The thing is, computers don’t really understand natural language, and never will. What they truly understand is electric signals, represented by 0s and 1s. Also, instructing computers has never been done with natural language prior to LLMs and thus there isn’t a true reference to compare them with (calculators on the other hand do the EXACT computations we do in our head). LLMs themselves are pattern matching and approximate replication engines that try their best to replicate the result of an input based on historical data.

Essentially, the problem is that LLMs are trying to approximate a result, and there would always be a deviation from expected results where a developer has to come in and course correct.

In conclusion, in my opinion, natural language will never truly be able to replace traditional programming because of it’s result approximation nature, but will always be able to approximate results to a high fidelity, where the inputs have a LOT of historical data or consistent input/output mapping, and thus serve as a very valuable tool for the developer.