The New Programming Language is Clarity

One evening, while preparing lesson plans and coding exercises for my students, a profound question struck me: "Isn't AI making all of this meaningless?" This wasn't a casual thought; it came from someone who spends their professional life as an AI expert, helping developers integrate these very tools into their workflows. I've witnessed AI evolve from simple autocomplete to sophisticated systems, and I use them daily. Yet, seeing entire functions and features generated from a few descriptive sentences made me wonder if the craft I loved and taught was becoming irrelevant.

The Magic of Early Programming

Programming has been a significant part of my identity for most of my life, and teaching it is a core part of my purpose. My thoughts drifted back to the beginning, to 1987, when I received my first computer, a Commodore C 128. By today's standards, it was rudimentary, but it was a gateway. I spent hours typing code from magazines, line by painstaking line. Most of the time, a single typo would render the program useless. But when it worked – when a simple game or a pattern appeared on screen – it felt like magic.

I remember the pride I felt after writing my first nested loop to draw patterns. I showed it to everyone. I even demonstrated my program on display computers at an electronics store, impressing salespeople and encouraging parents to buy machines for their children, framing programming as the key to the future. Back then, programming felt like music. I'd imagine something, translate it into code, and the pixels on the screen were my symphony. It was about expression, experience, and turning ideas into reality. I knew then that this was what I wanted to do for the rest of my life.

The "Programming is Dead" Narrative

Fast forward to today, and the sentiment is pervasive: "Programming is dead." People say it with excitement, relief, and even pride, believing AI now writes code based on simple descriptions. While technically true that AI can generate code, the real issue is that it's removing the very aspect many of us fell in love with. Experienced developers, who chose this path for the joy of building, now question their role. If a machine can perform a core task better, what's left for them?

This isn't just fear of technology; it's grief. Imagine a carpenter who cherishes the feel of wood, the smell, the act of shaping it. Now imagine a robot that can do the same work faster and more precisely. The carpenter could learn to program the robot, but something essential – the process itself – would be lost. This is the struggle many developers face today, and it's terrifying for educators. If machines can generate entire systems, what are we preparing our students for?

Redefining the Developer's Role

On that reflective evening, I realized the contradiction. I work with AI daily and, surprisingly, I don't feel fear or grief. Instead, I'm having more fun developing software than I have in years. The headlines suggested I should feel obsolete, replaced. But working with AI, I feel powerful. The distance between an idea and its realization has drastically shortened.

This feeling reminds me of my teenage years. A few lines of code could create something amazing, not because the code was perfect, but because I had made something happen. It was the first time I experienced "self-efficacy" – the belief that my ideas could change reality. Decades later, working with AI, I feel that again. An idea in my mind is brought to life faster, on a larger scale, with fewer barriers.

I realized I was never primarily in love with coding itself. I was in love with developing, building mental models, shaping ideas, and turning vague thoughts into tangible results. Code was merely a tool. This led to a crucial realization: I am not just a coder; I am a developer. Programming languages have always been abstractions, freeing us from low-level details. AI is simply another, albeit powerful, abstraction layer. It doesn't replace my role; it changes the level at which I operate. It expands my capabilities, allowing for bigger goals and more ambitious explorations. AI removes friction, not creativity.

The Enduring Value of Coding

While AI streamlines development, the love for coding persists. The mental challenge of describing something with precise syntax and semantics is something I don't want to lose. Coding isn't going to disappear. We still play chess, run, cycle, and sail, even though machines and engines are more efficient. Efficiency was never the sole point; experience was.

Coding will remain, not as the fastest path to software creation, but as a powerful method for cultivating specific thinking skills: precision, logic, and patience. It teaches the satisfaction of the computer doing exactly what you instructed. Perhaps one day, "handmade" software, valued for its intentionality rather than efficiency, will gain prominence.

Furthermore, AI makes mistakes. While these will decrease, they won't vanish. The final, critical percentages of accuracy are expensive and valuable. This is where individuals who deeply understand code become indispensable – for debugging, verification, and bridging the gap between near-correctness and actual correctness.

The Canary in the Coal Mine

My experience as a programmer is not unique; it's the first frontier. Programming is the initial profession where AI has challenged our perceived value. We are the canary in the coal mine, and the mine is now everywhere. Designers, writers, translators, lawyers, accountants, architects, and even doctors are facing similar existential questions as AI encroaches on their domains.

They are experiencing the same emotional journey: denial ("AI can't do that"), fear ("Maybe it can"), grief ("But I love doing that"), and, hopefully, redefinition ("What was I truly passionate about, and how can I continue doing that?"). The carpenter metaphor applies to every knowledge worker witnessing AI excel at their mastered craft.

Finding the Layer Above

The key lesson from being on the front lines is this: don't fight the tool; find the layer above it. For me, that layer was recognizing "I'm not just a coder, I'm a developer." For others, it might be "I'm not a pixel pusher, I'm a visual thinker," or "I'm not a sentence crafter, I'm a storyteller," or "I'm not a diagnosis machine, but a healer who understands context, fear, and hope."

Every profession must find its equivalent redefinition, forcing us to confront the essence of our work and identify what is truly irreplaceable. Programming led the way, but the rest of the world will follow.

The Evolution of Teaching

If my identity as a developer has evolved, so too must what I teach. Does learning coding without AI still make sense? Absolutely. We teach many subjects not for professional mastery but for how they shape our thinking. Not everyone who writes an essay becomes a professional writer, nor does everyone who learns calculus become a mathematician. Coding, like math, language, and music, builds a particular kind of thinking and can be part of a general education.

However, the method of teaching must change. With AI, natural language has become a programming interface.

Clarity: The New Programming Language

The thesis to remember is this: The new programming language is clarity. For years, programming was about translating ideas into syntax. Now, syntax is no longer the bottleneck; clarity is. Can you clearly describe what you want? Can you provide examples, set constraints, explain desired outcomes, and test results against your intent?

Communication is becoming a technical skill. Diagrams, examples, and shared understanding are paramount. Learning programming in 2026 means not only being able to write code but also to express intent so an AI can execute it. This principle extends beyond programming: clarity matters when lawyers use AI, designers prompt image generators, and managers delegate to AI agents. The skill of transforming a fuzzy idea into a precise specification, once a programmer's superpower, is now a universal requirement.

Conclusion

That evening on my desk, I stopped thinking of myself as someone who teaches syntax. I teach agency, clarity, and the craft of turning ideas into reality across abstraction layers. I still love coding, but it no longer defines my entire professional identity. The center has shifted, and that's okay. Because I'm not just a coder; I'm a developer. And my new programming language is clarity.