So You Wanna Build an A.I. Agent? Here’s How to Actually Get Started

Building an A.I. Agent

Building AI agents that can reason, make decisions, and help automate tasks sounds like something out of a sci-fi movie, right? But it’s not the future anymore — it’s the now. From self-writing code assistants to research bots that summarize long reports for you, AI agents are changing the way we work and think. But how do you go from zero to building something like that yourself?

If you’re someone with a programming background (even basic), and you’re curious about building smart, autonomous tools — this guide is for you.

Let’s break it down into a doable learning path.

Step 1: Nail the Basics of AI and Machine Learning

First things first — you need to know how AI actually works. Not just the buzzwords, but the real stuff under the hood.

Learn what machine learning is, how neural networks make predictions, and how large language models (LLMs) — the engines behind today’s smart agents — actually process and generate responses. You don’t have to become a data scientist, but you should understand how models are trained, how they learn from data, and what their limitations are.

While you’re at it, brush up on Python — the language nearly all modern AI tooling is built on.

Step 2: Understand How Agents Think

Now we’re talking agents. In AI-speak, an agent is basically something that can observe the world, make decisions, and take action to meet its goals. You’ll come across different kinds of agents: reactive ones, goal-based agents, utility-based ones, and learning agents that adapt over time.

This is where things get really interesting. Agents don’t just spit out answers — they have memory, planning strategies, even reasoning loops. Understanding the fundamentals here will set you up for everything that comes next.

Step 3: Play With Real Tools — LangChain, AutoGPT, and Friends

This is where theory meets real-world action.

Today’s hottest agent frameworks are built on top of large language models (think GPT-style models). Tools like LangChain, AutoGPT, BabyAGI, and CrewAI let you build autonomous agents that can use tools, search the web, execute code, and even collaborate with other agents.

You’ll learn how to:

Connect your AI to tools like calculators or file readers
Set up planning steps (like “plan → search → decide → act”)
Build memory so your agent remembers what it did earlier
Use vector databases for knowledge retrieval

Start with a small project — maybe a task manager agent or a research summarizer. Keep it simple, but hands-on.

Step 4: Give Your Agents a Brain (Memory, Planning, Tools)

Basic agents are cool, but real power comes from combining memory and tools. Want your AI to remember a conversation? Feed it a memory module. Want it to pick the right tool for the job? Teach it to make decisions and choose functions.

This is where things like Retrieval-Augmented Generation (RAG), tool use, and even multi-agent systems come into play. You’ll find yourself mixing logic, state machines, and API calls in new and creative ways.

There are even frameworks now where multiple agents collaborate like a team — a project manager agent assigns tasks to worker agents, who then report back. Wild, right?

Step 5: Build, Break, Repeat

Once you’ve got a handle on how agents work, start experimenting. Build projects. Break stuff. Try giving your agent tasks that require multiple steps, decisions, or collaboration.

Some fun project ideas:

A debugging agent that fixes broken Python scripts
An AI assistant that can schedule your meetings and send follow-ups
A research bot that digs through PDFs and gives you a summary

Don’t be afraid to go deep. This space is new and rapidly evolving, so half the fun is figuring it out as you go.

Keep Your Ethics in Check

AI agents are powerful, and with great power comes… well, you know the rest. As you explore what’s possible, it’s worth learning about the ethical side too — safety, alignment, transparency, and making sure your agent doesn’t go rogue and delete your entire drive (it happens).

There are tons of great discussions happening around the ethics of autonomous agents, so stay curious and stay grounded.

Final Thoughts

Learning how to build AI agents isn’t just a fun side quest — it’s a smart investment. Whether you’re into automating workflows, building products, or just curious about where tech is headed, this is one of the most exciting areas in software today.

Start with the basics. Don’t rush it. Get your hands dirty. And before long, you’ll have an agent that’s doing stuff for you — and maybe even thinking a few steps ahead.

Reasons to Learn F#

F# is a powerful, functional-first programming language that is gaining popularity among developers for its concise, expressive syntax and strong type system. Here are five reasons why you should consider learning F#:

F# encourages functional programming techniques, which can lead to more concise and maintainable code. In functional programming, functions are treated as first-class citizens, and immutability is encouraged. This means that you can easily pass functions as arguments to other functions, which can lead to more modular and reusable code.
F# has a strong type system, which helps catch errors at compile time rather than runtime. This can save a lot of time and frustration in the long run, as it is much easier to fix a bug that is caught early in the development process.
F# integrates seamlessly with the .NET ecosystem, which means that you can use F# to build web applications, desktop applications, and mobile apps using the same tools and frameworks that are used for C# development. This can be a big advantage for those who are already familiar with the .NET platform.
F# is a great language for data science and machine learning. Its functional programming style and strong type system make it well-suited for tasks such as data transformation and manipulation, and it has a number of libraries and tools specifically designed for data science and machine learning.
Learning F# can also be a great way to improve your skills as a developer more generally. Its functional programming style can help you think more abstractly and logically, and its strong type system can help you write more robust and maintainable code.

Overall, F# is a powerful and expressive language that is well worth learning. Whether you are a seasoned developer looking to expand your skillset or a beginner who is just starting out in programming, F# has a lot to offer. Its functional programming style, strong type system, and seamless integration with the .NET ecosystem make it a great choice for a wide range of projects.

How to get started in Linux Kernel Programming.

Linux kernel programming can seem like a daunting task, especially for those who are new to the world of operating systems. However, with a little bit of knowledge and some practice, it is possible to become proficient in this area of programming. In this article, we will cover some of the basics of Linux kernel programming and provide some tips on how to get started.

The Linux kernel is the core of the operating system and is responsible for managing the hardware and software resources of the system. It is a monolithic kernel, which means that it contains all the necessary drivers and modules needed to operate the system, as opposed to a microkernel, which only contains the essential components.

One of the first steps in getting started with Linux kernel programming is to set up a development environment. This typically involves installing a Linux distribution on a separate machine or virtual machine and setting up the necessary tools and libraries. Some popular distributions for kernel development include Ubuntu, Fedora, and CentOS.

Once the development environment is set up, the next step is to obtain the kernel source code. The kernel source code is freely available and can be downloaded from the official Linux kernel website or through a version control system such as Git. It is important to ensure that you are downloading the correct version of the kernel, as different versions may have different features and APIs.

Once you have the kernel source code, you can begin exploring and modifying it to better understand how it works. A good place to start is by looking at the documentation and code comments provided within the source code. The kernel documentation is located in the Documentation directory of the kernel source code and contains information on various kernel subsystems and APIs.

As you become more familiar with the kernel source code, you may want to try modifying and building the kernel. To do this, you will need to configure the kernel using the “make menuconfig” command. This will bring up a text-based menu that allows you to enable or disable various kernel features and select the modules that you want to include in the kernel. Once you have finished configuring the kernel, you can build it using the “make” command.

Once the kernel has been built, you can test it by booting it on your development machine or virtual machine. If you encounter any issues, you can use a kernel debugger such as GDB to identify and troubleshoot the problem.

As you become more comfortable with the kernel source code, you may want to try adding your own code to the kernel. This could be in the form of a new driver, a new system call, or a new kernel module. To do this, you will need to familiarize yourself with the kernel coding style and follow the guidelines outlined in the kernel documentation.

One of the challenges of kernel programming is dealing with concurrency and synchronization. The kernel is a multi-threaded environment, with multiple processes and kernel threads running concurrently. This can make it difficult to ensure that shared resources are accessed in a thread-safe manner. To address this issue, the kernel provides a number of synchronization mechanisms such as spinlocks, mutexes, and semaphores. It is important to understand and use these mechanisms appropriately to avoid race conditions and other synchronization issues.

As you gain experience with Linux kernel programming, you may want to contribute your code back to the community. The kernel is developed and maintained by a community of volunteers and is always looking for new contributions. To contribute your code, you will need to follow the kernel submission process, which involves submitting your code for review and testing by the kernel maintainers.

In conclusion, Linux kernel programming can be a rewarding and challenging field of study. With a little bit of knowledge and practice, it is possible to become proficient in this area in order to get started in Linux kernel programming, it is helpful to have a strong foundation in C programming and a good understanding of operating system concepts. It is also important to have a curiosity and willingness to learn, as there is a lot to learn when it comes to kernel programming.

One way to gain experience and knowledge in Linux kernel programming is to participate in online communities and forums, such as the Linux Kernel Mailing List (LKML). This is a great resource for getting help and advice from other kernel developers, as well as staying up to date on the latest developments in the kernel.

Another way to learn more about Linux kernel programming is to work on small projects and exercises. There are many resources available online that provide exercises and challenges for learning kernel programming. These can be a great way to practice your skills and get a feel for working with the kernel.

It is also helpful to have a good understanding of computer hardware and how it works. The kernel is responsible for managing the hardware resources of the system, so a good understanding of hardware is essential for kernel programming.

Finally, it is important to be persistent and patient when learning Linux kernel programming. It can be a challenging field, and it may take some time and effort to become proficient. However, with dedication and practice, you can become a skilled Linux kernel programmer.

Why Learn Linux in 2023?

Linux is a powerful and versatile operating system that is widely used in a variety of settings, from personal computers and servers to smartphones and smart TVs. While it may seem intimidating to those who are not technically inclined, learning Linux can offer numerous benefits for anyone looking to improve their computer skills and expand their knowledge of technology. Here are a few reasons why someone who isn’t technically inclined should consider learning Linux in 2023:

Cost: One of the biggest advantages of Linux is that it is free and open-source. This means that you can download and use it without having to pay any license fees or subscriptions. This can be a great option for those who are on a budget or who simply want to save money on software.

Customization: Linux is highly customizable, allowing users to tailor the operating system to their specific needs and preferences. This can be especially useful for those who want to use their computer for specific tasks or who want to personalize their computing experience.

Security: Linux is known for its security features, making it a good choice for those who are concerned about online threats such as viruses and malware. Linux is less susceptible to these types of attacks and can offer added protection for your data and personal information.

Compatibility: Linux is compatible with a wide range of hardware and software, making it a good choice for those who want to use their computer for a variety of purposes. It can run on older hardware and can be used with a wide range of applications, from office productivity tools to graphic design software.

Community: One of the great things about Linux is the strong community of users and developers that support it. There are numerous online forums, discussion groups, and resources available to help users learn and troubleshoot issues with Linux. This can be especially helpful for those who are new to the operating system and may need additional guidance.

Overall, learning Linux can be a great way for someone who isn’t technically inclined to improve their computer skills and expand their knowledge of technology. Whether you are looking to save money on software, customize your computing experience, or simply want to learn something new, Linux is a great choice.

Updates are forthcoming to this website!

Hey all,

This website has sadly been neglected for far too long. This is hopefully going to change. As I continue to write and produce content for Udemy, Kindle, and other platforms I am aiming this to be a portal to those particular platforms.

There are various reasons I have neglected this website. However, as I continue to produce content on other platforms this will be the best resource to get updates/deals on any course(s) I offer.

Please stay tuned to this website for any updates because the best deals will obviously originate from this website first!

For instance, my latest YouTube Tutorial series can be found here:

https://www.youtube.com/watch?v=MqneMDfD400&list=PLgIhXk-7SCrUMJ-zcv4AQ2BNLfmzG5yNE

Eventually, I may need to do a complete overhaul of this website as the need may arise. Thank you for reading any of my articles on this website. I appreciate it!