The Evolution of Programming: Why AI Won't Replace Developers
25 Feb 2026Lately, it feels like doom-mongering is everywhere you look: “In six months, 90% of code will be written by AI!” or “The software engineering profession is dead!” If you take these claims at face value, it definitely sounds scary. But let’s take a deep breath and separate the hype from reality.
Is it true that AI is going to type 90% (or even 100%) of the code? Oh, absolutely. But does that mean it’s going to actually write it for us? Like, design the architecture, figure out the business logic, and solve the real problems? That’s complete nonsense.
Sure, we’re not going to be furiously mashing our keyboards anymore just to hammer out endless lines of boilerplate. But make no mistake—this isn’t the end of programming. It’s just the next step in an evolution we’ve already been through.

From Assembly to Prompts: History Repeats Itself
Think back to the shift from assembly to high-level languages. Back in the day, developers were literally writing machine code by hand. Then the first abstractions rolled in. For a while, there was this messy dance between assembly code and early high-level languages. But eventually, the need to tinker down at the “bare metal” level just vanished. We got interpreted languages, massive frameworks, and beastly IDEs.
Did we stop programming because of all that? Nope. Did the number of developers drop? Actually, the exact opposite happened! The higher your level of abstraction, the cheaper and faster it becomes to build software. And when software gets cheaper and faster to build, businesses just demand more of it. Which means we need more code, and a whole lot more developers to architect it all.
Right now, we’re sitting at that exact same crossroads. Except this time, instead of jumping from C to Python, we’re leaping from rigid syntax to plain, natural language.

Death of Syntax, Long Live the Logic!
Up until now, the biggest roadblock between the software idea in a someone’s head and an MVP of the actual product was the syntax and the technical implementation and deployment details. You had to memorize exactly where the semicolons went, precisely how to declare every class, and which flavor of brackets to use. You had to be a technician, one that has to be very precise with the implementation details, not just an architect of the solution.
What’s happening right now with LLMs and its break neck speed of development is that we’re bulldozing that roadblock. You just don’t need to memorize syntax anymore. You get to just dictate your thoughts. It is very helpful to have a good understanding of the fundamentals. Sure, right now we still have to jump in and manually massage the generated code every so often. But give it a year, two, or three, and that awkward back-and-forth will be mostly a thing of the past. We’ll literally just be speaking our architecture and logic into existence.
The developer of the future isn’t the person typing 120 words per minute. It’s the thinker, the engineer, the architect—the person who can formulate their ideas with crystal clarity and give precise instructions to the machines. We’re about to have a lot more code, and it’s going to get much more complex.
Many studies have shown that the majority of software developer’s time roughly 90% is spent on reading code, not writing new code. With LLMs taking care of the syntax and boilerplate, developers will be freed up to focus on the higher-level abstractions, logic and design.
In line with the Jevons Paradox, the more efficient and cheaper something becomes, the more we end up using it. So as it becomes easier and faster to generate code, we’re going to see an explosion in the amount of software being created. And with that explosion comes a need for more developers to manage and maintain all that new code.
So as the amount and complexity of software grows, the need for skilled “developers” (we might be calling them “software architects” or “logic engineers”) to manage and maintain that code will only increase. The demand for such people is not going to decrease; it’s going to skyrocket.
This means we’ll need more developers than ever before to manage and maintain all this new code. But what kind of developers? The ones who can think critically, design robust architectures, and solve complex problems. The ones who can communicate their ideas clearly and work effectively with AI tools.
Fundamentals Still Matter (more than ever)
I think this puts the emphasis on fundamentals of computer science back. You can always ask the AI assistant to suggest/explain algorithms, data structures, and design patterns. But you need to understand those concepts yourself to be able to effectively plan ahead and hold the mental model of the system in your head. You need to be able to understand the trade-offs and make informed decisions about which approach to take. But I digress. Perhaps this is a topic for another post.
The age of syntax is coming to an end. The age of logic and architecture is just beginning. And I am excited to see where it takes us and how we can push the boundaries of what’s possible with software.

