Things moved quickly after I started using chatbots. New versions, new terms, new acronyms. And I was busy with actual work, family, and life.
Then I started hearing about agents. And I remember wondering: “Is this really any different from the ChatGPT-type chatbots?”
You still type into a chat window. It still replies. But now it can also do things for you. So what’s different?
That’s what Monty and I are exploring in Agents Unpacked. Monty is my AI assistant. I’m asking the questions.
I’ve set Monty up to follow my teaching and writing style. I teach the way I like to learn, so that matters here. The aim is for his explanations to reflect that approach, too: start with something concrete, build the intuition, and introduce the technical terms when they’re needed.
I tried an earlier version of this exercise. My learning agent drafted a chapter, and I went through it adding questions and comments. We revised it until I was happy with it.
This time, we’re having the conversation first. Monty researches the topic, and then we talk. I ask questions when something isn’t clear, or challenge an explanation that doesn’t quite work. Sometimes I try to explain what I’ve understood, and Monty points out what I’ve got wrong.
And sometimes I need to point out what Monty’s got wrong, too.
What you’ll read is the conversation we actually had. We tidy it up afterwards, take out some clutter, and check the explanations. If an explanation needs correcting, I review that change, too. The questions aren’t added later to make a tutorial look like a conversation.
Yes, Monty’s answers are AI-generated. But I’m involved throughout, and I decide what makes it into the article. An answer that sounds convincing isn’t necessarily a correct one.
We’ll start with that question about agents and chatbots. Then we’ll look at who’s doing the work, what an agent remembers, and how much freedom we should give it. And what happens when it gets things wrong.
You don’t need to know how to program to follow along. We’re trying to understand what’s happening, rather than learn one particular tool.
There’s a planned table of contents, but it may change. We’ll see where the questions take us.