Glossary
What is an AI agent?
Software that works toward a goal over several steps, choosing which tools to use, instead of answering one prompt at a time.
Definition
An AI agent is software that works toward a goal over several steps, deciding what to do next and which tools to use along the way. In sales and marketing, that might mean finding prospects, researching them, writing outreach and logging results, instead of answering a single question or running a fixed script.
How an AI agent works
Most agents run a loop. They get a goal, look at the current state, pick an action, use a tool (search the web, query a CRM, send an email, read a calendar), check the result and decide the next step. They stop when the goal is met, when they hit a limit you set, or when they need a human.
At the center is usually a large language model. What turns it into an agent is the loop, plus access to tools and a memory of what it has already done.
AI agent vs chatbot vs workflow automation
- Chatbot. Answers what you ask, one turn at a time. It doesn't act on its own between messages.
- Workflow automation. Follows steps someone defined in advance: when a form is submitted, add a CRM row and send email A. Anthropic's engineering team draws the line this way: workflows run language models and tools through predefined code paths, while agents direct their own process and tool use.
- AI agent. Gets a goal and chooses the steps. Two runs on the same goal can take different paths.
An example in sales
Say you sell bookkeeping software to dental clinics. A workflow sends the same three-email sequence to every clinic on a list. An agent given the goal "book five demos with clinic owners in Texas this month" would find clinics, check which owners are active on LinkedIn, read each clinic's site to tailor the opener, pick a channel, follow up when someone replies and send a booking link when a prospect asks for a time.
Common mistakes
- Calling any chatbot or rules-based sequence an agent. Ask whether it chooses its own next step.
- Giving an agent a vague goal. "Get leads" produces noise. A defined customer profile and daily limits produce usable work.
- Skipping guardrails. Set limits on volume, channels and what the agent may send without review.
How Siela AI uses it
Siela AI runs five agents, including an AI SDR that finds leads and runs outreach on LinkedIn, X and email from your own accounts within daily goals you set, and a Call Agent that joins Zoom, Google Meet or Microsoft Teams calls from a brief.
Questions
What is the difference between an AI agent and a chatbot?
A chatbot responds to each message you send and then waits for the next one. An AI agent takes a goal and works through several steps on its own, using tools like search, email or a CRM, and decides what to do next based on what it finds.
Are AI agents fully autonomous?
Not necessarily. Autonomy is a setting, not a fixed trait. Many teams let agents research and draft freely but require approval before anything is sent, or cap how many actions the agent can take per day. The right level depends on how costly a mistake would be.
Can a small team use AI agents for sales?
Yes. Small teams often benefit most, because they lack people for repetitive prospecting and follow-up. What makes it work is a clear target customer, sensible daily limits and someone reviewing the results every week.
Sources, checked 25 October 2026: Anthropic: Building effective agents.
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