I am yet to see that ‘companies with great ideas which simply cannot afford those very expensive developers’. For the most, issue is not programmer costs. Mostly it’s inability to formulate the MVP which makes sense. ‘uber for my industry’ is not a sensible business strategy Honestly, if you know guys whose bottleneck is pure software dev — please let me know, I have a good, experienced team in Eastern Europe, we can do wonders in product development. But coming up with sensible business ideas and executing on them in the real world is crazy hard and extremely rare.

Not if you account for labour.

> more work for the user Model routers allow this to happen automatically without any more work by the user. > a shittier model A ton of tasks don't require the most expensive frontier models, etc. > I’m not sure why anyone does it 1. Faster solutions from the LLM - also reduces employee costs of having the employee waiting on the LLM 2. Avoiding things like the half-billion dollar per month bill for a single company’s LLM use recently reported in Axios

It's pretty simple; organizations are willing to tolerate paying $1500/month/engineer, which seems to be roughly inline with "normal" consumption for most full-time engineers. If that number grows significantly, then I bet companies will start exploring flash models more, as you propose.

> 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.

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.

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.

The costs to hire management and "support staff" like TPMs that scale with SWEs that help them meet goals is proportional to SWEs - often that is taken for the higher end fully loaded costs, depending on how you define it. Office space in downtown SF, Mountain View, or Palo Alto costs more than office space for back office workers in Nashville or Utah. Firms that hire SWEs often have fringe benefits like free food etc. and while they may apply to all workers, it tends to go along with hiring lots of SWEs. But yeah, double is insane. When I saw prices for COBRA from Facebook, it was $3300 a month, and that was god-tier insurance - the insurance benefits were so good they had a custom list of what was covered that was probably way better than anything available on the market (e.g. you want brand name drugs? no problem. You don't want to try both ambien and trazadone before taking a sleep medication doctors actually recommend? No problem - etc.) - but for my needs it was barely better than COBRA costing way less than half. $3300/mo, or even $1200/mo for an entry level ops worker is a lot of their salary, and probably where the double comes from. At SWE compensation most of it ceases to scale. The fully loaded costs including proportional management costs isn't relevant to the true marginal engineer, but estimates I've gotten from higher-ups definitely factor into engineering decisions about "should we spend engineering time to save money/make more money - how much will doing this thing cost the company" (opportunity costs are also relevant, but usually less grounded, since most projects don't have concrete benefits like "we will save $x/yr in infra costs")

While the fully burdened cost of an engineer being double his salary sounds suspicious, this is indeed broadly the case. It has been (sometimes significantly) more than double in the case in every US employer where I worked and where I saw both numbers. In one case it was a hair under 3x. My experience was not with pure software houses; we had some labs, measurement and RF equipment, but even without the hardware component the offices, insurance, admin expenses, HR, janitors, conference travel and so on would easily bump the total employee cost to double the salary. My 2c.

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.

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.

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.

"$330k/year" Lol. I thought I clicked on hacker news 2022.

Is it too high or too low? Honestly cannot tell

Quoting the article : > Levels.fyi lists the median yearly compensation package for Uber software engineers in the USA at $330,000.

> Because companies are betting that this spending will allow them to reduce cost by firing people. I've never worked at a company that didn't have a technical backlog measured in years.

If they don't hire to get it done it means they don't think it's really important to get it done.

Uber cutting back to ~$1,500/engineer/tool/month makes it look to me like they think there's at least $1,500 of monthly ROI to be had per engineer.

1500/Mo per engineer is such a small price considering the base salary of these employees, Maybe Uber knows something we don't (the 5X engineering ROI isn't there for them?). Judging the ROI of an engineer is hard. Adding AI on top of that makes things worse, I think. I've heard AI makes engineers 3X, 5X, 10X and even 100X. If I told my CEO that I was 4X more effective with AI, I am doubtful he would be willing to spend even 1X my salary on tokens. Even though he would be making out in the end. At some point the ROI is pretty much vibes, man.

So touche, but since it's usage per task it's kind of weird. This means that the average engineer is efficient at (say) identifying the first 10 tasks they should do but there are diminishing returns after that? That seems like a weird pattern. Wouldn't it be more likely that certain tasks have a ROI based on how efficient the task is generated? Like I'm trying to imagine in my head, if you think an engineer is more efficient with the tool, why deny them more tokens. I guess so they think to use them more efficiently? So, maybe I conclude that I think your conclusion that there must be $1500 per engineer is flawed. And even if it were true, I don't think the benefit would be evenly distributed. I suspect this is a first pass at figuring how to budget them and there will be a second pass. While it certainly reeks of motivated reasoning, Jensen Huang assertion that an expensive engineer should be using at least their salary in tokens feels more logically sound to me (assuming the average engineer is efficient at using tokens, I have a feeling it's a normal distribution)

> The question you always have to ask is what problems does it directly solve Most directly, human labour. Labour is always a problem for capital. At a certain level of AI competence, businesses don't need to pay humans to complete the work they need doing in order to operate. I don't think anyone would dispute AI competence isn't growing steadily.

There's some software that can cost $1k or more per seat/month, but it's pretty rare. Big tier ERPs usually fall in the ~$600/seat/moth range, specialty engineering stuff can hit over $1k, Bloomberg terminal, etc. I wonder if what Uber's building with that $1.5k/month/employee is actually delivering the same value that something like an ERP would to the entire org...

Plenty of comparisons here between salaries and token costs. All fair but very much assumes that salaries are rational. Why do we pay some engineers 10x as much for the same role just because they are in a different location? The WFH discussion surfaced some of that. If money is cheap, all sorts of funny things are happening. Is it worth to spend 1500 USD on AI? I don’t know. Is it worth paying engineers 300k USD instead of 30k? Honestly, I don’t know

> All fair but very much assumes that salaries are rational. Why do we pay some engineers 10x as much for the same role just because they are in a different location? Who's this "we" you're talking about? Are you a software engineer or a temporarily embarrassed billionaire? Do you think the rational thing is to pay the lowest regional salary worldwide?

As well as rational vs irrational they are also just different types of spending. Hiring someone vs paying a vendor for a service: - different level of commitment - might tie your org to a physical location - different legal risks - shows investors a different picture (probably this would even influence a bank loan) - manager has to fight a different bureaucracy Not to mention that comparing the cost of a hire by looking at their salary is pretty dumb. ISTR hearing at Google that the overall estimated cost of employing a SWE is like 4X their compensation? Can't remember the exact figures though.

I don’t think companies will do that. Why don’t they just buy local on-premise infrastructure even though it’s cheaper than AWS? “AI in a box” sounds a heck of a lot like “the box” from the Silicon Valley TV show. Or the Google search appliance. Or name any other on-premise thing that is equally dinosauric. The real finding of this article is that AI tokens are direct competitors with offshoring. $1,500/month buys you a whole employee in India. And this is before AI companies inevitably increase pricing after the conclusion of the growth phase.

> it's WTF did Uber build with all of that spend? You can ask the same for the median 330k salary in the US for Uber Engineering... and being a bit snarky, attending Uber engineers talks here and there at a few conferences, looks like. they love to (re)invent internal tooling/platforms. That's pretty expensive on its own. EDIT: I'm not saying that Uber's engineers didn't add value to the company, they absolutely did and handling the scale up they had to handle is not an easy feat. But I do challenge the notion of "what features did they create with that (LLM) spending?" of GP.

> You can ask the same for the median 330k salary in the US for Uber Engineering People DO . It's well known that most tech companies are ran incompetently. As you say, it's not the engineers' fault. But most projects and hiring in these companies exists to juice promotion criteria. And that, depending on perspective, these companies are either massively overstaffed or massively underproductive. The comparison to AI spending being wasteful holds up pretty well, these are companies that readily piss away billions in pointless spending.

This is a very good answer but there's a flip side too. The idea of "if you add intelligence you make more money" is contradicted by the fact companies don't just always hire more people. Wy doesn't google just hire everyone?

> How did it meaningfully impact their revenue in a positive direction? It probably allowed them to avoid hiring as many people to build a certain amount of software. Even if it didn't increase revenue, it could have lowered human labor costs. > 128 GB machines that can run local LLMs are a bargain even if priced $5-8k. Don't forget the energy costs. Searching around, advanced models use an average of 25 Wh/1000Tok. $1500/month gets you about 150M tokens. At the aforementioned energy/token, that's 3750kWh. What are your local office electricity rates/tariffs? (Hint: they are going up because of AI data centers). Even if my price and energy assumptions are wrong above, you probably aren't going to get the rates that the hyperscalers do. Even at cheap (i.e Texas) retail electricity rates, that many tokens will probably cost you hundreds per month. In most other electricity markets, probably far more.

How much more software does Uber need? Unless they are iteratively replacing expensive vendors and optimizing other headcount costs?

In Latvia, the net salary for a Java dev is around 1729 - 4314 EUR, based on https://www.algas.lv/algu-informacija/informacijas-tehnologi... (crowd sourced data) For the employer those employees cost between 2945 - 7736 EUR per month based on https://kalkulatori.lv/lv/algas-kalkulators (income and social taxes). So on the lower end that's (1500 USD ~ 1300 EUR) close to half the total expenses of such a developer, on the high end here around 15-20%. That's quite significant, depends on whether their productivity also improves (if that's what the orgs care about). And we’re not even the country with the worst pay out there, but pay the same for tokens, cause regional pricing isn’t a thing!

That depends on where you are. $18K is the equivalent of paying around 15% more for your developer.

In hcol locations yes, but in south of spain you can get full time talent for that figure. It's also an entry-level salary in eastern europe, with ukraine and turkey even being somewhat cheaper.

That was badly worded on my part, my intend was to indicate that there was no way they can or will pay $1500 per month per seat.

I don't think it's necessarily what Uber build, but the gained productivity. If the engineers use the AI tools the correct way, it can drastically increase the productivity and that means they can actually use the LLM as a junior or an associate engineer. $1500/mo is way cheaper for that level of productivity where as they would have had to pay far more for a human engineer.

The real answer? Software engineer quality of life. There can be an increase in productivity without a corresponding increase in total output. The gains could be captured by software engineers doing a days work in an hour then fucking off in a variety of ways.

But that's an inefficient use of dev salary. Y'all are gonna get ground to smooth well-compensated paste.

$18K a year is a fraction of the salary of a junior engineer. Claude has allowed me to do refactors that would have taken weeks to instead take a couple of days. It has, objectively, increased the velocity of the engineering component of greenfield features by 40% in my org. You can put a number value on that and decide if it gives you favorable ROI.

$18k a year is near half of my salary as junior verging on senior developer in the conservation field. Not everyone works in FAANG.

> that I would not have written otherwise I think this is the part I struggle with. The code I write makes me money or is a way of teaching me something, both of which are reasons that I would write the code regardless. I don’t think I have any projects in mind that I’d be willing to spend half of a car on that I also wouldn’t have written myself. Obviously just a personal take though. I’m glad you get the usage you want out of it.

My "job" is building open source software for data journalism (and anyone else who needs the tools data journalists need, which is pretty much everyone else). I can build more of those tools, and better, in exchange for a fraction of the cost it would take to hire a team to help.

There are a lot of places in Europe where 1.5k$ is more than 50% of the total cost of an employee. And the obvious question: what it's the cost of that revenue? Because it looks huge but ...

Don't you forget about India and Latinamerica... No way I see companies paying that much for outsourced employees

One could hire a competent developer here in Brazil for that amount. I know because my workplace has hired competent developers for that amount. You can even call them senior developers, but you can't get "non-startup seniors" with actual experience, those expect a bit more. I just wanted to take their number at face value. It's not like it needs more real information to make AI a bubble.

So, are companies paying that amount for people at other roles to use it?

well, you couldn't justify the cost if you still employed all 3.7B

That's a bold assumption. Increasing costs by roughly $18 000 per employee worldwide is highly unlikely. For reference even at FAANG in Europe, that would be a 7-15% cost increase for a senior developer. More like 15-30% for non FAANG and even more for non-European markets.

> Office 365 An entreprise license for 0365 is something like $75 per person per month. Totally different order of magnitude. And regarding Bloomberg terminals, Bloomberg only has 1 million users (semi random guess). The reality will be that some places just won't pay for any licenses or will try to set up their own, local LLMs.

If a worker doesn't use their AI/LLM budget, can they get a raise?

Let's just say their performance (OKR, KPI, whatever "impact" metric you want) was indistinguishable from a peer that used the AI/LLM monthly allowance in full. Maybe a $10k raise would be nice?

> That means each employee's AI spending cap is ~11% of that median compensation package. when looking at costs - numbers make sense. however decisions as an org/company/solo founder - costs help you set prices, but to reach profitability you want to model around ROI. now the question is what's the ROI for a $36K/investment per engineer or $90M for the total org ? I bet the ROI is negative.

I'm in a similar boat - it's hard to measure, but let's say you pay an engineer 150K. Giving them a tool that costs 15K a year is effectively a 10% increase in that expense. If we were seeing 3X, 5X etc improvement from individual engineers, that 10% increase in expense would be a fantastic investment (even 3 engineers for the price of 1.1??!). I have a feeling they are just not seeing that much of an improvement.

It's also a useful signal for AI value. Looks like it's a max value add of $18,000 per engineer per year.

It means Uber thinks they can sustain that level of expense. Whether engineers at Uber are representative of the rest of the work force is an easily debatable question.

I think the logical follow up will be for Uber to lay off a bunch of people so that the remaining ones can token maxx. To the mooooon!

It finally puts a number on productivity gain of engineers with AI. This is probably less than 10% of the cost of an average uber developer. So they don't assume much more productivity gain from AI than 10%. (Cost of an employee is much higher than their salary, it includes things like office space, supporting structures like HR/accounting, insurance, hardware/software, and much more)

If you estimate 10k salary per engineer that means the moment it’s cheaper for them to hire another engineer but that doesn’t mean it’s improving productivity 15% but if 15% is the moment it stopped being better than another human we can assume 7.5%? Probably even less because you would spend those 1500 extra per employee also if you just save 10% so 150 per employee that’s 1.5% on salary. This is imho one of the best ranges we can assume for now how much would that be on the whole swe market?

What is the point of allowing a developer to spend $18,000 a year on AI subscriptions? Can't they hire a decent developer who is capable of producing a quality solution faster? Clearly, these decisions are all made by high-level management team. I was recently talking to an HR person from a European company, and she goes: 'We are forcing our developers to use AI coding agents, but they are still kind of hesitant.' This person had never written a single line of code, nor did she know what software engineering is. For these people, using AI coding agents = faster delivery without breaking anything.

It costs a lot more than $18,000 to hire a decent developer, pretty much anywhere in the world. Also using a model is better than another developer in some ways, because there aren't two independent minds trying to work with each other.