Well, a program is a series of tokens, and what is GPT-3 good at? Generating tokens. While that's oversimplifying, I feel like we're closer to automated programming than we realize.
Recently I wrote a python script to merge a bunch of videos with subtitle files using ffmpeg. It probably would have been faster to do it manually but I can imagine a world where telling GPT-5 to "Generate a python script that merges a folder of video files with subtitle files of the same name" is faster and more accessible than regular programming.
Yep. Its not hard to imagine mapping some description text to strictly deterministic operations like generating css/html for a front end, doing some definite data manipulation, or at the least, turning natural language description into an sql query.
Generating the tokens isn't he hard part. It's figuring out which tokens need to be generated in response to whatever solution needs to be coded. That's part communication, part comp sci and part artistic.
But if the system learned from enough previous examples, you may get a better, more cohesive, and artistic result. Though given the fact that Google can't filter obvious spam from my inbox, past performance is an indicator of future success.
Given how hard it is for humans to effectively communicate, im not sure we are so close. In essence, the hard part of most software is giving users something they want which is also correct.