And side note on your last point - I've been burned too many times by confident hallucinations to trust my foundational learning to GPT. I hope someday that will improve, but for now ChatGPT is as trustworthy as an evening chat with someone at the bar.
... Someone who has been drinking since happy hour.
If you'd like a trustworthy overview, the book Designing Data-Intensive Applications by Martin Kleppmann is a classic. I really hope we get an updated version, but the fundamentals all still hold anyway.
I read it a few months ago and was really impressed with how easy it was to read.
It starts out with simple stuff, like serialising data as JSON vs XML. But it moves into complex areas - like how replication and WALs work, including different ways of handling consensus when using leader-leader replication and how Spanner needs atomic clocks to handle it.
But even the complex stuff was explained in a way that I understood, which is an immense achievement.
Yep, this is my number 1 "I wish I'd read this X years ago" book.
I'm someone who has been doing this stuff for almost two decades without really knowing this is what I'm doing. I used to think what I was going to do was systems level programming like operating systems and maybe the database systems themselves (e.g. postgres, datomic etc.). But for whatever reason my entire career (so far, but I don't see it changing) has been building data systems for businesses and users.
I read the book from cover to cover and half of it was like "ohh... that's how that works, that's what I'm doing wrong" and the other half was "shit, this is something I kinda knew after trying and failing for years, and someone has just written it down in a way I never could".
> You might be surprised to learn that I actually think LLMs have the potential to be not only fun but genuinely useful. “Show me some bullshit that would be typical in this context” can be a genuinely helpful question to have answered, in code and in natural language — for brainstorming, for seeing common conventions in an unfamiliar context, for having something crappy to react to.
> Alas, that does not remotely resemble how people are pitching this technology.
And side note on your last point - I've been burned too many times by confident hallucinations to trust my foundational learning to GPT. I hope someday that will improve, but for now ChatGPT is as trustworthy as an evening chat with someone at the bar.
... Someone who has been drinking since happy hour.