Why build an agent

0:00 You'll gain a deep understanding of how these powerful AI tools work together under the hood. Lane will guide you through creating an agentic loop powered by tool calling, allowing your agent to interact with and modify code similar to advanced tools like Open AI's codecs. This unique focus on building from the ground up combined with the use of a free and accessible API provides a distinct advantage for those looking to truly master AI agent development and enhance their Python and functional programming skills.

0:45 Look, there's an alleged gold rush happening right now. It's called AI. You may have heard about it. Now, as you know, mining for gold in a gold rush is usually a losing strategy. And in this case, that means vibe coding. So, instead of mining for gold yourself, just sell the shovels. Or in other words, build your own coding agent. Okay? Look, we're not actually building our own AI agent from scratch because we plan to sell it and make millions of dollars.

1:10 No, no, no. Uh the reason we're doing it is so that we as programmers can better understand the tools that we use. It's the same idea behind why we still learn about binary trees. Even though modern databases handle most of that advanced data retrieval for us, we do it so that we can understand how the tools that we work with on a daily basis actually work under the hood so that we can then use them more effectively.

1:32 And honestly, building your own agent from scratch is just a really fun practice project. When you're done with this course, you'll have a solid understanding of how LLM APIs work, specifically the Gemini Flash API. You'll also have done one of the more advanced things that you can even do with these AI APIs, building an agentic loop powered by tool calling. Now, the coding agent that we'll be building is a command line tool. It's similar to OpenAI's codeex or Anthropics Claude code.

1:55 It's the same kind of fundamental agentic loop that cursor uses, just on the command line instead of through an editor's guey. But we're not just building any app here. We're building an app that can help us build other apps. And we'll be following along with the interactive version of this course over on boot.dev. So if you don't yet have an account, go to boot.dev and make one. All the content is free to read and watch there as well.

2:18 Now, please actually follow along and type out all the code yourself. If you just kick back and watch me do everything from start to finish, you won't learn nearly as much, if anything. Now, even though all the content on Bootdev and of course the content in this course on YouTube is free, if you do find that you enjoy the interactivity on the Bootdev platform as you're following along, the stuff like lesson submissions, quests, boots, the chatbot, and certificates of completion, those are paid interactive features.

2:42 But I just want to be clear here, you do not need a paid membership to follow along with this course. And finally, before we jump into my editor, I just want to give a huge shout out to Free Code Camp for allowing us to share this course with you. So, please like and subscribe to their YouTube channel. Their mission is incredible and they've helped so many people through these sorts of long- form videos. So, if you like this style of course specifically, you can also subscribe to my channel on boot.dev.

3:29 We have tons of these kinds of long form courses as well, including Prime's Git course, TJ's memory management course, and Trash Puppy's Python course, and a bunch of others as well. So, with all that out of the way, it's time to build an AI agent in Python. Okay, time for Bootdev to cash in on all this AI hype. Um, if you've ever used Cursor or Claw Code or OpenAI's codeex, that's basically what we're going to be building in this course.

3:55 Um, but it's going to be more of a toy version. But the fundamental idea is the same, right? We're going to be building an AI agent that can modify code on its own. And not just, you know, a chat GPT wrapper, but one that actually can scan the file system and make changes to files, even run code to kind of get feedback on what's working and what's not, and then take another pass at trying to fix, you know, what the bug is or maybe implement a new feature, whatever it is that we ask it to do.

4:17 So, what does an agent do, right? like what's the difference between an AI agent and just you know chat GPT? Well, very simply, it first accepts a coding task, right? Something like the strings aren't splitting in my app. Can you please go fix that? You can't do that with an in browser chatbot, right? Because it doesn't have the context of your project. So, if you've ever, you know, worked on a coding project while you're working within something like chat GPT, you're constantly copying and pasting code back and forth into the chat, trying to tell it what the expected behavior is, stuff like that.

4:42 A coding agent, you know, something like cursor or cloud code or whatever, it has the ability to scan your project directory, right? It can it can look at what files are in there. It can run the code. It can update the contents of different files. So it's able to kind of gather its own context about what's going on and that's why it makes it just a lot more powerful when you're building projects. So again, in this course, we're going to be building our own AI agent, our own little CLI chatbot powered by Google's Gemini, right?

5:30 All these agents are are powered by some larger LLM. So the thing that makes it an agent is that it can do things within a loop. So rather than just, you know, here's a prompt, give me back a oneshot response, the thing that makes it an agent is that it can kind of self-prompt itself over and over and over. It can take multiple passes at a single input prompt that you as a user give it. And and the way it kind of generates this feedback loop is through something called tool calls.

5:54 So for example, there's there's four kind of tool calls that we are going to make available to our agent. And it's kind of crazy how much it can do with just four tool calls. One, we're going to give it the ability to scan the files in a directory. Basically, give it the ability to type ls, right? Or use the ls command. We're going to give it