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Comment by thelean12 | Hacker News Reader

Sure, there's always going to be bloat, but complexity at scale isn't just because there are a lot of employees.

Twitter is a great example. I bet they have 20+ people working on a specific anti-abuse system. Another 20+ working on a specific ad type that makes the company money. Another team that just works on account security. Another team that works on internal tooling. Or the shared UI components team. Etc until you get the current state of Twitter.

All of those teams don't need to exist when Twitter is small, but do when they scale.

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We can definitely agree that as a company grows, it needs more employees. I think the point at issue is that there is such thing as having too many employees. There are multiple opposing forces in tension here, and the tricky part is striking the right balance. I think that GP was trying to say that they hired too many people, and introduced complexity.

A layoff is certainly a sign that they hired too much, I agree.

I was going off what I figured the poster was getting at: they don't understand how Uber has even 80% of their employees.

Is that what they were getting at? It seems to me like you made up that 80% number just now, to prove your point.

I think you forgot what thread you're in.

Uber is discussing laying off 20% of employees. 100 - 20 = 80.

It's completely reasonable to assume the OP was trying to figure out how they have so many employees, even after the layoffs.

But it's not about employees. It's about capabilities, and working backwards.

eg look at datastores. If you can fit your data in postgres on a single (potentially really expensive!) computer, you probably need two or three of those computers for a primary plus a couple replicas and a DBA.

Once you outgrow that, going distributed costs a team. There is a big elbow in the cost and headcount curve.

Once you want a different specific capability beyond the standard distributed datastores, that costs multiple teams. Yet another big elbow in the cost and headcount curve.

This happens on data stores, applications, translations, currency, etc etc etc. Imagine a Greek person with a Greek bank account driving Uber in France being paid with an American amex card.

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