Fazley RabbiAn AI agent is an AI system that works towards a goal by taking several steps on its own. It reads a request, decides what to do next, uses tools such as a record search or a calendar, looks at the result, and continues until the task is done or it needs help. A chatbot mainly talks; an agent can also act. That ability to act is what makes agents useful, and it is also why they need clearer limits than a chatbot.
Chatbots and agents side by side
| Chatbot | AI agent | |
|---|---|---|
| Main job | Answers questions in a conversation | Completes a task that may take several steps |
| Tools | Usually none, or a fixed set of answers | Calls the tools you allow: search records, fill forms, create drafts |
| Decisions | Chooses a reply | Plans steps, picks which tool to use, reacts to results |
| If it goes wrong | A poor answer | A wrong action, such as an incorrect record or message |
| Supervision | Light | Clear permissions, logs and human approval for important steps |
The line between the two is not sharp. Many chat assistants now have a few agent-like abilities, such as checking an order status. What matters is not the label but what the system is allowed to do.
How an agent works, in plain terms
Think of an agent as a new office assistant who reads very fast but has no common sense about your business. You give it three things:
- A goal, such as "find this customer's recent orders and draft a reply about the delayed one".
- Tools, each one a specific permission: read the order sheet, check the courier status, create an email draft.
- Instructions, covering tone, what it must never do, and when to hand over to a person.
The agent then works in a loop: think about the next step, use a tool, look at what came back, decide again. Connecting agents to business tools is getting easier through open standards such as the one explained in Model Context Protocol explained.
Work that suits agents
These hypothetical examples suit agents because every step can be checked:
- Order enquiries. A customer asks on Messenger where their parcel is. The agent finds the order, checks the courier status and replies with the facts, or hands over if something looks wrong. The AI assistant for Facebook page messages solution covers this set-up, including the hand-over to staff.
- Preparing paperwork. An agent gathers a buyer's details from an email, fills a quotation template from your price list and leaves it as a draft for the sales team.
- Research before a meeting. Before a call with a possible distributor in Khulna, an agent collects what their website says and your past emails with them into a one-page brief.
- Internal questions. A staff member asks about the return policy for damaged items, and the agent answers from your own policy document and shows where the answer came from.
What agents should not do alone
Some actions should never be left to an agent without a person approving them:
- Sending money, issuing refunds, or changing prices and discounts.
- Deleting records or editing customer data in bulk.
- Making promises about delivery dates, warranty or legal matters.
- Giving medical, legal or financial advice.
- Making hiring decisions or judging any person.
- Posting publicly under your brand.
Agents can misunderstand an instruction, act on wrong information, or be misled by text hidden inside an email or document they read. That last risk, often called prompt injection, is a strong reason to limit what each tool can do rather than relying on the agent's judgement.
Guardrails that keep agents safe
When I design an agent workflow, I start by listing what it must not be able to do, and then add only the permissions it truly needs. Useful guardrails include:
- Least permission. Read-only access unless writing is genuinely required.
- Draft, don't send. The agent prepares; a person approves anything that leaves the business.
- Clear hand-over rules. When the agent is unsure, the customer is upset or the request is out of scope, it passes the case to a person with a short summary.
- Logs. Every step and tool call is recorded, so you can see exactly what happened.
- Step limits. A cap on how many actions it may take per task, so a confused agent stops instead of looping.
- Testing on real examples before it ever talks to live customers.
The article on human review in AI workflows goes deeper into where people must stay in control.
Common questions
Is an agent the same as automation? An agent is one kind of automation. Rule-based automation follows the same path every time; an agent chooses its own path within limits. Use the simpler option whenever it is enough.
Do I need an agent, or is a chatbot enough? If customers mostly ask the same questions, an assistant that answers from your own information may be all you need. Agents make sense when a task requires looking things up or acting across several tools.
Can an agent work at night? Yes, within the permissions you give it. That is why night-time and holiday enquiries are a common starting point, with anything sensitive left waiting for staff in the morning.
Where to start
Write down one task your team does that involves checking two or three places and then writing something. List the tools it touches, the steps that are safe to automate, and the step where a person must approve. That list is the outline of a sensible first agent. If you want help turning it into a working design, see AI and workflow automation.