You are absolutely right that using natural language to specify problem means LLM has to guess a bunch of things. And obviously the guesses are not fully accura

You are absolutely right that using natural language to specify problem means LLM has to guess a bunch of things. And obviously the guesses are not fully accurate. So we go back and forth. But guess what, it gets 80/100 (if not more) assumptions right in a typical code problem. Majority of them boilerplate code assumptions. Thus you end up focusing on just the most important decisions and the LLM acts as a companion to you in a way a pair programmer does. Thus the ambiguity of the language is what benefits the system here. The power of LLMs is the fact that they use natural language. It’s like bashing on pipe based string processing that enabled all the Unix applications in the beginning. The simplicity of the system is what powers the entire thing. You cant take it away.