How employment is changing at Anthropic
anthropic.com
anthropic.com
Commits per engineer 5.1x
Queries per data scientist 3.1×
Contracts per legal employee 3.1x
Deals per salesperson 1.7x
Hires per recruiter 1.4x
Invoices per AP processor 1.4x
The first 3 stats, commits+queries+contracts, are secondary/meta statistics that could possibly go up 1000x and have very little affect on Anthropic's business, whereas that's much less likely to be the case with the last 3.
AI can make it very easy to do more and more busywork that doesn't move the needle.
If the above is true, AI econ must rely on a second order effect here in that busywork/BS is recognized more quickly and discontinued.
For example, if an organization paid an employee to compile a monthly report and it took them a very long time. But with AI, they can make that report every day. Now the organization realizes that they don't even need it.
https://fred.stlouisfed.org/series/OPHNFB
Annual growth over that period has been ~2.2%, sometimes a little faster, sometimes a little slower. The doubling from 50 in 1982 to 100 in 2017 (35 years) averages to 2% per year.
Even if the overall productivity boost due to AI "only" turns out to be 40%, the lowest among your numbers, it's equivalent to 17 years of growth at 2% per year.
That's not exactly small.
I don’t see how we’d get to 40% unless a) humans are out of the loop, or b) we hire lots more humans which would make AI cost-ineffective. What am I missing?
Apparently that 40% is the lowest productivity boost over half a year reported by Anthropic in TFA and reproduced above by djoldman.
Two reasons to question the 40% number:
- Anthropic probably represents the extreme case of AI adoption, if they're not the absolute leader. I would see 40% as the absolute max for that category without knowing anything else.
- Anthropic is a tech company, willing to change their workflows rapidly, having maximal enthusiasm for the technology, and maximum knowledge of it. The vast majority of the world's companies don't come close to it for these aspects and therefore adoption and speed should lag significantly compared to Anthropic.Anthropic’s revenue has seen enormous growth [3]. They have few employees. Obviously, as these things are measured, they are highly productive! It might be hard to reproduce that sort of productivity outside the tech industry, though. We can’t all be Anthropic.
[1] https://fred.stlouisfed.org/series/OUTNFB
I’ve seen so many “dream” projects finally realized recently that organizations had been chasing for years only for them to realize it provides no value. Easily could have wasted years of time and tortured dozens of people but instead only took a relatively small amount of time due to AI.
I know some people will say this kills jobs but I really don’t think these are the jobs humans should be doing. It shouldn’t take someone’s entire life to realize people don’t actually want to “gamify their credit card application process” or whatever dumb thing product comes up with. Also when you spend so much time on a dumb idea a lot of people will try to justify it which is why I think we see so many obviously bad ideas go to market.
The amount of requests I get to help “make the next Facebook” or “make an application to predict the stock market” have gone down substantially and I think this is a good thing.
While this is a possible explanation, it seems far more likely that people are finding more private/solo ways to pursue whatever their equivalent of “make the next Facebook” or “predict the stock market”.
I would be very surprised if the was a reduction in total duration of pursuit of these type of ideas. I think there’s just a reduction in them asking you as a dev to help.
I'm struck by the fact that the origin of the word "business" is "busy-ness".
- Deep curiosity and ability to absorb new information quickly - Evidence of ability to wield and coordinate agents to the max - Ability to clearly communicate ideas
You have these skills, you can conquer the software world.
Wow, so you worked with recent grads who are producing 100x the slop? No wonder Anthropic doesn't hire junior engineers.
"People with no taste or experience mass generating code by copying tickets into Claude and pressing accept is the best!" Ohhhhkie dokie broskie
But there are so many people who make statements like his that maybe we should assume that some of them are not idiots or bots. If he's not an idiot it means that he's working in an environment where that kind of statement is paying off. So it could be, for example, that he doesn't really have profitable customers. His main 'customers' are investors who are clueless, or who know that they are clueless but don't care because they are going to move it on to a greater fool anyway. Or that because there aren't any customers, the only thing they can measure is 'productivity' in terms of 'number of unused, unprofitable and unsustainable features'
There is another option to consider. What if they heard someone else say it and they believed it.
Now they go around, like many insecure people do, shouting about their unfounded take. Begging the universe to correct them or give them a good reason why they arent informed.
Then what usually happens with people who suffer from this type of short ordered thinking is, they realize they can't walk it back without social consequences because of the shouting they have done. So they just double down on it and find ways to live with the cognitive dissonance. Anthropic, openai, etc make billions off of people like this.
Because they propagate the BS advertising to people who don't know better, and then spend more money to try to make it real.
If everyone does it, no one monitors it anymore, and quality degrades the only way out is more tokens.
All they really need to do is convince enough people to adopt lower expectations and accept worse software products. At that point, mission accomplished. They've annihilated the source of value originally provided by people who actually know how to do things.
I mean real profit, not "adjusted profit."
As long as there other companies scooping up the juniors (which we cannot assume will happen), this could be sustainable.
This is every industry - barring unionized trades with established apprenticeship pathways - over the past few decades. Either someone does the early-career job-hop dance, or they take on student loans to (maybe!) skip some of that. (And, you know, universities would prefer not actually to train anyone, either. If they can - "highly selectively" - find cohorts who don't need much mentorship then that's much better for their bottom lines.) Regardless, the entire cost and risk of training has been pushed onto individual employees.
Yes, this works well for a small minority of highly-motivated people - who are, of course, vastly over-represented on this board, so few here will object to it - but it prevents far, far more people from ever reaching their potential.
And you can't just poach either because in that case we wouldn't have had juniors to begin with.
I've used vi and emacs and the number of their users that really 10x everyone else is vanishingly small. A large percentage of their userbases are people who wished they were the 10x but were much slower (or at best equal to) than the average Jetbrains tool users.
I have seen multiple cases that proves otherwise, some new programmers try to learn Vi because "All the cool haxxer on youtube use it"
We used to call this RDD - Resume Driven Development.
The difference between a junior and a senior is still very real. With agents, knowing what to ask them to do (or not do) is bordering on more important than it ever was. A curious junior might still go down rabbit holes for things that a person who had done this before. That’s what makes them a junior. Not everything we _can_ do we _should_ do
Anyone who has been in software for a while should hear alarm bells going off when they read this. Every line of code is a liability, not a trophy. This is what happens when people who don't know and don't care to learn about the existing body of knowledge in a discipline "reinvent" it.
Give it another year or two and Anthropic will be writing all about how they lowered LOC and got agents to be more conservative about generating new code and introduced a "verification gate" for every new line produced.
The compiler development teams make sure that the output of the compiler is correct according to the source code input, preserving semantics and issuing errors for incorrect statements.
Who is doing that for LLM prompts?
Imagine worrying about gcc or the python interpreter that much. No wonder they use the label "reverse centaur" for LLM usage. You must think carefully before coming up with a prompt, then review the code carefully for correctness. Double the stress for no reason. Or is it just going with the vibes and slinging slop?
That means knowing how output looklike with given input is important.
The preference in most industries has always been towards producing more code with some bugs rather than less code that's nearly flawless. Given that, I'm pretty confident that soon I'll not even read code anymore and become a tester (and/or req engineer) instead.
I mean the thing you imagine I don't mean.
> Anthropic reportedly screens job candidates with a culture interview testing whether they would put the company's mission ahead of their future wealth. One applicant was asked how they would feel if a safety decision sent Anthropic's stock to zero.
https://finance.yahoo.com/markets/stocks/articles/anthropic-...
You're supposed to say, 'of course I'll put the mission ahead and send the stock to zero', but then when you're in the position, you can never allow that to happen, it'll make your manager look bad. The joys of corpo life
Until adherence to the values may lead to a loss in share values, at which point you have to quietly abandon them. It's a tightrope to walk, especially if you're not neurotypical.
These people won’t necessarily need to be trained in CS, because in 10 years no one will need to know what a data structure is. So they can come from other fields (law, business) or just from other roles within the company.
Note this is basically how it already works in every non-technical field where there’s no clear definable “skill” on which to evaluate people.
The point is that judgment won’t be needed on technical aspects. It will be more soft decisions like how to manage the agents.
Maybe this is the bottom and things only get better from here. I’m hopeful.
Software, surprisingly, is a technical skill. Stop comparing it with poetry, sales or dancing.
Since we are talking about bridges, cars and ships, that is.
Don’t fear change.
If you don’t pay them, you can walk by feet. If they ban you, you can walk by feet. If their infrastructure is damaged, no one and nothing will be able to move.
Good point about infra, but that’s already the case with Cloudflare, GitHub, aws, etc
BTW, when (not if, but when) a war happens, they will become very nice targets to render this exact country completely disabled.
Humans are autonomous, distributed, and adaptable. In a package that weighs ~150 lbs, with very low energy requirements.
You literally cannot wipe them out without a sustained and incredibly expensive ground campaign, and even then it's not likely.
AI in a data center on the other hand... So easily disabled.
And voila. No cargo moved, no code changes or fixes, no medical diagnosis made,etc. A whole country is disabled.
I thought that was an interesting idea, but not something that could ever happen..
Re: war.. that’s why US spends orders of magnitude more on military than anyone else. If any infra is hit on US soil then im heading to the bunker because most of the world will have already been reduced to dust.
Single points of failure are a fact of life.
AI offers relative democratization. What’s going on with model competition is giving us more choice, not less.
My manager was dragging me through useless projects that went nowhere despite multiple people telling him "it ain't gonna work" while shooting down proposals that later turned out to be "high priority tasks required directly by upper management". And he's a well-paid, educated employee with years of experience. Don't even get me started on delivery guys who cannot read a simple instruction like "do not ring the bell, leave the package on the doorstep". They just follow a 50-line script and that's all they can do.
Whenever you mention that AI won't reach human intelligence, remember that this is the benchmark. Not Alexander the Great, it's the millions of people throwing their life savings ($1000 each) into Labubus. Long time ago there was a series of articles in my country about the costs of wedding receptions skyrocketing and some people taking out loans to pay that, and someone made a meme "robots will never have human intelligence!" with reply "bro, you took out a loan to pay for a wedding, I don't want your human intelligence".
Denying this reality is pure cope.
You are showing disagreements with your priorities (mostly money) as unintelligent. You're showing a lack of care and conscientiousness as unintelligent.
You're reducing intelligence to alignment with money and following instructions. Under that framing the argument is already won in favor of AI amd some vague effective maximizing of a cost function.
Many jobs are like this, so it's fine for employment. Maybe the vast majority of mankind was never suitable for reliable employment of the "cost function" style.
But I know two things:
1. Centralization should be avoided. The reality that AI can do most jobs is not a reason to concentrate power behind those portraying that or building AI. We still want local, ideally individual, empowerment. I don't see enough said about this. Maybe we can even say the system must be one people wish to opt in to, to maximize profit.
2. Intelligence is being very narrowly defined and humans value more than an INT score in the RPG sense. The more I meet people outside my belief circles, the more I realize the intelligence of some actions, in the sense of "logically deduced from a higher principle" not "aligned with my western white collar principles". The ultimate role of culture and humanity IS this principle exploration and to say we've reduced that exploration to "maximize X" is crazy.
At some point deciding fate of the company or system or state flows from principles embedded in cultures and that's in danger of being flattened away by optimizing outcomes with machines.
Vague and wishy washy, but its the clearest I can state it.
If the principle embedded in the culture of my manager is to do dumb shit that goes nowhere, then I'm not sure what goals we're achieving.
Denying that reality is pure cope.
Self-driving requires less holistic thinking than imagining, building, and evolving large scale systems. It requires abilities that LLMs do not have. It requires non-symbolic reasoning, intuition, etc. that are beyond LLMs.
Intuition exists outside the human brain?
No.
> Don’t fear change.
Change is inevitable.
What I understood from the comment is that Op fears the boiling frog scenario. [0]
Imagine I am 200IQ, and I can solve things you can't comprehend.
You appear to be saying I should this be able to run any system, including the entire United States fed govt, and anyone who even questions if that may have bad effects should "not fear change".
The industrial revolution was Change, but so is cancer.
That's the point, they are setting up the economy to be run by agents and they trust that it is possible. Step 1. Teach AI human knowledge (2022-2023). Step 2. Make AI agentic (2025). Step 3. Start autonomous research and create own corpus of knowledge (2026).
Step 3 will keep compounding (as we are witnessing) and most people will be left behind. I'm not against a revolution, I'm all for it.
It's not only AI. Betting is on the rise, adults and minors are being hooked by dopamine loops, social networks are causing well measured negative effects, children's educational scores are sinking worldwide, appliance manufacturers engage in surveillance...
It truly feels like the wild west.
In the US. When the inevitable legislations start popping up worldwide, don't be surprised when somehow the American consensus will be to do nothing.
fwiw, i think literally all largish corporations have been like that pre AI too? i can gurantee you that nobody understands how the whole system works at all of my last workplaces either...
people just know their small part and hope for the best - so from a devils advocate pov, its already been proved that its sustasinable. now wherever its _worth it_ is another question. large employers are - on average - incredibly wasteful with their resources. not to anthropics degree, but still.
if youre boostrapping, and VC token subventions go away... i suspect it'd be not worth it to develop like that. But i guess we will find out in a few month to 1-2 years
How about the dollar you earned, spent, invested? Do you know how it works?
How about the clothes you wear?
This is just a tiny subset of the enormous complexity we're immersed in, and no individual or collective has a complete understanding of it. If you do, you're truly an outlier and GP's point still stands.
Even for the COBOL based systems someone understands it well enough at the conceptual and business level. And when there's no one to the company migrates and modernizes.
You are conflating the subject matter expert who understands one area well and others not so well with a general newbie who understands nothing well
I don't think it is. @squidmaster specifically noted, 'The "Renaissance man" era is long gone.'
Is that really a problem though? We can solve problems empirically even if we don't keep the entire system's workings in our heads.
I agree that formalizing observations into a system can lead to additional insights, though it would probably be hubris to assume the formalization is faultless.
Yet even without AI, humanity's most complex creations are not understandable by mere single humans, or even groups of them.
For example, the US Healthcare Insurance system runs on the collective power of humans (and likely an increasing bit of AI), but no one human can understand the system as a whole.
So while some stuff may transfer over as a general thing, a lot will probably not.
Still interesting, of course, but to be consumed with a mountain of salt.
I think you left a tiny bit out: the smartest model in the world
probably irrelevant detail
At least they are honest about where this is going, just like when robots took over factories.
Naturally everyone thinks they are the lucky ones that will stay around, monitoring the robots.
Two vibecoders are walking down a forest path.
One of them spots a Zig codebase and challenges the other: “I'll give you $100 to convert this codebase to Rust!”. They accept and after spending $1000 worth of tokens on a thousand commits the codebase is now in Rust.
On the way back, the second vibecoder spots the same codebase again, and challenges back: “I'll give you $100 to convert this codebase to Zig!”. Another gajillion tokens later, the codebase is now in Zig.
Walking a little more, one vibecoder (in a moment of unusual clarity) asks the other: “It feels like we just did this for nothing”. “No”, the other responds, ”we just increased our company productivity by two thousand commits per day!”.
However you measure it, in LOC or in MB or in ops per second, demand for more software always seems insatiable. This trend will likely continue up until software can be produced with zero humans at all. But I can’t see that happening unless we invent actual real artificial intelligence.
There simply is no way to separate what’s reporting and what’s advertising.
They are offering a cure to the defining contradiction of capitalism: The tension between capital wanting maximal self-reproduction and labor wanting a fair wage and a good life.
Anthropics pitch is to finally redeem capitalism by getting rid of those annoying workers and their annoying demands - that is why C-Suites are so excited about it, that is why its talked about in messianic language.
Unless we somehow manage public control of AI, in which case we could hope for a Star Trek style technological utopia.
Rosa Luxemburgs word's have never rung truer - Socialism or Barbarism!
To the poster below who thinks anthropic is in this to destroy capitalism(lmao rofl), I guess maybe if you are interested in fuedal societies run by people who currently bomb schools, have chatbots and finely tuned recommendation engines designed to make children commit suicide but only after extracting as much capital as possible beforehand, try to sway elections in foreign countries, theottle the Internet so dictators can win wars, etc. Yea sure man they are all definitely interested in making the world better for everyone by also automating one of the few middle class jobs available in a country which has no manufacturing to fall back on. Super normal timeline.
If you are already an advanced company filled with skilled people, you may not see the gains that a mid-tier company filled with mediocre seat warmers would see when their "best and brightest" start adopting AI to replace said seat warmers.
An example: the UI applications suffer from massive amounts of repetitive code. People on hacker news will probably instantly jump to some kind of componentization strategy. More wise individuals probably understand you need to draw a winning strategy before that’s possible. Identify common workflows, from that, identify common components, figure out a parameterization and so on. The footguns are the slop having unintended consequences which fixing might actually cause production bugs by being “features”.
Hypothetical now: a current alternative solution which may exist is two simple detail views (of which there may be 30+ in the application) are 1000+ LoC template files, hand-coded, copy-paste, with all the errors you could imagine. You can get a lot of work from that so people are/could be content just fixing slop with slop and calling it engineering while piling on more features. Maybe it works but it doesn’t allow for much engineering room.
With AI tooling, popular support becomes less necessary - correctness matters more. Instead of galvanizing people to realize this is wrong (and it’s not just a want thing, with offshoring and the general difficulty of software engineering, many people don’t understand these concepts. They are great people but struggle understanding for loops intuitively; I don’t know what to say). Now I can provide my strategy to the tooling and do the decomposition and componentization myself. On top of this, my strategy can be more intelligent and robust because I’m not doing it by hand like concurrently using the API layer as a source of truth to give my agents more context on what the UI was trying to do. The code itself is confused so part of the work is learning the intent behind each module and also capturing bugs that are “features” to prevent regressions. Basically, a clean room rewrite (but we have access to the source code so I know that’s not the exact correct term).
The engineering moat is still there. If I say, “Claude make my UI codebase smaller” it will burn tokens and fail. One day it will succeed but right now it will fail. Likewise if I say “Claude suggest ways to make my codebase smaller”, it may suggest my strategy but it may not capture all the critical wrinkles. LLMs are not good at simplifying so to simplify (which is always a good goal in software engineering as long as the abstractions still hold), requires human strategies when complexity is high enough. Especially in my case where the behavior of the code is almost more emergent rather than engineered.
Then carrying on, hypothetically, I started to devise a system for not only rewriting the UI but the rest of the application (API and DB layer) as well as the corporate processes around the application. This may sound rude but these corporate processes can be disempowering and wasteful. The trick is inversion. First build a conceptual interface around the layer. The model will understand the purpose without understanding or rewriting the internals. This saves context and allows it to do more powerful reasoning by having perspective instead of being in a vacuum. Then when you have bandwidth, use that interface along with all the context you developed working on other modules, to take control. An example, you have a team which is responsible for building and deploying. To build and deploy, you may need to fill out forms, contact layers of people, all to achieve the end of goal of “building and deploying”. Through inversion, you communicate with an agent endpoint that handles communications to that team. Escalating, writing forms, and doing whatever is needed to get the code built and deployed. For all intents and purposes, you are now in control of that process. What used to be, for example, “I want my code built and deployed to QA” -> “message A” -> “message B” -> “write form A” -> “monitor for responses” -> “build triggered” can now be “I want my code built and deployed” -> “activate agent process” -> “build triggered”. This is an application of inversion in a nutshell. AI allows to apply engineering principles not only to our code but corporate processes where applicable.
So in this case, there could be 100+ individuals supporting this application and process. The one or two or three engineers that used to own the development process (more or less) were drowned out yet still responsible for the overall process and integrity of the software. It was an impossible task but now it seems more possible. The existential angst part comes from the all processes that were sprung up to support a reality where this all wasn’t possible.
Last, I definitely do not think the solution is one hundred engineers. If you know the show “Breaking Bad”, I actually find the reality of software engineering to be more like this now. The difference between 60, 90, 95, and even 98 percent purity is staggering. And the chemist who takes the input (money and tokens) and produces the highest quality output (codebase and processes), dominates. Just as in Breaking Bad when Walter White inherently has power, despite all other chemists and structures of authority, because his process had the highest purity output. It’s just business sense and adding more chemists does not increase purity. Output quantity is no longer gated by number of bodies so that argument goes out the window. Mentorship will be key (as in Breaking Bad) and large teams of all-high-quality producers should be put together into super high-thoroughput teams. But for regular operations, prioritize the highest quality output where the input is guided by the highest quality producer because adding more cooks will seriously degrade the output, at an exponential rate.
Consider for instance the bicycle youtuber Berm Peak, who's been using AI to reverse engineer and hack shitty ebikes. This kind of work is outside his expertise, so the relative lift he gets is massive.
Note that I specifically mentioned that I'm skeptical of claims of insane lift in workplace contexts. Several factors work against it there, organizational dysfunction not least of all, not to mention a disconnect between the people doing the work and the people for whom the work has value. People being crunched by their boss to ship some corporate portal software faster are going to make shit. You making something for yourself, to solve your own problem to your own satisfaction, needing to clear problems outside but adjacent to your proficiencies, should be able to do much better. Many people have found it to be so.
These tools excel at greenfield development, but they genuinely struggle in mature codebases. Especially when it’s a legacy system with spotty documentation.
There is no measurement. Think about how much of a difference empirical science made in such a short amount of time. Or think about how it is impossible to optimize software without measurement etc.
Also there is the AI companies’ atrocious reliability even if you trust the measurements
The company is literally trying to sell itself via an IPO ... every single word they say is advertising.
Every R&D company on the planet has this cycle. Hire lots of developers and researchers. Build product market fit. Lay off all but essential personnel, while increasing the amount of sales and operations stuff as much as possible.
Anthropic this isn’t novel or unique in any way. Stop pretending your AI wonder machines are the reason why. This analysis lacks ANY comparison to other non AI research company hiring cycles. Do your homework please, this is pretty embarrassing.
They are nowhere near profitable, have terribly bad products riddled with bugs (9,000+ open reports on Claude Code), and have no moat. Why would anyone listen to how they work internally?
I'm too lazy to bother looking up each of their credentials. Are any of them software engineers? Do they know anything about creating, maintaining, and evolving software?
I do know that Anthropic's CEO isn't a software engineer, so it would be hard for him to evaluate their claims with any deep insight from experience.
According to his LinkedIn profile, the software development he did was for less than 3 years in a very narrow field. I would call that very limited.
Coupled with the incentives driving him, his judgment would be heavily clouded.
I guess I'd be curious to see what this single-person startup is offering...
I'm also reading this with a healthy dose of salt. They rely almost entirely on the concept that using their tools is an economic advantage to companies + individuals, so... Of course we're outputting 5X the commits per engineer and sales positions are seeing a 1.7X increase! Our agents work 6X the hours of our human employees!
Say that it is borderline true (it's not, but let's pretend). Then companies can lay off 90 devs for every 100, and buy the remaining 10 devs Claude subscriptions. Isn't it better if they keep all 100 and buy everyone a Claude sub?
So shouldn't Anthropic actually be pushing the narrative that Claude doesn't replace devs but actually makes them vastly better at their jobs and so every company, big and small, should buy every dev the highest tier Claude enterprise subscription?
They don't want higher productivity because what are they going to do with that? Launching new products is costly and uncertain. They don't want to be paying the same number of developers and have them all spending money on Claude subs. But the idea of firing 90% of them and having the rest in fear for their jobs? Brilliant!
Back in the real world, the question is what's going to happen to companies that go through with this. When they have vast amounts of slop code that no one understands? When you have to sit in with a customer and explain why the product doesn't work and no one knows even how it works never mind how to fix it? We can already see the inklings of this in the huge buggy messes that Microsoft and Anthropic are producing. Interesting times.
I wonder how complex the prompt was to write this.
See the YouTube talks on Visual Studio roadmap, is all about AI.
Even the sessions about IDE tooltips, were in fact about how to give CoPilot prompts about Visual Studio features, instead of how to use them ourselves.
.NET is also getting the AI treatment, see all the AI stuff that they are pushing on Blazor and Aspire.
This may not be saying much at all. So much goes into deciding how fast to hire. Instagram had 13 employees / 1B rev at acquisition?
Also revenue per employee can vary a lot depending on the industry.
A better metric to understand AI effects might be revenue per employee at companies that have been around > 5 years that are AI-enthusiastic.
And all of this is then somehow classified as responsible development of AI, by people who claim AI could eradicate humanity, and that RSI will be our downfall. How exactly is outsourcing your work on agents to agents not RSI at this point? Why are these people still allowed to operate again?
One data point I’d be interested to know more about is if they’ve scaled back their hiring due to AI productivity gains, or if they’re just doing more engineering for the same money. As I see it that’s the big question for those of us who have to work for a living.
>"One possibility is single-person startups, each with a human founder steering swarms of agents to rake in billions in revenue. Another is companies built by AI genius CEOs employing human agents only to wield pipettes and testify before Congress."
Anyhropic is not a good example for anything. Their scale and growth is way beyond what like 99% of companies experiece. Their optimization formula is different.
So... The org is equivalent to 7500 engineers ? What are these 7500 engineers doing exactly ?
I know the infra is nothing trivial. And that there's a tendency to underestimate the difficulty of what others do. But 7500 ?
I'm not sure it's the productivity revolution that it is hyped up to be.
Obviously it would need to be sustained for a reasonable amount of time while also showing at least stable finances.
Elon already stopped talking about job loses and doom, and tries to talk only about the positive.
Problem one: extreme subjective bias in candidate evaluation. Anthropic has a litany of red flag deal-killers they are evaluating for. They are subjective and not validated by any kind of scientific evaluation. Charitably, it is benign cargo-cultism (similar to being "un-Googley" from back in the day); uncharitably it is just voodoo. Interviewers use this to kill candidate loops via conscious and unconscious bias. Typically an interviewer will note one or more potential issues which can kill the loop (all candidates will say something which can be considered problematic in their interview; the potential problem space is infinite). If the interviewer likes the candidate, they will ask a follow-up question which allows the candidate to redeem themselves. If they dislike the candidate, they will ask questions which only probe for potential red flags and will not continue, or end the interview, before the candidate can reveal the redeeming half of their story. Probe until negative evidence is uncovered, and then a) continue to probe or b) terminate early, depending on the preexisting bias for the candidate.
Problem two: ghost jobs. Anthropic maintains an evergreen list of open positions that they never hire into, even senior ones. This is due to a few reasons: a) they are holding out for the ideal candidate, basically a god in human form. But that is only the reason they give themselves as to why they reject almost all candidates which make it through their loops. The real reason is b) existing employees and managers do not want another peer to collaborate with, instead what they really want is more agents for them to command. It's an intoxicating feeling and much preferred over in-person interaction. With fewer employees, it's more scope and power for the existing ones. It's well known in certain circles that interviewing there is a waste of time. It's ironic that they claim to love humanity but actively dislike actual humans.
Problem three: extreme dependence on agents for daily operations. Because they don't hire enough humans for the reasons above, they are outgunned and completely dependent on AI to operate. If AI were shown to be problematic or dangerous, they must still keep running it internally. Thus, they have no control. They are structurally compromised by AI; they don't have the capacity to put humans back into the loop. AI has already left the box and the box has been dismantled.
I don't wanna be the guy calling out the lie or slop but when did Anthropic hire in the last two years for junior roles? OAI and Anthropic could literally hire seamlessly the best of the best worldwide for every job they advertise without having the need to think about the poor juniors.
actually, to me, it was one of the first signs of what’s favored and praised in the AI space (companies building models, doing ai research). an accelerationist mindset: do things to save the day and demonstrate some progress. no one cares much about what comes next, the human aspect, or the headaches you inflict upon your coworkers.
anthropic hiring those guys is not surprising at all, especially given their vibecode-oriented workflows disguised as next-gen product engineering (which is educated vibecoding adorned with some superficial engineering ethos).
they hired some seniors too. one of them went to work on claude code because he cared a lot about the craft and the product. (how ironic right!?)
soon after, they started talking crazy cult stuff like “the software problem is solved” and “this is probably the last job i (can) have (as a software engineer, product developer).” he also told a friend who applied to their team, “better hurry up, we might become jobless in 6 months” (this was almost a year ago :S).
In other news, Turkey farmers encourage you to buy more turkey for Thanksgiving.
> An executive assistant, who built a personal assistant agent for scheduling and email triage
Really? We should build our own agents for everything? Sounds a bit token-spendy.
Also, as far as I can make out, the paper was not written by AI (nor even with AI assistance?). You'd think they'd make a song and dance about it if it was. Maybe AI can't do this sort of thing yet (or ever).
also 'lines of code' or any other output based metric in the age of infinite slop is not a flex/indicator of usefulness or value.
and yes, everyone spends all their time reading Claude output. that doesn't mean better work is getting done, or progress is being made. i've been reviewing and fixing claude slop at work for at least a year. if anything companies/products are getting more homogonized and bloated. thanks anthropic, you are going to save the world
it was interesting in the beginning when there was technical substance, but now its just techno-bros vision of deep thoughts
If you wouldn't mind reviewing https://news.ycombinator.com/newsguidelines.html and taking the intended spirit of the site more to heart, we'd be grateful.
“Anthropic bad because automation of labour”
“Claude bad because it hallucinated that one time”
“This is a marketing post to hype up ipo numbers”