Software development is a relatively young field compared to other well-established processes that have evolved over thousands of years — such as construction or shipbuilding. Moreover, the rapid advancement of artificial intelligence in recent years, and in particular LLMs, has forced the IT industry to reinvent the way software is developed.
In the past, building a fully functional application required an entire team of specialists — people responsible for frontend, backend, databases, system architecture, servers, testing, security, DevOps, and so on. Today, even a single person with no technical background can create software. Will it be high-quality software? As of the time I write these words — February 2026 — it will not. That said, it does not change the fact that an enormous revolution has taken place before our eyes. Just a few years ago, building fully functional software as a non-technical person was simply impossible.
I am not a proponent of the narrative that AI will take everyone’s jobs, as is often heard in mainstream media. Nevertheless, there is no doubt that the landscape of how software is developed is changing drastically.
Despite this enormous simplification of the software development process, it also carries significant risks. One constantly hears about poorly secured applications, loss of customer data, or leaks of sensitive information — not to mention the proliferation of software that nobody needs and that is impossible to maintain.
This is not another course on a specific technology where you learn how to use a particular tool. Nor do we debate which AI solution is better than another. Even less so is this a course intended to convince anyone that software development has now become effortlessly simple and anyone can do it. Quite the opposite.
The choice of technology is largely left to the reader — although, of course, certain established industry standards cannot be avoided.
For the purposes of this course, we will be building a simple application ourselves, and we will try to demonstrate how it should be built under the new conditions we find ourselves in — surrounded by AI.
We will start by explaining why software is actually built and how one should properly approach it at the planning stage, how to build an MVP, and how to begin making it available to users.
We will then introduce the reader to the world of AI agents, where we will build several practical solutions.
Before we dive headfirst into generating code with LLMs, it is very important to understand how that code is actually produced. At this stage, we build our own mini-team responsible for the entire software development process. The difference is that we will build it completely from scratch, rather than configuring a commercial, ready-made solution. This will allow us to better understand what happens “under the hood” when we ask AI to create an application.
The subsequent stages will cover classic topics related to software development (Frontend, Backend, DevOps, testing, users, permissions, backups, security). As we progress through these chapters, we will continuously expand our knowledge, develop our application, and grow our AI agents.
After completing this course, the reader should have sufficient knowledge to view the software development process in a much broader context and understand its complexities.