The fundamental problem is that any language designed for humans to write and understand is, by definition, learnable by systems trained on human-written code.

The approaches suggested here (context-dependent syntax, position-based keywords, etc.) don't make a language "unlearnable" - they just make it require more training data. An LLM that's seen enough examples of your filename-length-dependent IF/If/iF keywords will learn the pattern just fine. You've increased the Kolmogorov complexity of the spec, but not made it incomprehensible.

The only way to truly prevent AI comprehension is to make the language incomprehensible to humans too. Which defeats the purpose.

A more pragmatic question: what problem are you trying to solve? If it's "prevent AI from writing code in my language," that's unwinnable - any pattern a human can learn, a sufficiently large model can learn. If it's "make codebases harder to reverse engineer," you want obfuscation not language design. If it's "preserve human jobs," the bottleneck isn't whether AI can write code - it's whether AI can figure out what code to write in the first place.