That's a really powerful approach because LLMs are very very strong at what is basically "style transfer". Much better than they are at writing code from scratch. One of my most recent big AI wins was going the other way; I had to read some Mulesoft code in its native storage format, which is some fairly nasty XML encoding scheme, mixed with code, mixed with other weird things, but asking the AI to just "turn this into psuedocode" was quite successful. Also very good at language-to-language transfer. Not perfect but much better than doing it by hand. It's still important to validate the transfer, it does get a thing or two wrong per every few dozen lines, but it's still way faster than doing it from scratch and good enough to work with if you've got testing.