AI can write code. Does that mean programming is dead?
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Goverdhan Jayaram
Chief Mentor & Founder, UXL Technology Academy · 30+ years in software engineering
My answer is: No— but I believe the reason for learning to program has fundamentally changed. In 2026, the value of a developer has shifted from being a “writer of syntax” to a “reviewer of logic” and an “architect of solutions.” I have watched this shift unfold over three decades, and it is the reason I built this programme.
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I use this analogy with every new student: the calculator's invention didn't make mathematicians obsolete — it just meant they no longer spent hours doing long division by hand. The thinking still requires a mathematician. AI is the calculator. You need to be the mathematician.
I have watched this shift happen in real time across three decades of working with software teams. Today, AI generates about 90% of boilerplate code — the repetitive, standard parts of an application. But in my experience, the developers who trust that output blindly are the ones who end up in trouble. Studies confirm what I see in practice: AI-generated code regularly contains serious problems:
23%
of AI-assisted code contains security vulnerabilities
1 in 5
AI suggestions contain factual or logical mistakes
100%
of "slopsquatted" packages go undetected without review
"Slopsquatting" is a new attack vector I warn every student about: AI occasionally suggests library packages that don't exist, which hackers then create to inject malicious code into your project. If you don't understand the programming language, you cannot peer-review the AI's output. You become a passenger in a car where the driver is 80% reliable — which, in my view, is a recipe for a crash.
In my view, we have entered an era of Absorption Capacity. Because AI can generate code instantly, the limit is no longer how fast we can type — it is how fast we can verify and integrate that code into a complex system. I teach my students to think in three layers:
Syntax
"The How" — AI handles this entirely
Semantics
"The What" — you must define what the code should do
Architecture
"The Why" — you decide how new code fits your system
I have worked with systems that are 16+ years old. AI cannot know their history, their constraints, the business rules, or the technical debt baked into them. Only the engineer who understands the system can make the architectural call. In my 30 years of practice, that judgment has always been the most valuable skill — and it is more valuable now than ever.
This is the argument I make to every student who asks me whether programming is still worth learning. The act of programming teaches three cognitive skills that no AI can replicate — because they require human judgment about the real world:
Decomposition
Breaking a massive business problem into tiny, logical steps
Edge Cases
Anticipating what happens when inputs, networks, or users behave unexpectedly
Debugging
The most critical skill in 2026 — AI generates more code to debug than ever before
Debugging is the example I return to constantly. AI ships code faster than any team can manually verify. The developer who can read, trace, and fix that code at speed is now the most valuable person in any engineering team. I built my entire curriculum around developing exactly that capability.
The New Skill Stack
How I see every role evolving
This is the transformation I prepare my students for. The old role descriptions are not gone — they have been compressed into a single expectation: you must now do all of this, faster, with AI as your co-pilot.
Level
Old Role (Pre-AI)
New Role (2026+)
Junior
Writing basic functions and loops
Prompting AI and verifying small units of code
Mid-Level
Building features from scratch
Orchestrating multiple AI tools to build complex modules
Senior
System architecture and mentoring
High-level system design, security, and AI Governance
My conclusion
AI raises both the floor and the ceiling of programming.
Anyone can now write a basic script. But to build professional, secure, and scalable software, you need a deeper understanding of programming fundamentals than ever before. The floor is higher — and so is the ceiling. That is precisely why I built this programme, and why I am selective about who I admit to it.
I teach the 10% that AI cannot replace. Here is how to apply.
