How can you not get that? Do you believe LLMs remember what you show them between calls? That's not how they work. Each call starts from a clean slate, you have to re-describe the new language each and every call. There's no way to get around that. They are not magic. They do not learn from your prompts, which have absolutely no effect on the model itself.
If you think they do, you are falling for an illusion. ChatGPT is appending each of your incremental prompts to the full prompt, and it grows and grows longer and longer every time you add something. Sure, it summarizes when the full prompt gets to long, but that makes it distort and forget your language definition, and you have to add it again. If you give it the prompt to generate the language from scratch each time instead of the generated language itself, it generates a different language every time. You can't "cleverly hack" or "wish" your way out of that.
They may be good at generating new languages, but one thing that LLMs aren't good at apparently is warning you it's futile to generate a new language intended for llms to program instead of just using existing languages. They just play along and do ridiculous useless things out of syncophancy.
Do you propose just ask AI to generate orchestration in Python?
Design programming languages for humans first. If they're good enough to catch on, and people write lots of code in them, ask and answer lots of questions about them, write tutorial and have hacker news discussions about them, then they will naturally and eventually end up in the training data, and the models will know about them. Problem solved.
It's ridiculous and costly to design a language for LLMs but not humans to use, and then necessarily and repeatedly insert the entire language definition and examples into every single prompt, instead of building it into the model. It's a tragic waste of electricity and money, and has a huge carbon footprint. Why isn't this obvious?