It's more complicated then that.
For example the right decisions in a small company vs. FANG is often quite different, potentially outright the opposite. Not just because of differences in people, time and money resources but also due to scale.
Like you spending a day or even week to optimize something to be a bit faster can save millions in just a year if used on the scale of google. But in a startup the pure salary cost of spending a day on it can easily be more then it saves in 5 years. And due to the small number of time and human resources the actual cost can easily be much higher.
You can see this in some of the design decisions around open source tooling from FANG companies. They are often designed for a context of: "Many highly qualified people working at the same time at the same project. And micro optimizations being important."
But what smaller companies have is: "A small group of very mixed qualified people working one it. Rarely more then very small number at the same time on the same component. Most micro optimizations being clearly out of scope. Constantly chasing a schedule where a single larger delay can be a catastrophe for the company."
For example for a FANK company breaking changes on internal APIs are often a no go, but for small companies they can often be a no brainier especially if it doesn't involve any migration complications.
Or for example for Google a single service stopping is often worse then it running amok and creating a mess, for a small company which might only provide one or two services such a mess can mean insolvency, but an outage might not.
Or for example in a small company having a repo where you define all the (internal & external) APIs and use it to generate glue code to bind all your services together in a "type safe" manner can be a grate thing to have (if you have the right tooling). For a FANG company where not just many people but many teams might work on code interacting with the same overlapping APIs this isn't a viable approach at all.