I was always an average developer. Although I had stardom moments, most of the time I struggled with basic programming problems—how to organize my classes, refactor the code, and where to put what. Until someone would make a simple remark in a code review or a water-cooler discussion, and suddenly it all made sense to me.
Sometimes I was confused about whether to use an AND or OR operator in a condition. That’s how bad I was.
I had problems understanding what I was truly working on. There was always this brilliant developer on the team who knew the exact answer to every question. He pointed to the exact part of the system where the issue lay and could tell the whole history about this particular part of the code—how and when it was created and how it evolved over time.
I was never that developer.
I, on the other hand, had to think long about every problem or question, and sometimes had to sleep on it for a few nights. When I came up with the solution, it was usually too late.
At some point during my career, AI became a hype in software development. Everyone was talking about it.
I knew that AI would never replace me at my desk. I mean, how could AI figure out all the required changes in our multi-service ecosystem, think of the ways to implement those in different services, test, and make them all work together? C’mon, every task I do is a struggle just to even set up the environment so the services can work together. Sometimes I just rely on tests in one service and test with other services in a staging environment. No, AI will never be able to do that.
But then again, I remember the hype in the industry when the Internet was invented. Yes, I’m that old. The Internet itself is a much simpler thing, and still, it disrupted the whole industry.
So I thought I should not underestimate the impact that AI would have on the industry.
I thought, instead of AI making me obsolete as an employee by replacing me at my desk, I could imagine companies changing—new companies using different tools to create products that are more suited for the current generations; companies changing their approach to developing products and services. I imagined companies that understand the moment and the new user base, able to deliver with tens of fewer employees than traditional companies.
I decided to incorporate AI into my daily work. When I designed a new feature, I sketched the solution into a few classes and asked AI to implement it for me in the way I imagined. It worked pretty well. It even refactored the code the way I told it to.
When even the most stupid thing was not clear to me, I could ask and get the explanation I really understood.
Then I thought, I can try to create something of my own using those tools. I could learn frontend and implement some of the ideas I had along the way. I already knew the backend. I could fill in infrastructure gaps also with aid from AI. I could have a complete product myself.
So I tried many ideas.
I used ChatGPT to create a React frontend for an appointment scheduling app, and also used ChatGPT to automate email communication with users. Success bookings, reminders, and error emails were all handled by AI.
Then I switched to Copilot to create a React app for displaying all possible guitar scales. I used AI to also help me with my pipelines, building out my CI/CD.
I tried building a shift scheduling app, again with help from AI, to create schedules based on rule inputs. I also automated communication about shifts, including the ability to cancel or swap, using ChatGPT. It was the best customer support I’d seen—and it was automatic.
I tried those ideas and many more.
And I failed in all of them.
But the industry changed very quickly. Many companies struggled, and layoffs were inevitable.
And when layoffs happened, some were kept. Some were even able to find jobs in other companies. Not the ones who kept JVM internals in the back of their head. Not even the ones who mastered object-oriented principles and were able to apply them in no time.
The ones who stayed—or got hired—were those who could adapt to new tools and use them to quickly build and deploy complete products and services. With a little help from AI.
And users loved the products, according to the reviews and reactions.
It’s 2025. I’m still an average developer. But I build brilliant things for people.
Read the story from parallel universe here.
Fatal Error 