Comment by wiz21c

> The goal is to build digital “twins” of the experts on how they debug, architect, and maintain these systems in practice.

Sounds great but... I have migrated a big cobol codebase several years ago. Knowledge stored in the experts is 1/ very wide 2/ full of special cases that pop up only a few times in a year 3/ are usually complex cases involving analysing data, files which are on paper, etc. I strongly doubt an AI will be able to spot that.

The knowledge that usually misses the most is not "how is that done", because spending a few hours on COBOL code is frankly not that hard. What misses is: "why". And that is usually stored in laws, sub-sub-laws, etc. You'll have to ingest the code and the law and pray the AI can match them.

So in the end the AI will make probably 50% of the effort but then you'll need 150% to understand the AI job... So not sure it balances well.

But if it works, well, that's cool because re-writing cobol code is not exactly funny: devs don't want to do it, customers do it because they have to (and not because it'll bring additional value) and the best outcome possible is the customer saysing to you "okay, we paid you 2mio and the new system does the same things as before we started" (the most likely outcome, which I faced, is "you rewrote the system and its worse than before). So if an I can do it, well, cool.

(but then it means you'll fire the team who does the migration which, althgouhg is not funny and not rocket science, requires real expertise; it's not grunt work at all)