This made me laugh pretty hard, but it's basically my take too.
I'd pretty much go with the same thing. It's interesting to me, though, that people see Postgres as the "big database" and MySQL as the "hobby database." I basically see things as the exact opposite - Postgres is incredibly flexible, very nice to use, and these days, has fewer foot guns at small scale (IMO) than MySQL. It's more academically correct and it generally tends to "work better" at almost any achievable "normal" scale.
On the other hand, Postgres is full of pitfalls and becomes very difficult at exceptionally large scale (no, not "your startup got traction" scale). Postgres also doesn't offer nearly the same quality of documentation or recipes for large scale optimization.
Almost everything in the 2016 Uber article you link, which is a _great_ read, is still true to some extent with vanilla Postgres, although there are more proprietary scale-out options available now. Postgres simply has not been "hyper-scaled" to the extent that MySQL has and most massive globally sharded/replicated systems started as MySQL at some point.
For this same reason, you are likely to be able to hire a MySQL-family DBA with more experience at hyper-scale than a Postgres one.
With all that said, I still agree - I'd almost universally start with Postgres, with MySQL as a back-pocket scale-up-and-out option for specific very large use-cases that don't demand complex query execution or transactional workload properties. Unless you have an incredibly specific workload which is a very specific combination of heavy UPDATE and `SELECT * FROM x WHERE id=y`, Postgres will do better at any achievable scale you will find today.