Why I am working with AI agents.

I have been working in sales for almost 10 years, and I have learned one thing: time is always tight. Most tasks repeat themselves, some are boring, and many require a lot of effort. This is exactly where Artificial Intelligence comes into play.

In the coming weeks, I will evolve from a traditional sales professional into an "AI Consultant." To do this, I am starting with a topic that everyone is talking about right now: AI agents. But what are they exactly, and why should you care about them?

🤖 What are AI agents exactly?

To put it simply, an agent is a digital assistant or team member that can do more than just answer questions (like a chatbot); it also takes action.

An agent can:

-research information on the internet

-extract data from documents

-fill out tables

-use tools (e.g., email, calendar, CRM)

-plan steps and make decisions

The key point: agents are goal-oriented. I give them a goal ("Research three companies and summarize them"), and the agent finds the way to get there on its own.

💬 The difference: Chatbot vs. LLM vs. Agent

It is helpful to look at the differences:

-Chatbot: The classic version. It answers questions, usually from a specific set of knowledge (FAQ, support). It is mostly reactive.

-LLM (Large Language Model): The "brain" behind it. An LLM like GPT-4 or Claude is a language model that understands and creates text. Without tools, it stays limited to text.

-Agent: An agent combines an LLM with tools and a logic for taking action. It can open browsers, save data, and start workflows. This turns a chatbot into a "team member" that becomes active on its own.

In short:

👉 Chatbot = Q&A. 👉 LLM = language intelligence. 👉 Agent = an intelligent assistant that actually acts.

Why do we need AI agents?

In sales, marketing, or operations, we often hit our limits:

-Research takes forever.

-Data is scattered across PDFs, emails, or spreadsheets.

-Routine tasks eat up valuable time.

An AI agent can take over these repetitive tasks and deliver in just a few minutes what would otherwise take several hours.

Examples:

-A research agent automatically creates customer profiles.

-An extraction agent moves data from PDFs into the CRM.

-A proposal agent writes drafts including pricing info.

This is what makes AI agents so exciting: they are a way to scale up and save time at the same time.

How do you get started?

The good news: you don't have to be a programmer to start with AI agents. My tip for getting started:

1. Build a basic understanding -What is an AI agent, and how is it different from a chatbot? -Learn basic concepts: goals, tools, and guardrails (e.g., step limits).

2. Experiment with no-code tools -Platforms like Lindy, Relevance AI, Zapier, or n8n offer templates. -Usually, it is enough to: pick a template, activate tools, enter a goal, and start.

3. Start small -Example: Build an AI agent that researches 3 companies and writes a one-page briefing. -Failure is part of the process: you will quickly see that agents need clear boundaries and rules.

4. Grow from use case to use case -Start with research, then extraction, then workflows. -This way, your understanding grows step by step.

🎯 My conclusion

For me, agents are the next logical step in sales: moving away from manual, time-consuming tasks and toward more focus on the customer.

On my journey, I want to find out: -Which AI agents bring real value? -Where are the limits? -How do you use them safely within a team?

👉 In the coming weeks, I will study, document, and share exactly that. If you are interested, you can follow along—from the first steps to a finished AI agent in daily life.