Not All Programming Languages Are Created Equal
The key to using AI productively in coding is knowing exactly where the contextual minefields are hidden before your AI coder blows up the entire project.
Of all the myths around AI and coding automation, this may be the most damaging:
AI will soon make developers unnecessary.
The logic sounds obvious. All programming languages collapse into one common abstraction, the LLM learns it, and humans get pushed out of the loop.
AI is already very good at writing the visible code, but it still sucks when it has to deal with what actually makes a real-world project work: the hidden structure of the programming language.
If you thought programming languages were just different syntaxes for the same thing, sorry, but you are wrong. Not all programming languages are created equal. Some hide layers of context, ownership, state, order and semantic rules that all have to remain correct at once.
Or, in plain words: the different contexts that even one simple line of code can carry with it make the myth completely false and the developer in the loop more necessary than ever… depending on the programming language. And once you see it, you will know exactly which group you are in.
Case in point: The C++ Nemesis
That AI can write C++ does not mean that it can build a reliable C++ project.
It can generate templates, write RAII, produce concepts, iterators, lambdas, move constructors, forwarding wrappers, allocators and concurrency code that looks frighteningly competent. Fine.
Yeah, we agree with the fearmongers here. Much of that visible code production is already being automated.
But don’t pop the AI champagne yet.
Because C++ has a nasty property that languages such as Go expose much less aggressively: the meaning of a line can depend on several interacting semantic contexts that are not visible in the line itself.
A piece of C++ can compile cleanly, pass superficial tests and still be wrong because correctness depends on something living several semantic layers away: name lookup, ADL, template dependence, overload resolution, concepts, value categories, object lifetime, ownership, concurrency, you name it.
And this is exactly where AI can screw up your entire project.
The problem is not that it cannot produce the syntax. The problem is that C++ can require something closer to
(code, nested contexts) → meaning
rather than simply
code → meaning.
Now you know where current AI sucks most: nested contexts, whether in C++ or in any other programming language that relies heavily on them.
And if you have read my articles before, this is another smoking gun for why we need a completely different kind of AI, built on a different mathematical foundation from the one we use today.
So the important point is simple:
The line of code is only the visible surface. The real semantics live underneath. And that is exactly where current AI sucks.
Why AI cannot understand what an average developer does without effort
This is the question that really matters to any developer, not just C++ developers, who feels threatened by automation.
An average developer, let alone a senior one, can look at a line of code and immediately recover much of the context surrounding it.
So what is so difficult for an AI about something you do almost routinely?
The animation below will look as familiar to you as the ABC of C++, but the same idea applies to any language with several nested contexts hiding behind even a single line of code.
This simple fact kills any AI coder. This is not a matter of more or less human supervision. The problem is that AI is blind to many of those nested contexts, as you will see in the examples coming next.