Comment by FartyMcFarter
1 day ago
If any company announces that they use token consumption as an employee performance signal, for me that's close to a red flag to stay away from that company.
No company with good engineering leadership should act like this is remotely a good idea.
As I have snarkily observed at work: if I go $100 over the meal allowance on my business trip, I'll have to have an unpleasant conversation with my manager or finance. If I use $500 in AI tokens unproductively I'll be recognized for being a top AI adopter.
I have seen this type of behavior happen many times in different companies.
For example, at more than one company I've worked for, if you wrote shitty code but got it into "testing" faster than anybody else, you are considered a superior programmer. And then, if you fixed the hundreds of bugs found in your code seen as an extraordinary programmer going above and beyond the call of duty.
Management is always measuring the wrong thing.
You'd be surprised, I know a few devs in very big tech companies, not faang but you definitely know them, and they all have some kind of token leaderboards, a few told their dev "we don't want you to write a single line of code manually anymore", etc.
I assume the execs perspective is something like: if the top 20% of worker produce 80% of the code with LLMs and the company still works then we can get rid of the bottom 80% of devs and save money
But even if the end goal was to lay off 80% of programmers, shouldn't the 20% to keep be the developers delivering the 80% of the code, regardless of whether they spent the most to do it? Like what if the 20% of workers spending the most tokens were actually the bottom 20% in terms of delivery because they were using the worst prompts and having AI constantly implement 5 different versions of everything, then throwing it all out because their prompt was so bad anyway?
Ah, but "who uses the most tokens" is a number, a number generated by a computer no less. Questions like who delivers lots of high quality work require you to do research and make judgements, which is work.
Problem is that those 20% depend on the code reviews of the 80% for some form of pushback.
I think there's probably something to token use as some kind of metric. If you aren't using these tools much, you're definitely not going to remain a top contributor. The world is evolving quickly here.
But it's just one signal out of many, and more isn't somehow inherently better beyond a certain point.
Tokens are the new "lines of code per engineer". Easy to graph, easy to "manage".
The new TPS reports!
Oh, so that was actually a Token Per Second report! Wild!
...and easier to bill! Back, then noboday had the idea to charge per "lines of code", but today it seems accepted to charge per words processed?
The problem is that many companies which had reasonable leadership in the past with the advent of LLM AI started to make rushed (and dubious from my point of view) decisions - using token usage to evaluate an employee performance is just one of them.
Meta does this. Guess what one of the criteria for their recent layoffs was.
Meta tracks token consumption, but has explicitly stated that it is not a primary performance metric. Instead, employees are evaluated on "impact."
Indeed, they also said that previous time off for ill health wasn't a reason either.
but looking at the number of people who had taken leave, it suggests otherwise.
6 replies →
Famously honest and on-the-level company Meta, who we can parrot the word of uncritically and unquestioningly.
And my CTO insists that PR count isn't a performance metric. But guess what number gets used the minute people are forced to stack rank (of course they don't call it that, but... that's basically what it is)?
You get what you measure.
Sure, and I have a bridge to sell you. Or alternately refer you to the inevitability of Goodhart's law.
Do you have any source for this at all? I’ve seen so many different exonerations for Meta’s layoff criteria including claims that engineers using the most AI were laid off because Meta had them build AI tools to replace themselves.
Everyone is oddly confident despite all of the conflicting explanations.
Without any evidence, I would be shocked if performance rating wasn't a factor in the layoffs. But performance rating is not the same thing as AI tool use.
I worked at Uber from 2022-2025. The engineering culture was pretty abysmal, so it checks out.
I worked at a YC company that was doing this and left last month. I wonder where this all started from, VCs and tech execs are such a monoculture
The where may be the decision makers chasing social media trends. A friend sent me a link to this, this morning, about devs rather than managers, but I suspect it's the same: https://youtu.be/IW3Sbe0Hbgg