What are AI agents?
A great way to understand agents is to compare them with something we’ve all used before: AI chatbots like ChatGPT.
Existing, popular LLM-based chatbots are designed around the assumption that the user wants, expects, and will receive text output—words and numbers. No matter what the user types into the prompt, the tool is ready to respond with letters from the alphabet and numbers from the numeric system. The chatbot tries to make the output useful, of course. But no matter what, it’s designed for text in, text out.
Agentic AI is different. An agent doesn’t dive straight away into the training data to find words to string together. Instead, it stops to understand the user’s objective and comes up with the component parts to achieve that goal for the user. It plans. And then it executes that plan, usually by reaching out and using other software and cloud services.
