alt Hacker NewsWho is more impactful, the startup engineer who singlehandedly ships a feature that increases a startup revenue by 25% off a base $5M/yr ($1M extra rev), or a Meta/Google team of 5 engineers who ship a .01% revenue improve off a base of 150B/yr (15M/5 = $3M/engineer).
As an engineer you are thinking about impact as 'scope' or 'features'. Leadership will be thinking marginally on what adding a net new engineer will provide to the business.
“Marginalism is the economic doctrine that we can best understand value by considering the question of how many units of a good or service an individual has, and using that starting point to ask how much an additional – or marginal – unit would be worth in terms of other goods and services.”
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A lot of rationalization for what is fundamentally just market inefficiency: economies of scale and network effects (aka Monopoly).
Remove Google's monopoly level distribution, and then build that feature and tell me how much revenue it generates.
The value is in the monopoly which was formed by the founders and all the early employees by having the right products at the right time decades ago, not in the "upgrade now" button some worker bee added to Gmail in year 25 of the company.
Yes, that "upgrade now" button probably does generate $100M in revenue per year. But the reason why isn't because of some unique engineering talent on behalf of the worker bee.
They just pay that dude so much because activist investors don't scrutinize costs too aggressively on growing monopolies (wait until revenue growth stops) and they value stability. If you don't value stability to the same degree (you aren't a massive 200K employee org), I wouldn't hire the "upgrade now" button guy.
If some engineer optimizes something in the Google search stack that makes it, on average, just 0.01% faster (not 1%, but one-one-hundredth of a percent), then they have paid their salary for the entire year. Almost in perpetuity. No matter what level they are.
Very small gains multiplied out over extremely large amounts of compute over large amounts of time add up big.
And that's why Google can spend so much money on fairly small scoped teams.