An AI agent is software that pursues a goal on your behalf: it decides the steps, uses tools (search, email, a code editor, a CRM) to carry them out, checks the result and tries again if it fails. A chatbot answers; an agent does. You give it an outcome (“find three suppliers and draft the outreach emails”), not a prompt for each step.
The quickest way to understand one is to use one. Skip to Try one yourself, or read on for the definition, the types, and how to tell a real agent from a relabelled chatbot.
Tools worth knowing
These are the agents we’d point a newcomer to first, scored on our methodology (overall score out of 10):
- Everyday general-purpose agent: ChatGPT8.4 out of 10 — free tier, 8.4 overall. The most capable all-rounder, with browsing, code execution and a deep-research mode.
- Long documents and careful reasoning: Claude8.3 out of 10 — free tier, 8.3. Strong on large-context analysis and writing.
- Cited research answers: Perplexity7.1 out of 10 — free tier, 7.1. Shows sources for every claim, so it is easy to check.
- No-code workflow agent (email, CRM, calls): Lindy7.1 out of 10 — free tier (about 400 credits a month), 7.1. The gentlest on-ramp to an agent that acts rather than chats.
- Software tasks in your own repo: Claude Code8.3 out of 10 — from $20/mo (Claude Pro), 8.3. For developers who want to delegate multi-file work.
What counts as an AI agent?
Four capabilities, and a product needs all of them to deserve the label:
- Planning. It breaks a goal into steps without being handed the sequence.
- Tool use. It calls external systems — APIs, databases, a browser, code execution — so it can act, not just describe.
- Memory. It keeps state across steps (and sometimes sessions): what it tried, what you prefer.
- Self-correction. It checks its output against the goal and fixes mistakes.
If a human wrote the sequence and the AI just fills in blanks, that is a workflow with AI inside it. Analyst firm Gartner has warned about “agent washing” — vendors rebranding chatbots and RPA as agents — and estimated that only around 130 of the thousands of vendors claiming agentic products offer genuinely agentic capability. Our agentic AI vs generative AI guide covers that line in detail.
AI agent vs chatbot vs assistant
| Chatbot | Assistant | Agent | |
|---|---|---|---|
| You give it | A question | A request | A goal |
| It returns | An answer | A draft or suggestion | A completed task |
| Steps | One | One or a few | Many, self-planned |
| Acts on other systems | No | Sometimes, with approval | Yes, within limits |
The boundaries blur: ChatGPT8.4 out of 10 and Claude8.3 out of 10 are chatbots in ordinary use and behave as agents when given tools and a multi-step objective. The capability is a mode of use, not a fixed property of the product.
The five types of AI agent
The classic taxonomy, from Russell and Norvig’s standard AI textbook, still maps neatly onto what you meet in products:
- Simple reflex agents react to the current input with fixed rules — a thermostat, or an auto-reply that fires on a keyword.
- Model-based agents keep an internal picture of the world, so they cope with things they can’t see directly.
- Goal-based agents choose actions that move toward a target. Most modern LLM agents live here.
- Utility-based agents weigh trade-offs — cost against speed, risk against reward — to pick the best route to the goal.
- Learning agents improve from feedback over time.
For how these pieces are wired together inside a real product — the loop, the tools, the memory and the failure modes — see how AI agents work: architecture and risks.
Where AI agents are used today
- Customer support: agents resolve tickets end to end — look up the order, check policy, issue the refund. Quickchat AI7.5 out of 10 (free tier) and Intercom Fin7.3 out of 10 (from $49.50/mo) are two scored examples, aimed at small teams and larger ones respectively.
- Coding: agents read a repo, edit many files, run tests and open a pull request. See our ranking of the best AI coding agents.
- eCommerce: shopping assistants, post-purchase support and returns handling.
- Content creation and marketing: drafting, repurposing and optimising content at volume — useful, but with a human editing before publication.
- Research: agents that search, read and synthesise sources, from Perplexity7.1 out of 10 to specialised tools in the research category.
What agents are bad at
Honest limits matter more than the pitch. Agents make confident mistakes, and an agent that has already acted (sent the email, issued the refund) turns an error into a consequence. They work best where success is checkable — tests pass, the refund posted — and worst where “good” is subjective. Gartner has also predicted that over 40% of agentic AI projects will be cancelled by the end of 2027, citing cost, unclear value and weak risk controls. Start narrow, keep approval steps on anything irreversible, and measure completion rate, not demos.
Try one yourself
You don’t need a budget or a developer to see an agent work. Three low-friction starting points:
- ChatGPT8.4 out of 10 (free tier). Ask it to research a topic and produce a sourced one-page brief, then watch it search, read and revise. Free, and the broadest capability of any entry in our directory.
- Perplexity7.1 out of 10 (free tier). Ask a factual question with real-world stakes — a product comparison, a regulation — and check the citations it returns. Good for learning how much to trust an answer.
- Lindy7.1 out of 10 (free tier). Build a tiny agent that triages an inbox or logs a lead into a CRM. This is the clearest demonstration of an agent acting rather than talking.
Developers can add a fourth: point Claude Code8.3 out of 10 at a small repo and ask it to fix a failing test.
Which should you choose?
- Just curious, or general daily use: start with ChatGPT8.4 out of 10 or Claude8.3 out of 10; both are free to try and both scored highest in our directory.
- You need answers you can verify: Perplexity7.1 out of 10.
- You want to automate repetitive business tasks without code: Lindy7.1 out of 10, then compare workflow automation tools.
- You write software: Claude Code8.3 out of 10, Codex7.8 out of 10 or Cursor7.4 out of 10 — compare them in the coding ranking.
Next step
Open the ChatGPT8.4 out of 10 and Claude8.3 out of 10 pages to compare scores, pricing and weaknesses side by side, then read how agents work under the hood in Understanding AI Agents: architecture and risks. When you are ready to pick a tool for a specific job, use our guide to choosing the right AI agent.