# What are AI agents? How AI that plans, uses tools and acts works, explained

> A chatbot answers your question; an agent takes your goal, plans the steps, uses apps and the web, and asks before it pays or sends. Here is how they work, with real examples.

- Publisher: NextDiff (https://nextdiff.com/)
- Section: AI
- Author: NextDiff Editorial
- Published: 2026-10-22T05:08:45.245Z
- Updated: 2026-10-22T12:49:22.452Z
- Canonical URL: https://nextdiff.com/posts/what-are-ai-agents/
- Topics: agents, llms, gemini, openai, chatgpt, google

## In short

AI agents are AI systems that take a goal and work toward it on their own: a language model plans the steps, uses tools such as a browser, email or code, checks the results and repeats until the task is done. Examples include Google's Gemini Agent, OpenAI's ChatGPT agent and Anthropic's Claude computer use.

## Key takeaways

- An AI agent is a language model in a loop: plan, act with a tool, observe the result, check, repeat until the goal is met.
- Unlike a chatbot, which gives one answer, an agent does the multi-step task itself, such as sorting an inbox or booking a car.
- Real examples include Gemini Agent, ChatGPT agent, Claude computer use and coding agents like Claude Code, Codex and Jules.
- Agents are still slow and error-prone on fiddly tasks, and good ones ask before paying, sending or deleting.

**What are AI agents?** An AI agent is an AI system that is given a goal and works toward it on its own: it plans the steps, uses tools such as a web browser, email, a code runner or other apps, checks the results and keeps going until the job is done. A chatbot answers your question. An agent does the task.

Our 24-second version:

https://www.youtube.com/shorts/F2DlIXfeyr4

That is the short version. [IBM](https://www.ibm.com/think/topics/ai-agents) puts it as a system that "autonomously performs tasks by designing workflows with available tools", and [Anthropic](https://www.anthropic.com/engineering/building-effective-agents) draws the line between agents and simpler AI workflows by who is in charge: in an agent, the language model itself "dynamically directs" its own process and tool use. The rest of this explainer shows what that means in practice, with real products and numbers.

## What are AI agents and how do they work?

Think of a chatbot as a very well-read adviser on the phone: it can tell you how to book a rental car, but you still have to open the website and do it. An agent is the same adviser sitting at your computer, with permission to open the browser, compare prices and fill in the form, stopping to ask you before it pays.

Under the hood, almost every agent runs the same loop:

1. **Goal.** You give it a task in plain language: "organise my inbox" or "fix the failing test".
2. **Plan.** A large language model (LLM) breaks the goal into steps.
3. **Act.** It calls a tool: a web search, an API, a click or keystroke on a screen, a line of code in a terminal.
4. **Observe.** It reads what came back: search results, an error message, a new screenshot.
5. **Check and repeat.** It decides whether the goal is met. If not, it adjusts the plan and goes round again.

![Chatbot vs AI agent: a chatbot gives one answer, an agent runs a plan, act, observe, check loop with tools](/media/35632349a35040949b3c.jpg)
*Chart: NextDiff*

Three ingredients turn a plain LLM into an agent. Anthropic calls the building block the **augmented LLM**: a model "enhanced with augmentations such as retrieval, tools, and memory". **Tools** let it act on the world. **Memory** lets it remember earlier steps and your preferences. **Reasoning** lets it notice when a step failed and try something else.

Some agents work through APIs (they send structured requests to Gmail or a calendar). Others use a computer the way you do. [Google's developer documentation](https://ai.google.dev/gemini-api/docs/computer-use) shows the loop for its Gemini computer use model: the app sends the model a screenshot plus the history, the model answers with an action such as "click here" or "type this", the app performs it, takes a new screenshot and sends it back.

![Google's diagram of the computer use agent loop: screenshot and context go to the model, the app executes its action, then captures the new state](/media/6dceeb87506b482eafd2.jpg)
*Image: Google AI for Developers, Gemini API docs (CC BY 4.0)*

## Examples of AI agents you can use

- **Gemini Agent (Google).** [Announced on 18 November 2025](https://blog.google/products-and-platforms/products/gemini/gemini-3-gemini-app/) with Gemini 3, it handles multi-step tasks inside the Gemini app, connecting Gmail, Calendar, Deep Research and live web browsing. Google's example: "book a mid-size SUV for my trip next week under $80/day". It launched for Google AI Ultra subscribers in the US and, Google says, asks for confirmation before purchases or sending messages.
- **ChatGPT agent (OpenAI).** [Launched on 17 July 2025](https://openai.com/index/introducing-chatgpt-agent/), it merged OpenAI's Operator (which browses websites) and Deep Research into one mode that works on its own virtual computer with a visual browser, a text browser and a terminal. It first rolled out to Pro, Plus and Team users.
- **Claude computer use (Anthropic).** In [October 2024](https://www.anthropic.com/news/3-5-models-and-computer-use) Anthropic let developers have Claude look at a screen, move the cursor, click and type. On the OSWorld benchmark of real computer tasks it scored 14.9% in the screenshot-only category, almost double the next system's 7.8%. Anthropic called it experimental and "at times cumbersome and error-prone".
- **Gemini 2.5 Computer Use (Google).** A developer model [released on 7 October 2025](https://blog.google/innovation-and-ai/models-and-research/google-deepmind/gemini-computer-use-model/) that drives web browsers by clicking, typing and scrolling, with a safety service that checks each step before it runs.
- **Coding agents.** Tools such as Anthropic's Claude Code, OpenAI's Codex and Google's Jules read a codebase, edit files, run the tests and fix what breaks. Model makers now compete on "agentic coding" benchmarks, as our coverage of [GPT-6.1 Sol](/posts/gpt-6-1-sol-near-frontier-fifth-of-the-price/) and [Gemini 4 Argon](/posts/gemini-4-argon-benchmarks-vs-gpt-6-astra-claude-opus/) shows.

![Gemini Agent turns the request "organize my inbox" into a written plan: retrieve emails, then generate actions](/media/cf6293db8c71448ab78d.jpg)
*Image: Google, Gemini Agent demo (Gemini 3 announcement, November 2025)*

![Gemini Agent shows suggested inbox actions, with buttons to confirm or decline each one](/media/3935303c8bdb42fba808.jpg)
*Image: Google, Gemini Agent demo (Gemini 3 announcement, November 2025)*

The demo above shows the pattern every good agent follows: it writes a plan, proposes concrete actions, and waits for you to press confirm before it touches your inbox.

## AI agent vs chatbot vs assistant

| | Chatbot | AI assistant | AI agent |
|---|---|---|---|
| What you give it | A question | A command ("set a timer") | A goal ("organise my inbox") |
| Steps per request | One reply | One action | Many, chosen by the model |
| Uses tools | No, or rarely | A fixed set | Picks tools as it goes |
| Checks its own work | No | No | Yes, loops until done |
| Who does the work | You | It, for simple tasks | It, for multi-step tasks |
| Example | A plain FAQ bot | Classic Siri or Alexa | Gemini Agent, ChatGPT agent |

The labels blur in real products: ChatGPT and Gemini are chatbots until you switch on agent mode. The useful question is not the name but whether the system can take several steps and use tools without you driving each one.

## Why AI agents matter, and who they are for

Agents move AI from advice to action. For individuals, that means delegating chores that span several apps: sorting email, comparing prices, filling forms, turning research into a spreadsheet. For developers and companies, agents can run long jobs such as fixing bugs, processing invoices or answering support tickets end to end.

That is also why the industry measures models differently now. Benchmarks such as OSWorld (real desktop tasks), SWE-bench (fixing real GitHub issues) and AutomationBench (business workflows) score whether a model finishes a job, not whether it gives a good answer. When we reported that Gemini 4 Argon is strongest at long, multi-step agent work, these were the kinds of tests behind it.

## Common misconceptions about AI agents

- **"Agents are a new kind of AI."** Most are the same LLMs you chat with, wrapped in a loop with tools and memory. The loop is the new part.
- **"Agents work unsupervised."** The good ones are built to stop and ask before risky steps such as paying, sending or deleting, and Google and OpenAI both say their agents do this.
- **"More autonomy is always better."** Anthropic, which builds agents, advises "finding the simplest solution possible" and adding agent autonomy only when it clearly improves results. A fixed workflow is cheaper and more predictable.
- **"They already do anything a person can on a computer."** Not yet. They are slow (Google's own chart puts its computer use model at about 225 seconds for tasks it gets right 70% of the time), they still fail on fiddly actions like dragging and scrolling, and websites can try to trick them with hidden instructions, a risk called prompt injection.

## Latest news on AI agents

- [Gemini 4 Argon benchmarks: where it beats GPT-6 Astra and Claude](/posts/gemini-4-argon-benchmarks-vs-gpt-6-astra-claude-opus/): Google's flagship leads most of its own agent tests and runs in a hosted agent harness.
- [GPT-6.1 Sol brings near-flagship performance at a fifth of the price](/posts/gpt-6-1-sol-near-frontier-fifth-of-the-price/): OpenAI's cheaper model targets agentic coding and computer use.
- [ChatGPT's Intelligent UI turns answers into working tools](/posts/chatgpt-intelligent-ui-gpt-6-interactive-answers/): chat answers that you can click and use, a step between chatbot and agent.

## Questions readers ask

### What are AI agents in simple words?

An AI agent is AI that does a task for you instead of just answering a question. You give it a goal, and it plans the steps, uses apps or the web, checks its work and keeps going until the task is finished.

### How do AI agents work?

A large language model runs in a loop: it plans a step, calls a tool such as a search, an API or a click on a screen, reads the result, and decides what to do next. Memory keeps track of earlier steps, and the loop ends when the goal is met or it needs your approval.

### What is the difference between an AI agent and a chatbot?

A chatbot replies to each message and leaves the work to you. An agent takes a goal, chooses its own steps and tools, and carries out a multi-step task, usually asking you to confirm risky actions like purchases.

### What are examples of AI agents?

Google's Gemini Agent, OpenAI's ChatGPT agent, Anthropic's Claude computer use and Google's Gemini 2.5 Computer Use model, plus coding agents such as Claude Code, OpenAI Codex and Google Jules.

### Are AI agents safe to use?

They are useful but imperfect: they can make mistakes and can be tricked by malicious web pages (prompt injection). Major agents are built to ask for confirmation before purchases, sending messages or other high-stakes actions, so check what they propose before approving.

## Sources

- [Anthropic — Building effective agents (Dec 2024)](https://www.anthropic.com/engineering/building-effective-agents)
- [IBM — What are AI agents?](https://www.ibm.com/think/topics/ai-agents)
- [Google — A new era of intelligence with Gemini 3 in the Gemini app (Gemini Agent)](https://blog.google/products-and-platforms/products/gemini/gemini-3-gemini-app/)
- [Google — Introducing the Gemini 2.5 Computer Use model](https://blog.google/innovation-and-ai/models-and-research/google-deepmind/gemini-computer-use-model/)
- [Google AI for Developers — Computer use (Gemini API docs)](https://ai.google.dev/gemini-api/docs/computer-use)
- [Anthropic — Introducing computer use, Claude 3.5 Sonnet and Claude 3.5 Haiku](https://www.anthropic.com/news/3-5-models-and-computer-use)
- [OpenAI — Introducing ChatGPT agent](https://openai.com/index/introducing-chatgpt-agent/)
- [Neowin — OpenAI introduces ChatGPT agent that can complete tasks using its own computer](https://www.neowin.net/news/openai-introduces-chatgpt-agent-that-can-complete-tasks-using-its-own-computer/)