AI agents are AI systems that can work through tasks by selecting from connected tools—such as web search, file retrieval, application functions, or computer interfaces—and using the results to decide what to do next. The model can request an action, but the surrounding application runs the tool and controls what systems and permissions are available. An agent’s capabilities therefore depend on its configuration, not on an assumed ability to access everything.
What makes an AI system an agent?
There is no universal, standards-based definition of an AI agent established by the sources cited here. OpenAI describes agents as “systems that independently accomplish tasks on behalf of users,” a vendor’s working description rather than an industry-wide standard. In practical terms, an ordinary text assistant mainly generates a response; an agent can also use a configured tool, inspect what it returns, and continue through additional steps.
“Independently” does not mean unrestricted or guaranteed to succeed. Developers determine which tools the agent can use and the environment in which those tools run. OpenAI’s March 11, 2025 announcement gives its description of agents; its function-calling guide explains how an application connects model decisions to executable functions.
What can an agent do with connected tools?
OpenAI’s A practical guide to building agents puts it this way: “Broadly speaking, agents need three types of tools:” data tools, action tools, and orchestration tools. In a working system, these categories can support several kinds of tasks.
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Find and retrieve information
A configured agent may search the web, inspect uploaded files or PDFs, or query internal records such as a customer database. Retrieved information gives the model context for an answer or a later step. What it can find depends on which sources the application connects and what those sources permit it to read.
Use application functions and APIs
A developer can expose an application function as a structured tool. The model can request that function with arguments; the application’s code then runs it and returns the result. A function might retrieve information or make a change, depending on how the developer implemented it. The model’s request alone does not execute the function.
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Change records or send communications
Tools can be designed to update a record, send an email or text, or route a customer-service ticket to a person. These are possible integrations, not default abilities of every agent. The application’s tool configuration determines which actions are available.
Interact with a computer interface
Computer-use tools can let an agent navigate websites and interact with browser interfaces to gather information, test a site, or use an application through its user interface. This can be useful when an application lacks an API, but the agent’s reach is limited by the configured browser and runtime. OpenAI describes its implementation in the computer-use guide.
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Run code, edit files, and use connected services
Depending on the tools and execution environment, an agent may run code, edit files, connect to services through MCP, or produce files. These capabilities are implementation-specific; the OpenAI Agents API FAQ describes capabilities for that product.
Coordinate work with other agents
An agent can use a specialist agent as a tool, for example, coordinating research, writing, or support tasks. A workflow with several tools or agents is more complex than one tool call, but additional steps do not guarantee a better result.
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How does a connected-tool call work?
- The application sends the model a request. It includes the task context and the tools available to the model.
- The model may return a tool call. It selects a configured tool and supplies arguments when it decides a tool is needed.
- The application runs the tool. For example, it may call an API, query a database, or use a configured browser or sandbox.
- The application returns the result to the model. The model can use that output to answer or decide on another step.
- The cycle may continue. The model can request another tool call or provide a final response.
This division of responsibility matters: the model proposes a call, while the application executes it and supplies the result. OpenAI’s function-calling guide documents this pattern. Developers configure the model, instructions, tools, and execution environment; a workflow may connect APIs, an MCP server, a browser, or a sandbox.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What determines an agent’s capabilities and risks?
An agent can only attempt actions made available through its connected tools and execution environment. A retrieval-only setup has different consequences from one that can change records or send messages. Computer-use access is likewise bounded by the configured browser and runtime. Tool access should therefore match the job: a workflow that needs to read information does not automatically need permission to alter a system.
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Tool use can affect external software, including records, communications, and websites. OpenAI’s computer-use guide describes origin approval in a browser workflow, but that should not be taken to mean every agent action requires user approval. Approval behavior depends on the particular application and tool.
For the OpenAI Agents API beta covered by its Help Center FAQ, OpenAI stated that data residency was supported in the United States only and that Zero Data Retention was not supported, including when using a self-hosted sandbox. These are product-specific terms that can change; check the current FAQ for the exact product and region before deployment.
How to assess a specific agent
To understand what a particular agent can do, inspect its actual implementation rather than relying on the word “agent.” Check:
- Connected systems: Which applications, records, files, and services can it access?
- Tool effects: Can tools only retrieve information, or can they also change data and communicate?
- Interaction method: Does it use APIs or MCP connections, or operate through a user interface?
- Execution environment: Where does code or computer use run, and what is that environment permitted to reach?
- Data terms: What retention and residency terms apply to the exact vendor product, plan, and region?
There is no independent side-by-side reliability benchmark established here for ranking agent providers by success rate. Capability descriptions and data terms should not be mistaken for comparative performance results.
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