Losing a Job Was the Wake-Up Call I Didn’t Expect

In November 2025, I lost my job. Since then, I have been applying continuously and struggling to understand how, despite having more thana decade of experience in product development across mobile, web, and backend systems, finding a new role was not coming easily. Over time, I realised the real problem wasn’t just the job market – it was my mindset.

I was stuck in the same SDLC patterns, assuming companies still valued long, rigid processes, while the industry had already moved toward faster execution, measurable outcomes, and rapid iteration. The uncomfortable truth was that I was almost a decade behind the reality of modern software development. That realisation forced me to pause and reassess what truly matters in today’s tech landscape.

Enter Artificial Intelligence. I started focusing on understanding how AI is reshaping the way software is built. In this article, we’ll dive into why Artificial Intelligence is no longer optional, whether you’re a front-end, backend, DevOps, or full-stack developer.

The Fear That AI Will Take Jobs & Why It’s Already Partly True

One statement that has always haunted me is that Artificial Intelligence will eventually take over our jobs, leaving only the kind of work that AI cannot reach. For a long time, I believed that domains like healthcare, agriculture, or even sales would remain mostly untouched. After all, I couldn’t imagine a machine diagnosing complex human problems, optimising real-world farming decisions, or convincing me to buy something. That assumption, however, is quickly falling apart. That future is no longer distant; in my ways, it is already here.

Bringing this back to software development, a field where I believed I had strong expertise, I realised that knowledge alone was no longer enough. Continuous practice through books, tutorials, and real-world problem-solving was still required, but the way I practised had changed. Initially, my biggest support came from my eldest brother. Over time, however, AI began to outperform even that human guidance. Today, I rely heavily on Artificial Intelligence tools in my daily development workflow.

I started using JetBrains AI tools and AI agents to build software, where my primary responsibility shifted toward reviewing generated code, making necessary corrections, and identifying critical edge cases. One such tool is Junie, an AI agent from JetBrains, which has proven to be extremely effective. At the same time, I am currently working on eight different products, each focused on solving a unique real-world probelm something that would have been significantly harder to manage without AI-assisted development.

You Don’t Need to Build AI Models to Stay Relevant as a Developer

There is one more important thing to understand here: you do not need to master building systems like ChatGPT, Claude, large language models (LLMs), or other foundational AI technologies unless you are specifically pursuing a career as an AI or machine learning engineer. These tools already exist, and they are mature, accessible, and ready to be used in a real-world product today.

I initially misunderstood what it meant to stay relevant in this era. I started learning Python with the assumption that I would eventually build my own version of ChatGPT, Claude, Gemini or advanced AI agents. In reality, developing such systems requires deep research, long-term focus, and serious academic commitment, something I personally plan to pursue through a master’s degree.

However, for full-stack developers, frontend engineers, and backend developers, the real advantage lies in learning how to use AI tools effectively rather than attempting to build them from scratch. Most modern AI platforms provide well-documented SDKs that are easy to integrate into existing applications. The barrier is no longer access; it is simply the willingness to learn and adapt.

How Companies Should Use AI to Increase Productivity, Not Replace Engineers

Today, companies are actively looking for developers who are skilled at using AI-powered tools because they significantly improve productivity, accelerate learning, and enable teams to move faster. Where many organisations are going wrong, however, is assuming that AI alone can replace engineers entirely. Layoffs are becoming inevitable not because engineers are obsolete, but because AI allows a single engineer to work efficently accross multiply tools and responsibilities.

For example, I can use tools like Loveable to generate a web page based on an existing design, then step in to review the generated code, ensure nothing sensitive slips through, optimise performance, and confirm that everything is structured correctly. This is where human judgment still matters. With AI handling much of the repetitive or time-consuming work, developers can spend more time reviewing, refining, and making critical decisions.

That said, becoming fully dependent on AI to fix bugs, update databases, resolve system conflicts, or generate revenue without proper oversight is a dangerous approach. AI is a powerful accelerator, not a replacement for engineering responsibility, and companies that fail to understand this balance are setting themselves up for long-term problems.

Why This Blog is Moving Beyond Tutorials in the Age of AI

One conscious decision I have made with this blog is to stop publishing a large volume of traditional tutorials. Today, most technical solutions can be found quickly through AI-driven platforms such as ChatGPT, Claude Code, Google Gemini, and similar tools. Repeating the same step-by-step guides no longer adds meaningful value in a world where answers are instantly accessible.

Instead, the focus of this blog will shift toward discussing the software industry itself, real experiences, evolving practices, and the practical impact of Artificial Intelligence on how products are built. As I continue building my own products and move deeper into the entrepreneurship space, while also seeking opportunities at companies where I can learn and apply AI at scale, this platform will document that journey and the lessons that come with building world-changing products.