Designing programming languages beyond AI comprehension
What characteristics should a programming language have in order to make automated analysis, replication, and learning by artificial intelligence systems difficult? Any idea?
A private blockchain is just a database.
Change capitalization of keywords based on filename length. If for odd length IF for even. iF for prime numbers.
variables named in English are strongly typed, variables in Spanish are weakly typed.
change symbols based on line absolute number. && on even lines AND on odd.
line terminators differ based on the number of consonants in the method name
every 5th consecutive line should begin with the symbol for comments unless there's a real comment more than 10 lines above but less than 23.
closing brackets are left brackets when the file-size is over 3k
switch assignment evaluation left vs right based on folder depth.
all conditions that an IDE could handle in a rote, calculated way real-time but would probably make the training data nonsensical. An LLM might produce the code based on language features but likely will never get the syntax right making any LLM output largely useless.
I'd make that so it's on even significant lines of code.
So you can't just leave a blank line to leave the rest of the file syntactically correct.
And of course enforce no braces on single line bodies, and enforce the first brace to be on the next line as the if/for/whatever statement (so that the parity of the SLOC number changes if a single statement body turns into a two statement body)
If that pattern is figured out, im sure it can be used to train an LLM to 'comprehend' that programming language. Think of it like designing a cipher or a puzzle; you can create a very complex cipher that is understood only by you or those you choose to share it with. But if the 'trick' is revealed, then the entire cipher is broken.