AI Agent
By Federico Donatone · Updated October 15, 2026An AI agent is software that uses an AI model to work toward a goal in a loop: it reads the situation, decides on an action, uses a tool such as a CRM, browser or email, checks the result and repeats until the job is done. Unlike a chatbot, it acts instead of only answering.
What is an AI agent made of
- A model that does the reasoning, such as Claude.
- Instructions: the job, the rules, the voice and what it must never do, usually kept in a plain-text file.
- Tools: connections to email, calendar, CRM, files or the web, so it can act and not just write.
- Context: the information it can see while it works, from the task itself to the results of earlier steps.
- A trigger: a schedule, an incoming message or a person asking.
- Guardrails: approval steps before anything is sent, paid or deleted.
The model is the part people compare. In our client work, the part that decides results is usually the instructions. Our guide to AI agents for business breaks a good brief into four parts: a definition of done, the constraints, one excellent example and a self-check the agent runs before showing its work.
AI agent vs chatbot vs automation
| Chatbot | Workflow automation | AI agent | |
|---|---|---|---|
| What it does | Answers questions | Runs fixed steps | Pursues a goal |
| Who picks the next step | The user | Whoever built it | The agent |
| Uses tools | Rarely | Yes, fixed ones | Yes, chosen as needed |
| Handles surprises | No | No, it stops or errors | Often, by trying another path |
| Best for | Quick answers | Stable, repeatable tasks | Multi-step work with judgment |
The line between them is blurring. A chatbot becomes an agent once it gets tools and permission to loop, and many automation platforms now let an agent handle one step inside a fixed flow.
AI agent examples in B2B sales
- Prospect research: reads an account's website, news and hiring pages and writes a sourced brief.
- Call preparation: pulls CRM history and recent activity into a one-page brief before a meeting.
- Follow-up drafts: turns a call transcript into a recap and next steps for the rep to review.
- List building: finds companies that match the ideal customer profile (ICP), identifies the right contacts and checks their emails.
- CRM hygiene: flags deals with no next step, missing fields or stale close dates.
An agent that writes to a buyer should never send on its own. We keep a human approval step in front of every email, post and proposal, and we build agents on plain-text rules the team can read and edit. Our walkthrough on how to build an AI agent with Claude shows that setup step by step, and the AI SDR guide covers how to split work between agents and reps.
Where AI agents still fall short
Agents struggle when the truth lives in conversations nobody wrote down, when judgment depends on internal politics, and when the task changes from week to week. They also need maintenance: when a website changes or a login expires, someone has to read the alert and fix it.
None of this is a reason to wait. Inside those limits, research, drafting, enrichment and reporting already work with a clear brief and a person checking the output. Start there, measure how long reviews take, and widen the agent's job only when the corrections drop.