There’s no denying it. The sun will soon begin to set on my long and fulfilling career in technology. I’m still some years off, but as I approach retirement I’m finding myself drawn back to where it all began: the simple, pure joy of coding. It’s a feeling that’s been stirring for a while now, a quiet longing for the days when I could lose myself in lines of logic, crafting something from nothing.
My journey started in 1981, hunched over a Commodore VIC-20 in my parents’ front room, learning Commodore BASIC. There was no Stack Overflow, no integrated development environments, no IntelliSense. Just me, a magazine listing, and an almost religious commitment to typing in hundreds of lines of code. The real learning came not from the initial successful run, but from the inevitable typos. Debugging was less about formal tools and more about meticulous line-by-line inspection – a crucible that forged my problem-solving skills from day one.
A Career Forged in Code
Fast forward to 1988, and I landed my first professional programming gig as full-time employee number one at a small software house, writing programs in GW-BASIC and then QBASIC on PCs running MS-DOS. For five years, I was immersed in the trenches of early commercial software development. After a brief sabbatical, I fell into programming with a little-known 4GL called System-Z on the AIX (Unix) operating system, and began navigating the complexities of enterprise IT. Then, as the web began to bloom, I taught myself Visual Basic, crafting VB6 applications for major UK utility companies, picking up invaluable Oracle PL/SQL skills along the way.
For a significant part of my career, I lived and breathed code. But as happens to many seasoned professionals, my path eventually veered towards leadership and management. While I embraced the new challenges of guiding teams and shaping strategy, the hands-on coding slowly receded. I kept my fingers somewhat limber with personal projects – VBScript on ASP, JavaScript, Java, some Ruby on Rails, and Python – but the serious, dedicated coding became a distant memory.
It’s been over ten years since I last truly immersed myself in a coding project, and I miss it a lot.
The Allure of Python and the AI Question
As retirement appears on the horizon, I’m contemplating a return to the keyboard, purely for the love of it. My language of choice? Python. Its reputation for readability, versatility, and a vast ecosystem makes it incredibly appealing. I also like the way it’s primary an interpreted language (like BASIC), albeit with elements of compilation.
There’s a question that nags at me though – one I know many developers, both old and new, are grappling with:
With the explosive rise of generative AI being used to produce code, is learning Python “properly” still a worthwhile endeavour? Or is it a waste of time, like stubbornly using a rotary phone in the age of smartphones?
My gut feeling and experience tell me it isn’t a waste of time. I think my approach should be “retro-style”, much like how some people still appreciate the rich, tactile experience of listening to vinyl records.
The “Vinyl Enthusiast” of Coding in the AI Era
My professional experience tells me that the future of commercial programming will indeed leverage AI extensively. AI will become an incredible force multiplier for developers, handling boilerplate stuff, suggesting syntax, assisting with refactoring, and even debugging. The role of the commercial programmer will evolve into that of an architect, a problem definer, a prompt engineer, and most crucially, a critical evaluator and refiner of AI-generated code. Understanding why AI code works (or doesn’t) will be paramount.
But for the hobbyist, for the enthusiast, for someone like me who simply misses the act of creation? That’s where the “retro-style” approach will truly shine.
Learning Python properly isn’t a waste of time – it’s an investment in a deeper form of enjoyment and mastery.
I think of it this way:
- Understanding the “Why”: AI can give us Python code, but it doesn’t give us the intrinsic understanding of why that code is the best solution, or how to adapt it when it inevitably breaks or needs to handle a nuanced edge case. That foundational understanding comes from learning the language from the ground up – data structures, algorithms, object-oriented principles, testing methodologies.
- True Debugging Prowess: When AI-generated code inevitably fails, we’ll need the skills to debug it. Relying solely on AI to debug AI can be a frustrating loop. Anyone with “typed-from-magazine-listing” debugging skills like mine will be valuable, but not likely to be working in the commercial world for much longer.
- Unleashing True Creativity: AI excels at synthesising existing knowledge. But to truly innovate, to solve novel problems in elegant ways, still requires human ingenuity and a profound grasp of the underlying tools.
- The Sheer Satisfaction: There’s a unique, almost meditative satisfaction in building something functional and elegant with our own hands (and mind). It’s the same joy a woodworker gets from shaping timber, or a musician gets from mastering a piece. The process itself is rewarding.
- Maintaining Intellectual Agility: Engaging with the logic and syntax of a language keeps the mind sharp. It’s a mental workout that’s hard to replicate.
So, as I look ahead, I’m not just thinking about what I can build with Python, but the process of learning it again. It’s about reclaiming that early joy of creation, that pure problem-solving thrill, and experiencing the satisfaction of mastering a craft. The world of programming is changing dramatically, but the fundamental appeal of creating something with code, for code’s sake, remains as compelling as ever. And for enthusiasts, that “retro-style” approach might just be the most fulfilling path of all.
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