Hacker News new | past | comments | ask | show | jobs | submit
thundergolfer | on: Uber's $1,500/month AI limit is a useful signal for AI tool pricing
> That means each employee's AI spending cap is ~11% of that median compensation package.

Probably better to use the fully-loaded cost of the engineer, which is much higher than their compensation package. The fully-loaded cost is the total cost paid for the labor power of the engineer, and it includes big ticket items such as office space, food, equipment, insurance, payroll tax, fringe benefits, recruiting costs.

If the median compensation package is $330k/year then the median fully loaded cost is probably around $450-500k.

munk-a | parent | next
My usual rule of thumb for the US is north of double the received compensation but something in that range sounds reasonable with such high compensation. It's actually really interesting and underappreciated how that fully-loaded cost varies from country to country. Canada (for most salary ranges) is about half again instead of double owing to the insurance portion coming out of income tax rather than being a hidden expense so Vancouver ends up being attractive for trading 160k USD for like 120k CAD in compensation and then also lowering overhead from 100k USD down to like 60k CAD. The savings can be extremely dramatic.
hansvm | root | parent
Why would double be a good rule of thumb for typical US SWEs? Most of the costs aren't proportional to salary, and the ones which are aren't anywhere approaching 50%, much less double.
loading story #48392438
loading story #48392570
newsoftheday | parent | next
> $330k/year

For a traditional software engineer? I retired last year after 3 decades and my salary was about the same as it was in the early 2000's at the last company I was at. Maybe I should have negotiated more but I thought only FAANG paid traditional pre-AI engineers more than $250K.

simplyluke | root | parent | next
Uber's comp packages are probably right in line with that. Tech salaries are trimodal, and uber's right in line with the big public tech companies.

https://newsletter.pragmaticengineer.com/p/trimodal

closeparen | root | parent | next
There is a tier just outside of FAANG that pays similarly or better, prominent examples being Uber, Airbnb, Stripe, Block, Databricks, Datadog, Pinterest, Snowflake, etc.
nicebyte | root | parent
250k for base pay is about in line with median I'd say.

If 250k was the total comp (taking into account bonus/stocks/what have you) then yeah, you definitely should have negotiated.

stingraycharles | parent | next
I’ve even heard the rule “twice the salary” being used here in EU, but the tax and insurance burden may be higher. All kinds of those are based primarily on total payroll amount.
consp | root | parent | next
That number usually includes cost of habitat and others. It's also a stupid number as it is skewed by how much you can squeeze out of your employees. A better number would be to compare it vs revenue per capita.
spacemanspiffii | parent | next
It is also possible that capping at $1500 will give you ~99% of the benefits. So even with gains that are much higher, a cap could be a rational decision. Also, most decisions, especially around AI aren't exactly rational, so I wouldn't read to much into this number.
notnullorvoid | parent | next
Both metrics are valuable.

If one uses AI minimally and is able to out perform peers who are maxing out AI spend, one might want to use that in salary negotiations.

ransom1538 | parent | next
"$330k/year" Lol. I thought I clicked on hacker news 2022.
barumrho | root | parent | next
Is it too high or too low? Honestly cannot tell
random__duck | root | parent
Quoting the article : > Levels.fyi lists the median yearly compensation package for Uber software engineers in the USA at $330,000.
stego-tech | parent
It’s also worth noting that’s the peak benefit. Expect most engineers to not hit those limits on the regular (if at all, since limiting this puts skills in focus again), and that limit to come down over time as the easy processes are automated and humans are re-tasked with harder problems relative to their TC.

This is not a good bellwether for the AI industry, including its adherents. Their growth assumed a level of indispensability that’s not being reflected in hard numbers and real costs, which lends credence to the notion that these IPOs being fast-tracked are meant to try and cash out before the bubble really pops in earnest. There’s no way consuming enterprises are going to pay such insane costs for such minimal uplift in the long run, and the AI companies can’t keep offering subsidized tokens via subscription plans at their current pricing.