the cited sources. This means that agents can answer questions using the latest news and facts from the internet and provide a reference to transparency. This tool can help you build agents such as research assistants, shopping guides, and travel planners who need live information.
- File search: Agents quickly sift through large collections of documents or data provided by developers to find relevant information. This is essentially a private knowledge base query tool. Agents can be used to answer customer support questions by searching policy documents, or retrieve text from a library of files to assist in legal investigations. This tool can be deployed in scenarios such as customer service bots and internal company assistants who need to reference proprietary information.
- Computer Usage: A new feature that allows AI agents to perform actions on computers as if they were human users operating the machine (currently in research preview). Featuring Openai’s Computer Usage Agent (CUA) model, the tool transforms AI intent into keyboard and mouse actions to navigate software, websites, or other digital interfaces. Essentially, it allows for automation of tasks that do not have a simple API. For example, you can enter data into a legacy system, click on a web app for testing, or check the information in the graphical interface.
By incorporating these tools, AI agents can not only consider the problem but also consider the action. This means searching for information, retrieving specific data, or manipulating a digital environment. This greatly expands the functionality of the agent, making it even more convenient for real applications.
Openai expects developers to combine these tools as needed. For example, an agent uses web search to collect public information and file searches to extract internal data, and then use that combined knowledge to draft reports or perform tasks. All of these can be tailored through the answers API in a unified way, rather than requiring separate services or manual integration.
A broader impact on AI adoption and accessibility
Analysts say the launch will help accelerate the adoption of AI agents across the industry by lowering the technical hurdle. For businesses, the appeal of these new tools is the ability to automate and extend processes without extensive custom development.
Routine tasks such as information search, form processing, or cross-app data entry (which could have required critical coding or multiple software systems) can now be handled by AI agents using OpenAI building blocks. For example, built-in search tools allow businesses to connect AI to knowledge databases or to the web almost instantly, while computer usage tools provide a way to interface with legacy applications that do not have APIs. Meanwhile, the open source nature of agent SDKs allows businesses to have more control, integrate these AI agents into their existing infrastructure, and even use different AI models when needed.
Openai’s move is part of a wide range of races with developers building agents. Competing tech companies and startups have deployed their own AI agent platforms, and Openai’s comprehensive toolkit may help it stand out. In fact, timing comes amid a surge in interest in autonomous AI agents around the world. For example, Chinese startup Monica recently attracted attention with its Agent Manus, claiming it is superior to Openai’s own prototype agent in certain tasks. By providing an important part of the platform’s open sourcing and built-in tools, Openai appears to be responding to competitive pressures while also promoting wider adoption of AI.
From an accessibility perspective, these tools can democratize those who can build sophisticated AI systems. Even small businesses and individual developers can make it feasible to create AI-driven assistants or workflows without the need for a large research team. The integrated approach (where a single API call can handle multiple steps) and availability of Openai’s example documentation reduces the entry barrier for newcomers. Openai also provides an observability interface for developers to track and inspect what agents are doing. This is important for debugging and building trust in AI output. This focus on usability and safety (guardrails and surveillance) is expected to encourage more companies to experiment with AI agents, knowing there is surveillance and management.
AI agents can be as common and essential as the Internet’s existence. Openai’s latest tools help turn that vision into reality by making agent development more accessible and allowing the wider community of developers and organizations to build their own agents.
