My point was just that neither company's engineers has the necessary knowledge to make any meaningful assessment of the other company's architecture and codebases. Both sides are the result of years of iterations to address very unique problems.
Also - Let's not act like Twitter is absurdly complex. Handling that amount of traffic was hard in 2008, yes. It's not hard in 2022. The app itself is what? CRUD with stream processing? Some complexity with scaling that, but it's not self-driving... that's for damn sure. Even if they haven't reached L5 yet, L4 AV is an infinitely harder problem than storing arbitrary text/images and serving ads.
It is but it's a different problem. Solving Fermat's last theorem is an infinitely harder problem than, say, speedrunning Minecraft in under 13 minutes but you won't see Sir Andrew Wiles doing the latter - because they are different skillsets.
edit: No idea why I typed Simon Wiles, I know full well his name is Sir Andrew!
VERY few developers are at this level, though. Most (>99%) are stuck in some paradigm associated with their typical tasks.
Tesla engineers working on AI have their own domain specific knowledge they likely spent many years to get a PhD for. The same goes for Twitter engineers working on natural language understanding AI to detect certain types of posts. By your logic there is just one broad category of AI researcher and they're all the same and have the same expertise. Scratch that.. there's just one broad category of computer engineer and they're all the same and have the same expertise. Twitter or Tesla engineers could easily do a code review of Space X's code base right?
All the codebases will look like they were created by an undergrad CS major and then have accumulated 16 years of edge conditions. And if you pull it all down and try to rewrite it because it is all overly complicated and everyone who built it was wrong: https://fs.blog/chestertons-fence/