Why I Think You’re Wrong About the Future of Code

The past few months have been a mental rollercoaster. One moment I am staring at my screen thinking, wow. The next moment I am asking myself, what am I going to do if this keeps accelerating at this pace? Underneath that oscillation sits a deeper question that has nothing to do with frameworks or models. It is a question about worth. About identity. About what defines us in a world where code is no longer scarce.

If you work in software, you can feel it. The ground is moving, and I think many experts in our field are misreading the direction, or at least are still clinging on to something, even though they don't have to.

From Tech Demo to Default

A few months ago, the dominant narrative was comfortable. AI is good for proof of concepts. Nice for MVPs. Fine for prototypes. Not ready for production. It produces messy code. It hallucinates. It cannot reason about complex systems. It will assist developers, not replace programming.

I understand that position. I mostly held it myself.

But if you zoom out and look at the rate of progress rather than the current snapshot, the conclusion changes. What was a toy last year became useful this year. What was useful three months ago is now capable of shipping real systems. What required heavy supervision is increasingly autonomous.

We judge AI by today’s output quality and forget that production code written by humans is far from perfect. Most real world systems are full of compromises, technical debt, and silent bugs. We act as if human written code is some gold standard of purity. It is not. It is a messy artifact of deadlines, context switching, and evolving requirements.

If the trend continues, and all evidence suggests it will, AI generated code will not stay in the prototype phase. It will become the default. Not because it is flawless, but because it is fast, cheap, and improving at a rate no individual engineer can match.

Dismissing that possibility feels less like critical thinking and more like denial.

My Own Journey: From Assistance to Replacement

In 2024, I replaced the entire software stack of my property management system without writing code in the traditional sense. No IDE. No manual architecture sessions. Just intent, iteration, and orchestration through AI.

Last week, I deleted all my IDEs.

That sentence would have sounded absurd to me two years ago. My editor was a vital instrument of my craft. Removing it felt almost symbolic, like stepping away from an identity I had carried for years, and yet, the output increased.

We guided someone with no prior coding background to ship a production-ready application. Not a toy project. Not a tutorial clone. A real app used by real users. Another friend, a domain expert with twenty years of experience but constant friction turning ideas into software, built his own application using an AI agent. Something that had been stuck in his head for years became real in days.

These are not isolated magic tricks. They are signals.

Builders Were Never Just Coders

Here is the part that feels important.

I was always decent at programming. Maybe even good. But I never fully identified as a programmer in the romantic sense. As a kid, I did not build the Lego sets. My friends built the spaceship. I played with it. I imagined the story. I extended the universe in my head.

Looking back, that says something.

Builders are not defined by syntax. They are defined by problems they choose to solve. By the worlds they want to create. By the courage to ship something imperfect into reality.

The crazy ones. The misfits. The ones who see what could exist and cannot let it go. That old Apple narrative still resonates because it points to something deeper than tooling. It points to agency.

If AI writes the code, it does not remove the builder. It amplifies the builder. It removes friction between idea and execution. It is a new abstraction layer.

Martin Fowler once described software development as a constant movement to higher levels of abstraction. We moved from machine code to assembly, from assembly to higher level languages, from manual servers to cloud infrastructure. Each step felt threatening to someone. Each step removed a layer of manual control. Each step unlocked more possibility.

This is the same pattern, just faster and more visceral.

Where I Think the Experts Are Wrong

The common argument goes like this. AI will assist, but it will not replace programming as a whole. We will still need engineers to design, review, and maintain systems. Production is too complex. Edge cases are too subtle.

That argument assumes the future will look like today, just slightly improved.

What if that assumption is wrong?

What if “programming” as an activity shifts from writing functions to defining intent, constraints, and outcomes? What if the scarce skill is no longer typing correct syntax, but asking the right questions and shaping the right systems? What if debugging becomes less about stepping through code and more about steering intelligent agents?

Yes, today’s agents still make mistakes. But so do junior developers. So do seniors. The difference is that AI systems improve globally. When the model gets better, everyone benefits instantly.

The belief that this will remain a side tool feels similar to early reactions to the internet or the cloud. Convenient. Useful. Not core. Until it was.

I might be wrong. I am open to that possibility. But ignoring the trajectory seems riskier than embracing it.

So What Defines Us Now?

This brings me back to worth.

If writing code is no longer rare, what is?

Judgment is rare. Taste is rare. The ability to understand a messy human problem and translate it into a coherent product is rare. The discipline to ship. The responsibility to own outcomes. The empathy to design for real people.

Intelligence, at least for me, is not raw problem solving speed. It is the ability to navigate ambiguity. To choose what not to build. To connect dots across domains. To hold long term vision while executing in the short term.

Even in a world of heavy automation, those qualities do not disappear. They become more important.

The engineer of the future may look less like a typist of logic and more like an orchestrator of capabilities. A conductor rather than a violinist. Still deeply technical, but focused on leverage rather than manual output.

More Creation, More Life

For those of us building lean software businesses, this shift is not just about productivity. It is about leverage in the truest sense.

If the distance between idea and working product shrinks, we can experiment more. We can validate faster. We can run profitable products without bloated teams or endless overtime. We can spend less time wrestling with implementation details and more time thinking clearly about direction.

That margin translates into something deeply practical. More time with family. More time training and staying fit. More time creating for the joy of it, not just to keep up with a backlog.

If we use this well, it is not about doing more work. It is about doing more meaningful work and reclaiming the rest of our lives.

The question is not whether AI will change software engineering. It already has. The question is whether we cling to a narrow definition of what makes us valuable.

We are moving to a higher abstraction. That can feel threatening if your identity is tied to the layer being abstracted away. It can feel liberating if your identity is tied to building.

I do not know exactly where this ends. None of us do, but the speed is real. The shift is real. And I would rather adapt early, rethink my definition of intelligence and value, and build with these new tools than defend a version of the craft that is quietly dissolving.

The future of code might not look like code at all. That does not diminish us as builders.

It challenges us to become better ones.