Meta and Microsoft take steps to reduce employee usage of Claude AI

So they're going to fall even further behind? Buying puts on Meta and Microsoft, or even better might give it to Fable to handle it for me

• outside1234 · 22 hours ago

  Microsoft is only limiting employees to $10k a month, down from $100k a month. :)

  • oofbey · 21 hours ago

    Absurd

• bitexploder · 22 hours ago

  Microsoft is like $100bn deep into OpenAI.

  • iAMkenough · 22 hours ago

    I hope leadership isn’t susceptible to falling for the sunk cost fallacy.

• RealityVoid · 22 hours ago

  Who's ahead, again? Do they have a moat, or just a nice field?

  • pixelesque · 22 hours ago

    Maybe a "ha-ha".

This may be seen as radical. But I think AI tools should be paid by the employee. After all, you should know how to do your work without AI.

• Jagerbizzle · 22 hours ago

  I could still do my job by typing all code into notepad, but companies don't charge employees for their IDE usage for a reason.

  • gonzalohm · 20 hours ago

    And I could do my job by paying someone overseas to do it for me. Why is that not paid by the employer then?

    • SatvikBeri · 15 hours ago

      If you can actually do that effectively, many companies will happily make you a manager.

• watwut · 22 hours ago

  Employer pays tools used for work. Whether they are used to speed up work or to make it possible.

• frisbm · 22 hours ago

  "employees should foot the bill for tools that directly benefit their billion dollar employers"

• kittomic · 22 hours ago

  Should they pay for their pipelines too? After all, they should know how to compile their software. Any automation of that process is cheating their employer.

• bayindirh · 22 hours ago

  If my employer is not forcing me to use a tool and gives me freedom, I'll be perfectly OK to use my own tools which I bought with my own money. If my employer is putting scoreboards to see and champion who uses a tool which costs money to use, they shall pay for the tool. Sorry, I'm not a ladder climber, yet I'm not mindless enough to bankrupt myself.

• iAMkenough · 22 hours ago

  I’d love it if I could bring my own computer to do my work, rather than be stuck with garbage hardware because of an enterprise agreement.

  • cyberpunk · 19 hours ago

    Wait, okay maybe I'm in a bubble, but every org I've worked at understood that giving us whatever hardware we want more than pays for itself, and very quickly. I can't fathom the logic of paying 10k a month for a developer and giving them an 800 device. Insane. Your leadership is severely broken. If you can, work somewhere that values you.

• Avicebron · 22 hours ago

  I don't understand your logic, why would an employee pay for a tool their employer wants them to use?

  • NewJazz · 22 hours ago

    Yeah that only makes sense if they are a freelancer/contractor.

• robotburrito · 22 hours ago

  The forklift should just be paid for by the employee. After all they should be strong enough to do work without one.

  • platevoltage · 21 hours ago

    The better analogy would be "Tools should be paid for by the mechanic". Experienced ones tend to have $10K+ worth of tools that they paid for.

    • hhjinks · 8 hours ago

      Your mechanic is an independent entrepreneur. If they work in a shop with other mechanics, they for sure don't each have duplicate $10k sets of tools.

• basiliobeltran · 22 hours ago

  I am fine with that if I can keep the time saved for my personal use.

• hypfer · 22 hours ago

  Nah. Work provides the tools. An LLM is not too dissimilar to a Work Laptop or an IDE license.

• ungovernableCat · 21 hours ago

  You're opening yourself up to data right and privacy risks with that. My company demands that I use their enterprise account because they can claim full ownership of all produced output and have full logs of every interaction. I think that gets legally murky, if the employee is the one who pays for the tool.

• outside1234 · 21 hours ago

  In California this would mean the employee would own the IP -- or at least it would be murky -- and companies and lawyers don't like murky.

• wrxd · 21 hours ago

  Sure. Should I also pay rent for my desk at the office?

  • platevoltage · 21 hours ago

    They're welcome to let you use the desk at your house that you own.

• platevoltage · 21 hours ago

  As someone who does have to pay for my own AI tools (if I didn't use OpenCode's free models), I agree.

This is not surprising. Every big lab blocks competitor tools for internal use; it is a data governance thing, not a quality statement.

• jvanderbot · 22 hours ago

  Right! it seems obvious why: Both these companies want to dogfood their own coding models and stop paying competition. You can also read this as diminishing returns / AI isn't good enough, etc, but the simplest explanation is that they don't want to send money to Anthropic.

  • fasterik · 22 hours ago

    This, and in addition to dogfooding, incentivizing employees to be more effective with the cheaper models. A lot of problems don't need anything fancy, but it takes more brain power and engineering effort to make that work. By default humans will take the path of least resistance if it's available.

  • NewJazz · 22 hours ago

    Does MS have coding models?

    • dymk · 17 hours ago

      yes, but there's a reason nobody talks about them

  • mattm · 22 hours ago

    This is likely the future as well. Down the road, every company will have their own internal coding models.

• octoberfranklin · 22 hours ago

  So nobody except AI labs is allowed to do "data governance"?

• WaltPurvis · 21 hours ago

  But Microsoft and Meta are not blocking competitor tools for internal use, they're merely trying to reduce costs and divert a fraction of use to their own technologies. Microsoft and Meta are both still spending nine figures a year on Claude, and the article does not state or imply they're even considering a complete halt.

• AIblemblio · 21 hours ago

  Microsoft has full and unlimited access to OpenAI models. That was some agreement when they invested originally.

I should probably know more about Claude's TOS, but it is probably a mistake for these companies not to leverage the plausible deniability of their usage and turn it into a massive distillation resource for their own models.

Limited to $10,000/employee/month lol. This is just to cut off a few people doing absurd things with low ROI. Don't read too much into it.

• smy20011 · 22 hours ago

  That's what you got from 200$ claude sub.

• whiplash451 · 22 hours ago

  OTOH "$105 million to Claude Code over a 28-day timeframe" $1.4B/year is not a small number, even at Meta's scale, when it's money going to a competitor

  • loeg · 18 hours ago

    It's a small number if it generates +$14B in revenue.

• sublimefire · 19 hours ago

  From what I could see these numbers would usually be hit by people doing vast amounts of analysis over files, they would usually rock up tokens very fast. Then you combine this with the selection of Opus models which are much more expensive internally than GPT ones and the limit gets reached quite quickly.

My company took away my Claude because it’s too expensive. I feel like there is a reckoning coming. The accountants are finally realising the cost of token maxing.

• sergiotapia · 22 hours ago

  which is quite sad because opus 5.5 is really good. i say this as an anthropic hater. i wish I could move away to other models like 6.1 sol or deepseek or whatever, but they just all lack something. i _trust_ opus 5.5 i hope other labs catch up, especially chinese labs.

  • dude250711 · 22 hours ago

    Not sure it's even possible to catch up by distilling.

  • fn-mote · 16 hours ago

    > i _trust_ opus 5.5 Just passed the Turing test.

• vablings · 22 hours ago

  That's pretty stupid. Most people who are incurring significant costs are just tokenmaxxing rather than being efficient with usage. You can get 99% of jobs and work done with Haiku/Luna in a collaberating working enviroment. I feel like people who are later to the AI game just like to "oneshot" and sink a bunch of usage into generating garbage

  • Tsarbomb · 22 hours ago

    There really is a skill to using it effectively. I've tried coaching some of the devs on my team. Some get it, some don't. Our company has been tracking token usage and models used vs output (tickets, story points, PRs, deploys, etc...). A dev got chewed out, even after I warned him, because he spent over $2k in a single month almost exclusively on Opus while his actual productivity in terms of what he delivered was abysmal.

    • n4r9 · 22 hours ago

      What do sorry points mean anymore.

      • SOLAR_FIELDS · 22 hours ago

        Did they ever have meaning? It's always been a nebulous feels term

        • Terr_ · 22 hours ago

          Attempting a serious but not-a-certified-whatever answer: "Points" do have meaning when properly used as a kind of moving-average tool for forecasting within a particular context. Problems arise when people try to perma-peg them to particular tasks, or (worse) man-hours or (much worse) man-hours across teams. Even just encouraging the humans to answer in terms of hours/days taints the accuracy of the forecast by introducing a kind of bias.

          • fdsajfkldsfklds · 21 hours ago

            For forecasting what, if not man-hours?

            • t-writescode · 21 hours ago

              Effort. Which is a very nebulous term, I agree. So, what you do is you recognize every ticket has a somewhat variable “actual effort”; and, if you’ve been honest in approximate effort pointing, you’ll know your team (or your own) velocity. From there you can run Monte Carlo simulations - say a few hundred thousand, and get a pretty good estimate of actual time spent. I’ve seen it work before with shocking accuracy.

              • Terr_ · 20 hours ago

                To play with the math analogies, imagine a black-box function: estimate(human_estimator, task_description, world_state) -> numeric_effort Assume that for various practical reasons, we've decided it's one of the best functions out there. How do we use it effectively, especially when it has noise, and drifts over time with unseen changes to the human_estimator and the hideously complex world_state? A popular option is to run it multiple times with different person/task combinations, putting a projected number on to each task. Afterwards, the tasks finished in sampling period ("sprint") become a quantifiable total for that period ("velocity"). Do the same process again with the next set of tasks, and you can figure out which ones are likely to fit if the velocity doesn't change much. If you know the velocity will change due to losing staff or vacation days... well, we apply a multiplier and hope for the best. Trying to "fix" the meaning of points is maladaptive, because they reflect many changing things which are outside our control and can't be independently measured.

              • n4r9 · 7 hours ago

                Honesty isn't the issue, in my experience. The issue is unknowability. You usually can't know what clients actually want until you've given them a prototype and gotten their feedback. You often can't know the rough performance impact until you've done the first implementation. Sometimes you just have to work through a list of candidate solutions S1, S2, etc... and you can't know which one will eventually work. All of which means that forecasting beyond a couple of weeks is wasted effort, except for rote factory-line work.

          • bitwize · 19 hours ago

            Sorry. My wife, despite loving all things French, just doesn't "do metric". She wants my height in feet and inches, my weight in pounds, boom done. So while I know my mass in kilograms, she needs the conversion done before she can even begin to have a reference point. Upper management is the same way. They have forecasts that they need to make, deadlines and budget goals that they need to hit. They only deal in the units of hours and dollars (or local currency). Every software engineer is accountable for their work in those units only. The conversion needs to be done before the management chain has a reference point. One easy way to do this is to have each engineer estimate the time it takes to fulfill a story after it's been pointed; then, upon completion, record their actual hours spent. Their estimated vs. actuals tend to stabilize over time, so even if they misestimate a task, you can arrive at a good guess at the time it will actually take.

            • Terr_ · 17 hours ago

              > > Problems arise when people try to perma-peg [points to man-hours] > Upper management [...] only deal in the units of hours I feel you're mixing up different operations here. You can always express unfinished work as likely to require a certain number of team-sprints, which are convertible to theoretic man-hours. The key is that the conversation rate is only valid for a moment, and technically that moment was the prior sprint. That's very different from management thinking (or worse, declaring) that points have a permanently fixed proportion to man-hours. > [...] and dollars If your management deals in international currency, then perhaps that would be a useful analogy to them: Points and Man-Hours are different sides of FOREX, and they fluctuate based on different conditions. When Engineering predicts a group of tasks is 54 points, that's like a foreign company signing a long-term contract in €100 EUR instead of USD. You can estimate that you'll receive ~$112 USD in a year, but the actual dollars will likely be different because the exchange-rate will continue changing before that happens.

            • n4r9 · 7 hours ago

              > estimated vs. actuals tend to stabilize over time Have you measured this stabilisation?

      • senko · 22 hours ago

        I love the typo.

        • btown · 21 hours ago

          Claude, vibe code me an entire startup, the actual product doesn't matter, but it should all be based on the incredible pun "turn 'sorry' points into story points." /goal get accepted into Y Combinator, you have an unlimited token budget, be bold. EDIT: no, do not just make a product that gives away your unlimited token budget to users for free!

          • fragmede · 20 hours ago

            Ah not to worry, you'll make it up in volume!

    • cyanydeez · 22 hours ago

      there's a manifold to what "effective" means. The problem is once you get into the vibe flow, it's really difficult to eject yourself into the other realms of vscode or IDE or whatever it is you normal do because the vibing provides no anchor to what you're doing. Even if these models are smart enough to reorient themselves, they get entirely stuck in a desert and now you're asking someone to just pull up stakes and digg them out even thought they only watched them get there and the UI provides so much speed that no human can comprehend how they got there in the first place. It's like asking a pilot to take over in an emergency situation when they're not tasked with any of the every day requirements of the job. The orgs are relying on borrowed time of experienced professionals, and that's going to erode away and what replaces it is mostly people who understand how to navigate context but not use any of the _classic_ tools. It's a real conundrum and won't be easily surfaced but for a decade.

      • mainmailman · 21 hours ago

        I’m trying really hard to keep my skills up but it doesn’t feel productive when I’m using it to write code. It feels like I’m slowing down the AI to the point that it’s not as effective as just letting it go. But I don’t get all the learning that comes from that time along the way. Have you found ways to stay sharp while using it? Or are you relying on other projects outside of work to keep your skills fresh?

        • cyanydeez · 17 hours ago

          I'm primarily using local models. I turn on thinking visible and try to review at speed what it's doing. Other than that, no. I drag myself out to poke around occasionally because at times the local models get to far into context and refuse to do simple tasks.

    • proxyscore · 21 hours ago

      So you are going to blame this one that dev? Define productivity, and while at it, quality, maintainability , modularity and so forth.

    • weinzierl · 21 hours ago

      I get it but it goes against the grain for me. Isn't it ironic that we have to waste our precious and expensive human brain cycles to think about how to use AI cheaply so that it is not more expensive than us? In other words I want to spend 100% of my mental capacity in the problem domain for the things AI cannot do for me, like steering, grounding, verification and not for things AI could do.

      • ForHackernews · 21 hours ago

        I dunno, using tools and resources effectively is arguably the essence of good engineering.

      • remus · 20 hours ago

        > In other words I want to spend 100% of my mental capacity in the problem domain for the things AI cannot do for me, like steering, grounding, verification and not for things AI could do. It sounds like the parent is less talking about this, and more people burning tokens while not getting useful work done.

      • Gigachad · 19 hours ago

        This is much like how devs got grilled for creating expensive test VMs on AWS. Someone has to pay for all this at the end of the day.

      • jjav · 9 hours ago

        > Isn't it ironic that we have to waste our precious and expensive human brain cycles to think about how to use AI cheaply so that it is not more expensive than us? Nothing ironic about it, it's basic engineering efficiency optimization. Just today I was calculating that if money was not a factor at all, we could simply use Mythos to handle all of our continuous security scanning needs, at a cost of about $15 million a year. Well, my budget is far (far, far, far, far) below 15M a year, so that's not going to work. So I must find compromises to make it work within budget. The single most important engineering constraint is always budget. Everything would be easier with infinite money, but there is never infinite money.

        • weinzierl · 8 hours ago

          It is ironic because choosing the right model is what the models themselves are good at. If there were no business incentives it'd be easy to have just a single frontend that routes to a suitable model. Instead I have to develop the decision skills which is a complete waste of my time which I could better spend in the problem domain for tasks I'm better at than the AI.

    • PunchyHamster · 20 hours ago

      It's funny, the thing that makes effective prompt also makes effective documentation/communication. It's bizzare to see people that made clown issues (not enough detail etc.) suddenly start writing detailed prompts just because it is AI that will do the task and not the human on the other side.

      • LtWorf · 18 hours ago

        You mean that now rather than taking 30 seconds to write a ticket, because we all know what we're talking about, we must take 10 minutes to give all the background information to the AI?

      • ctkhn · 15 hours ago

        The guys that made clown issues are still using AI to make clown issues, they just look like plausible specs now that claude wrote it more thoroughly. At least pre claude I could tell that they had missed something earlier on, ask a question to clarify, and get a real answer they had to type themselves. Now most of my stories are rehashed after I raise PRs or even after these same guys approve the PR and then realize they forgot a requirement.

    • onehair · 20 hours ago

      rookie numbers. in one of the top companies, i know someone who tokenmaxed so hard they ended up spending $50000

    • kragen · 18 hours ago

      What are the biggest pitfalls devs on your team fall into?

    • jjav · 9 hours ago

      > There really is a skill to using it effectively. I've tried coaching some of the devs on my team. Some get it, some don't. Very much this. There is a vast range of effectiveness and combined with so many models and pricing tiers, it can be tricky for some. You really need to treat it like partly a programming language, but also partly as a management delegation exercise (do I delegate this task to the intern (cheapest model) or to the principal engineer (frontier model) based on complexity). I do coworking sessions with most in my team to see how they are using it to understand and coach for effectiveness. Just using the most expensive model for everything isn't going to cut it anymore in the post-tokenmaxxing age.

    • RataNova · 3 hours ago

      If someone burns through two grand in api tokens over a month and still can't move tickets across the board, the bottleneck definitely isn't a lack of compute.

  • usaar333 · 22 hours ago

    > You can get 99% of jobs and work done with Haiku/Luna in a collaberating working enviroment. Optimally? Opus will pay for itself if you save just 10% of your time

    • geodel · 22 hours ago

      True. I always Opus to pay for itself if it wants to get used by me.

      • AIblemblio · 21 hours ago

        the poster did mention "if it saves 10% of your time". So be less snarky?

    • qznc · 19 hours ago

      Only if all money is equal. Budgets in big enterprises work differently.

  • perching_aix · 22 hours ago

    What on earth do you even do with these models? Or does a "collaborating work environment" mean that everything is basically spoonfed to them? Or do you only ever use ghost suggestions? I genuinely cannot even fathom. Just how do you even get into a state where tasks are so clear and cookie cutter? These things are abhorrent. Not only are they not useful, it's an outright form of psychological torture to try and use them. They almost fight you. Luna doesn't even respond to steers properly! You try steering it and it immediately gets distracted and then just stops. I can imagine coercing Sonnet into doing some of my tasks okay, but Haiku? Especially 4.5? Really?

    • dpkirchner · 21 hours ago

      I think you might be overestimating the sort of projects most of us have worked on throughout our careers -- we haven't been doing much groundbreaking work. LLMs can easily and successfully write most code.

      • perching_aix · 21 hours ago

        It's possible it's my role distorting my perception, cause technically I don't write software, I work an SRE role. None of my items come pre-chewed or paced, it's all good luck and god bless. I'm desperately trying to classify and standardize my work items and delegate them to less capable models, because my usage is clearly unsustainable and this same sentiment as above keeps being pushed on me too. But all my tasks are genuinely fairly arbitrary, so there's no real way around the agent actually being able to reason about business and technical context proper. It's not even that they're hard, it's just that they're dynamic. I can get Luna to do things like walk our observability stack and perform a healthcheck, then defer to a stronger model if anything looks super off, but if I'm being entirely honest, this could basically be just a script. Which Opus 5.5 will immediately write for itself if it doesn't yet exist, run that, and then off it goes depending. But Luna will never actually do an investigation proper. Heck, it can't even read our dashboards most of the time, tripping up on Grafana minutia. It feels like that surgeon vs surgeon comparison, where you're made to decide based on their surgery success rate, and the better succeeding surgeon simply reward hacks the number by only operating on less dicey cases. Except there's no objective way to make this classification here, so jackasses like the above get to play with my insecurities with full obnoxious confidence, while I'm left desperately trying to slim my usage and failing to do so between two moments of crippling self doubt and blockers.

        • AIblemblio · 21 hours ago

          Our ai basic analysis for SRE / k8s based platform is haiku and its surprisngly good. I wouldn't even tried it, i would still just go with even Opus (we don't have that many alerts) but it really surpsied me. When i ran into usage limits a few days ago i switched most to Sonnet and again was surprised how good it is now.

          • perching_aix · 20 hours ago

            I wish we had such a platform (and was properly adopted). Maybe then the necessary context would be properly organized, and these lesser models could be effective here as well, especially if combined with harnessing integrations too. I still have a hard time accepting that Haiku/Luna tier models can be effective there even then, but I'll just have to take your word for it I suppose.

        • qlte · 19 hours ago

          For the last few weeks I've been using Luna with Medium Reasoning for routine debugging, installing/updating dependencies, test creation/fixes, CLI/config miscellaneous problem solving, etc and it's been solid. I can let it churn away for a half hour and it barely moves the needle on remaining usage on my Plus plan. Previously I had been using Sol Low/Medium and would frequently hit the 5 hour limit doing those kind of tedious automation and routine problem solving tasks.

      • steve_adams_86 · 19 hours ago

        I equate most LLM work to squeezing a glue bottle It's just glue code It's not complicated. Someone just has to be there to squeeze the bottle

  • funnym0nk3y · 21 hours ago

    Sorry, but that is nonsense. Compared to opus haiku doesn't cut it most of the time.

    • usef- · 20 hours ago

      I think they mean the new Haiku, which is mildly above Luna now . If you have a plan written by a smarter model (so the hard parts are solved) they can be great at implementation.

      • latentsea · 16 hours ago

        I use Qwen3.8-27B as a daily driver, and for things I know will be quite hard I tend to get ChatGPT to do the planning. Works very well.

        • usef- · 15 hours ago

          It's impressive for its total size if you need local inference. Though it's significantly slower in Token/s and also thinks a lot more without matching the same intelligence (xhigh qwen27b scores lower than haiku's medium setting, and haiku-med is $0.05 per task compared to Qwen27B's $1.01 on AA's comparison) It seems like more a backup if you need to work offline, imo, unless time doesn't matter and/or your electricity is free. Or you want independence from the labs (fair enough).

          • latentsea · 11 hours ago

            > Or you want independence from the labs (fair enough) This.

  • hatthew · 21 hours ago

    I feel like it's only within the past few months that opus got to the point where guiding the model is faster than doing things myself. I tried out sonnet recently and it was not a net positive to my work. I feel like anything that I'd trust haiku to handle isn't worth doing in the first place. For context, I'm doing a range of tasks, everything from one-shotting adhoc scripts to having 4 hour 10M+ token conversations debugging things.

    • LeBit · 19 hours ago

      That is always amazing to me. There is no way I can beat even local models at generating complex Python scripts fast. hn is filled with uber geniuses.

      • hatthew · 18 hours ago

        It's not so much that I can code fast, it's that it takes a significant amount of time to tell the model what exactly I want the script to accomplish, and at that point I might as well write the script myself. And often, figuring out what I want the script to do is that hardest part, so it doesn't really matter whether writing the script takes 10% or 20% of the total time.

      • californical · 18 hours ago

        I’m a different person and definitely not a genius but my experience today goes even beyond theirs. I had Opus trying to simplify a query for me which was slow - it ran for maybe 30 minutes, including writing and running tests, and came up with a refactor across 9 files with a couple hundred lines changed. I was looking through the output before moving onto the next step, and noticed something a little fishy- I said “why does it do x, isn’t that a more complex y?” Opus thought for another 20-30 seconds then output “Actually that would make the majority of the diff irrelevant, if we do that change it is just these 4 lines in this single file instead. So then I had it do that. 5-10 minutes of writing and testing and that was done. So my company spent $25 in tokens and I spent probably an hour in total for a 4 line change that, in the days before Claude, I probably could have found the correct file and thought through the problem, understood the solution, and written the 4 lines of code myself. Probably in the same amount of time. So basically there was no benefit at all for my time, an extra cost to the company of $25, and now I understand our codebase a little bit less instead of more if I had done all the work. As good as Claude is at building greenfield projects it still struggles a lot at complex ones

        • strange_quark · 16 hours ago

          Matches my experience to a tee. And don’t forget the company also spent a bunch of money in tokens for the initial author to implement the thing poorly.

          • californical · 12 hours ago

            Thanks for the reply, I appreciate the validation :)

        • NichoPaolucci · 15 hours ago

          This is a recurring issue for us. Very small team. We move fast and pretty loose. Dev + AI spend 3-4 hours on a project plan, there's a "wait a minute" moment, and finally they spend another hour dialing it back to a solution that could have been built, tested, and deployed in 2 hours. Example: Someone was setting up a dev environment with multiple DB migrations from different branches - AI planned this wild 8 phase solution with a pretty fancy cutover event. In review I essentially said... "Wait, isn't this a dev environment? It doesn't need 0 downtime, why not just destroy and recreate the DB" and it turned into a <1000LOC script. Technically the original plan would have worked, it would have been more robust, but it would have taken a good deal more time to implement. Some of this falls on the devs to know what fits our team well, what's realistic, what's obviously overengineered, etc... But some of it feels like AI just defaults to the most complex version of a thing. I catch it SUPER frequently. (And unfortunately some devs think that more complexity means it's a better solution)

          • californical · 12 hours ago

            Thanks for posting this! I feel like I’m going crazy, using all of the best models, spending time to have excellent prompts, configuring tools and skills… and still getting overly complex solutions with mediocre results. Like it’s still impressive how far we’ve come, and undoubtably cool technology. It’s made a bunch of personal projects possible that I never would’ve started. But for a business I’m struggling to see the ROI. Sometimes there’s a big benefit and sometimes it’s net negative. Not saying we won’t get there but I’m trying to stay grounded in the reality of today rather than the hopes of where the technology could get to

            • NichoPaolucci · 1 hour ago

              It's brilliant tooling, and made the mundane/tedious parts of my work a lot easier. But, I fear that the "facade of complexity" makes the output SEEM better. Someone might read a 10 page Codex generated plan with fancy diagrams / charts and have a feeling that because it is so complex, it must be good! Same deal with text output in general. Oh, it uses a lot of big words and there's a LOT here, it must have done a lot of work to get to that point. I find, in reality, that it takes much more effort to get to the simplest solution. As they say, any old fella can build a bridge that stands, but it takes an engineer to build a bridge that barely stands...

        • RataNova · 3 hours ago

          Classic tradeoff. Generating syntax is cheap, maintenance is expensive. RN models heavily optimize for the former at the expense of the latter :)

    • jjav · 8 hours ago

      > I feel like anything that I'd trust haiku to handle isn't worth doing in the first place. The trick is making the workload manageable by the cheapest models, or costs will destroy you. We seek to make all repetitive tasks be effectively done by cursor composer model which is the cheapest. Doing recurring tasks with anything more expensive than that will burn the budget in no time.

  • cogman10 · 21 hours ago

    That's what happens when token usage becomes a performance metric. As has been done at my company.

  • onehair · 20 hours ago

    in my company there are a few who keep sharing screenshots of reaching limits on 3 separate subscriptions, 2 of them their personal on top of the company subscription

    • esseph · 19 hours ago

      Wonder when subscription-hopping attacks will become more often (jumping from a personal model to injecting instructions into the business account and exfiling data)

  • nozzlegear · 18 hours ago

    > You can get 99% of jobs and work done with Haiku/Luna in a collaberating working enviroment. You can get the same jobs and work done with Kimi and GLM (ZDR on OpenRouter) for a fraction of the price too.

    • poisonborz · 10 hours ago

      No large companies I know allows chinese models, and OpenRouter is abysmal for enterprise usage. Don't confuse personal/yolo startup usage with corporate use.

  • hexapus · 17 hours ago

    I'm not exactly one-shotting software, but because of the pace I'm expected to keep, I place a lot more trust in the bot that I'm actually comfortable with. I need the job for the time being, so I just keep hitting the button and letting it do its thing until the tests are green. I'm just working in DevOps though, so it's writing IaC, not application code (save the odd Lambda function or python script). Still, even when I spend an entire day conversing with Claude and watching "bot go brrrrr", I'm one of the lowest users in our company. I have no idea what the devs who regularly hit their limits are doing.

  • VCFundedGenYer · 15 hours ago

    That’s just not how any of this works. You’re conceptualizing. In reality, AI is expensive, power consuming, planet destroying, and overall productivity killing.

• password54321 · 22 hours ago

  You realise the subject here is Meta, which is all in on this stuff? Of course they are going to use Muse Spark over Claude. >Great Depression style collapse and all the current AI companies go bankrupt. Oh this is just a 33 day old doomer account.

  • righthand · 21 hours ago

    And yours is a 4 year old hype account?

    • password54321 · 21 hours ago

      Nah, I just respond to a few things here and there.

• righthand · 21 hours ago

  My thoughts were the reckoning would come when Infra teams started offloading AWS usage to LLMs and ended up token maxing and deploy maxing.

• lenerdenator · 21 hours ago

  We're just getting put on a budget. Our velocity is twice as high as it was before Claude, so I doubt that we'll ever go back, but I could see efficiency being a priority.

  • 233mhz · 19 hours ago

    > Our velocity Is this the new buzzword for the quarter? Last quarter was "granularity", I didn't get the memo yet

    • lenerdenator · 19 hours ago

      Is that not a widely-known word in project management circles for scrum and other methodologies? I've heard it for years. Basically how much work you get done through the lens of how long it took to get done via a pointing system.

      • 233mhz · 19 hours ago

        I didn't know people were using these non ironically. Might as well go back to counting the number of lines or number of commits. It doesn't sound as good as "granularity" and "velocity" though. The good thing with velocity is that it doesn't care which way you're going as long as you're going there fast, so you can never be wrong

        • jpleyden98 · 16 hours ago

          > The good thing with velocity is that it doesn't care which way you're going as long as you're going there fast, so you can never be wrong Velocity famously being a vector with a direction. Go in the wrong direction you'd have negative velocity. Your description would be better for the concept of speed (IE the magnitude of velocity or directionless velocity).

  • Gigachad · 19 hours ago

    Does all this velocity translate to increased income to the business though. At some point if we are releasing 20x more features, more games, more music, who is actually buying it all?

    • lenerdenator · 19 hours ago

      At this point we're solidifying a lot of stuff for the product: disaster recovery, getting workflows to scale so we can actually sell it to more people, paying off the Fort Knox of tech debt, so, at least in my case, yeah. YMMV.

      • NichoPaolucci · 15 hours ago

        I'm in a similar boat. When I joined my current company the tech was this 700KLOC legacy behemoth stuck in 2005. It was pretty much all tech debt. With agents I've been able to make a decent sized dent in it. Lots of this gain is due to AI - but the fact of the matter is we still have 50+ bigger projects we could work on, and non-developers building with AI has increased that number. Busier than ever, because of AI.

        • Gigachad · 11 hours ago

          That’s not the original question though. Are there more subscribers to the product now? Certainly more change is getting done, but is the market paying more for it?

          • NichoPaolucci · 6 hours ago

            No, our sales are up slightly YoY. The system is more stable than it has ever been. Customers are more happy. Some of our AI tooling IS “generating revenue”, but not most of it. Much of it is workflow efficiencies and general improvements. One of our big initiatives is cutting out the CRM we use. It’s going to save about 30K a year to do that in house. Our AI bill is going to be sub 30K USD this year, and if you asked the CEO if there was a return on that investment I believe they would be positive. But, I am 100% sure there are multiple companies wasting money on AI and dialing it back because they are NOT getting a return.

• woah · 21 hours ago

  $200 a month is too expensive yet they employ human developers?

  • platinumrad · 21 hours ago

    Corporations pay API rates.

    • proxyscore · 21 hours ago

      So what, if they're cutting it, it has propagated to the last bean counter that the roi isn't there. This takes some doing and now is the time where it's dawning on the finance departments.

      • 233mhz · 19 hours ago

        > So what, So it's not $200 a month but it can easily reach $200 a day, and unless you're a startup playing with monopoly money the maths don't work

        • Chris_Newton · 15 hours ago

          As a point of reference, I tried an experiment with Claude Code and the latest Opus the other day. It was work for my company, so this was using API tokens and not the individual user plans that have non-commercial terms. A simple task, migrating a typical password reset flow as part of updating a long-lived web application from legacy libraries and software architecture to modern equivalents, apparently cost roughly the same as 2 months of Pro subscription, over the equivalent of about half a working day in wall time. It produced code of decent quality at a small scale, but it wasn’t always on point architecturally. It also had a tendency to drift off topic and try to tangle up other changes it decided should be made with the main change we were supposed to be working towards. So even for a routine task, based on a plan developed using the harness first and with the agents working under close supervision, a near-SOTA model is still producing quality on par with a decent mid-level developer but substandard for anyone senior+ in this case. Moreover, based on a direct comparison with other migration tasks of similar complexity that I’d already done by hand, it was actually a bit slower overall to work this way. I had to babysit Claude throughout and review everything it proposed carefully, both to avoid subtle errors (it would have made several) and to prevent drifting off track. I also had to spend a significant amount of time cleaning up its final output to an acceptable standard after the session. Those two overheads more than cancelled out the much faster code generation an LLM offers under favourable conditions. So for now, I remain sceptical about these high multiples of improved productivity that I keep seeing claimed online from people who are apparently writing almost everything using AIs now. I could certainly have achieved a multiple of my normal productivity by YOLOing everything without reviewing it in detail and then accepting the output code without tidying anything up. However, I doubt this codebase would still have been good enough for normal human developers to work on it reasonably after even 10 or 20 AI-led sessions like that. The architecture would have degraded significantly and the test suite would have been large and largely pointless. And again, this wasn’t rocket science in this experiment, it was completely unremarkable maintenance of a relatively small and simple web application.

          • pimeys · 12 hours ago

            Yes. Hundreds of dollars per day is easy to burn with Opus if you pay the API rates. And now if you get the task done faster with the same quality. And the cost is 80 cents, considering DeepSeek and your own server starts to starts to be relevant...

          • 233mhz · 9 hours ago

            Definitely, according to my omp stats I spent the equivalent of $650 opus 5.5 tokens at api price, this model isn't even a month old, I'm exclusively using the $20 plan and I'm not a power user at all: no backround loop, no automated anything, just using it for development and I stay in the loop the whole time

    • IshKebab · 21 hours ago

      I use Opus 5.5 heavily but only spend around $800/week at API rates. I mean, I say "only"... That's a lot in absolute terms, but trivial compared to my salary and EASY worth it.

    • CamperBob2 · 20 hours ago

      And someday I hope to understand why they do that. CEO: "Let's see, I can pay $200/month for Bob's tokens, or I can pay $2000/month or so, and then hope he doesn't screw up and rack up a seven-figure bill. The service is the same either way. Hmm."

      • endless1234 · 19 hours ago

        It's not like they can't decide to pay API or subscription rates. Subscriptions aren't possible for >150 person companies.

        • CamperBob2 · 19 hours ago

          Is there something in the ToS that says you can't give each of your employees a personal $200/mo subscription... and if they happen to use it at work, well, that's their business? Even if so, it might be worth spinning up a separate LLC for each division, given what they are charging for the API.

          • pimeys · 12 hours ago

            You can also ask your employees to bring their own pirated Adobe Photoshop and avoid paying for the license..

            • CamperBob2 · 19 minutes ago

              Nobody's talking about pirating anything.

          • endless1234 · 9 hours ago

            >Is there something in the ToS that says you can't give each of your employees a personal $200/mo subscription Surprisingly, yes.

  • cpncrunch · 21 hours ago

    It's unclear how much OP's company was spending. The article gives a figure of $100k/month per employee. But even $200/month is worth shaving if it doesn't generate value.

    • chrisweekly · 21 hours ago

      $100k/month per employee? um.

      • pimeys · 12 hours ago

        It is called paying per token.

  • AIblemblio · 21 hours ago

    Besides that the article states quite high numbers, budget is budget in these companies. You had budget for your normal salaries, for externals and now suddenly you have a few millions additional. What do you do? You compensate. Business people doing business things.

• dyauspitr · 21 hours ago

  I mean, we’re not far from a situation where instead of how many story points you completed per sprint the metric to optimize is going to be what was your efficiency? How many story points did you complete while minimizing your token usage. In fact, that’s a pretty good idea. I’m going try and implement it at work with some sort of complexity normalization function

• yeahBoiii · 21 hours ago

  The reckoning started years ago when we did the equivalent to token maxxing hiring coders for everything to crank LOC Software is inherently a physics problem not all the job titles and specializations made up the last 20 years as dev job salaries kept attracting people That was all illusory social construct to prop up jobs Still a whole lot of that in tech but it's all at the top of the org now. Leadership sensory experience and thus innate habit to forecast future been programmed by years of yes men they refuse to accept the jig is up for them too Sensory memory of being a useless figurehead fosters a lot of existential dread in priests, politicians, and the like. Completely aware their day to day effort is insufficient to sustain them they know how co-dependent they are. They'll dig in harder. See Chris Matthews flame out shrieking about socialist execution squads. Dude seriously thought everyone wants to hang him from a lamp post. The reality is people just want a sense of control back and not have their perception dragged along by Chris Matthews.

• AIblemblio · 21 hours ago

  The reckoning will be throwing out all external help, then reducing team sizes.

• tty456 · 21 hours ago

  Do you know the details of the Claude Code plan you and your company are using (if not part of some enterprise deal)? Does your individual capacity out run something like Claude Max 20x ($200/mo)?

• user43928 · 20 hours ago

  Good luck to the accountant that tries to tell leadership to slash AI usage. I'm sure investors will love it. Now we're starting to see real impact from AI, people are learning how to use it, and OpenAI cut prices by no less than 60% like a week ago. You think now is the time they're going to cut the spend?

• inferniac · 20 hours ago

  taking away sounds insane, we had basically unlimited tokens (inference bought from aws) and they moved us back to the $100 sub to save money

  • lbreakjai · 18 hours ago

    I've got a 100$ openAI sub through work and I never even get close to reaching the limit. I really wonder what the hell is everyone else doing that they could even get close to spending 4 figures a month in tokens.

• compiler-guy · 20 hours ago

  That's funny. In a meeting with my manager recently, they specifically called me out for not spending enough money on tokens. It's not like I didn't use it, just apparently not enough, and apparently on too low a setting. Since then I've had fable cranked up to 11 for even the most trivial of tasks.

  • aix1 · 13 hours ago

    That's insane. What type of company are you at? (Or even the actual company if you're OK sharing.)

    • compiler-guy · 3 hours ago

      One that is all in on AI, and wants to be sure its engineers are too.

• 233mhz · 19 hours ago

  I know plenty of people working at very well known and very large companies who's CEOs were boasting about "not hiring anyone anymore", "all the code will be generated in 3 months", etc. they all went from "unlimited budget per dev" + public dashboard with ranking to flex how much credits everyone was burning to hard caps at $500-$1000/month/employee real fast. Some are even not allowing their devs to use the more expensive models

• epolanski · 19 hours ago

  My company (me, I'm self employed) did so as well. Since this summer coding on Opencode Go + Codex for a total 28$/month gives me more intelligence and token than 400$ did in may. Also, SOTA models are increasingly useless for anything even barely tangential to security work.

• locknitpicker · 13 hours ago

  > My company took away my Claude because it’s too expensive. My company didn't took away any expensive model, but it did imposed a tight budget and gave my team hardware to run local models. The budget works mainly as an influence on the decision process of which model to run. We can still run expensive budget-burning models if we really want to, but there is a clear incentive to use options that allow us to save our token budget for a rainy prompt. Surprisingly, I feel this had a positive impact on results. Instead of succumbing to extremely expensive one-shot prompts with the most expensive model in the news, chaining agents running cheap models equiped with context and specialized skills and scripts ends up having a better and more reliable output. And faster too. I think there is a lot of propaganda, perhaps even astroturfing, on how only the most expensive models churned out by US companies are worth using. Nowadays the cheapest models get the job done, and local models can already handle most tasks as well specially as part of orchestration chains.

• morgoo · 7 hours ago

  My company gives all employees $2500/month. I tokenmaxxx to make the most of it but have a gut feeling I could get as much work done with 10% of the budget spent on DeepSeek V4.1 Flash and similar models.

If you were wondering the same thing I am - it's not about skills loss, quality, and less about money spent. It's more about frontier AI shops dogfooding their own models.

• tinza123 · 22 hours ago

  Microsoft?

  • ihuman · 22 hours ago

    Copilot

    • NewJazz · 21 hours ago

      That's not a model.

      • therein · 21 hours ago

        If you ask Microsoft, it is a lifestyle.

      • ihuman · 21 hours ago

        True, but its not pure OpenAI GPT. If the point is dogfooding, then they'd use Copilot instead of using OpenAI's models directly

        • 98codes · 21 hours ago

          They do.

      • Zambyte · 17 hours ago

        They had phi for a while. Interesting that they haven't really continued with anything like that.

        • wolvoleo · 17 hours ago

          Phi was more of a research project. Not trained on real world data but synthetic input. That's really good to control if you go for strict limits but it also loses a lot of originality. But it was never a SOTA model.

• wffurr · 21 hours ago

  Meanwhile https://www.reddit.com/r/GeminiAI/comments/1wh0qxq/google_fi...

  • nwhnwh · 21 hours ago

    What in the world is happening?

    • CamperBob2 · 21 hours ago

      Ask Claude

      • nwhnwh · 20 hours ago

        We broke up, ask it yourself.

        • netsharc · 17 hours ago

          I wonder if there's a couple (2 humans) out there where his name is Claude and her name is Alexa... Or Siri.

          • nwhnwh · 4 hours ago

            I wonder what they would talk about?

  • coef2 · 21 hours ago

    This made me laugh https://www.reddit.com/r/GeminiAI/comments/1wh0qxq/comment/p...

  • kelvinjps10 · 21 hours ago

    They give claude usage on antigravity and aren't them a investor on antrhopic?

  • actionfromafar · 20 hours ago

    Life uhhh... finds a way.

  • casta · 20 hours ago

    Talking to my friends working there, they said they were surprised when that happened and they didn't find Claude quality to be that much better than Gemini when using agy. So maybe after all the issue is not mainly the model, but harness and custom tooling.

• ActorNightly · 21 hours ago

  I wonder why they allow it at all. Like its a no brainer to force your employees to use your own models, then RL train them to be better.

  • InsideOutSanta · 21 hours ago

    Or let them use Claude, track everything, and use that data to train your own models.

  • user43928 · 21 hours ago

    If you assume that noisy general usage data enables good RL, particularly compared to curated RL training sets. I am not convinced that's the case.

  • p1necone · 20 hours ago

    Only if all you care about is developing models. I assume the rest of the business would rather just use whatever's best in class regardless of who made it, so I'm sure it's not that straightforward of a decision.

    • locknitpicker · 13 hours ago

      > Only if all you care about is developing models. Is security no longer a concern? When you are using a third party model, you are literally feeding it not only your current software but also all the context and work fronts under development. This is way more than granting a third party access to your internals. This is feeding it in advance updates on all their operations in real time.

      • NewLogic · 7 hours ago

        Rule 2 security went out the door months ago. Nobody seems to give a shit that all unmonitored agent runs hit the trifecta.

    • pimeys · 12 hours ago

      I would say the rest of the business world is looking for price and ROI rather than the best in class.

      • p1necone · 12 hours ago

        Those things fall under the 'best in class' calculus for me.

• nateglims · 21 hours ago

  If it’s anything like AWS there’s hundreds of people making bespoke software factory setups, enhanced interfaces for ai tools, spinning up 10 parallel review agents with the best model available, etc because the budget is basically unlimited.

  • UltraSane · 20 hours ago

    That sounds both very fun and very stressful.

  • seanmcdirmid · 19 hours ago

    Token maxing really is a thing if your token budget is unconstrained.

    • claysmithr · 18 hours ago

      No, because not all work is productive

      • onion2k · 16 hours ago

        Tokenmaxxing doesn't say anything about productivity. It's only about using as many tokens as possible; there's nothing about using them usefully.

        • red-iron-pine · 4 hours ago

          no joke when we were trying test and baseline token use they had us do anything w/ the AI. ask it for recipes, weather, directions, explain baroque art, etc. arguably still a common use case...

          • kingstnap · 1 hour ago

            All these things are sort of irrelevant amounts of tokens. Even if the answers are worthless. Like in my experience the real burn is if there is some sort of feedback edge where an agent is producing stuff that eventually it has to reconsume. Like if there is a dag of agents doing something its almost fine. But if there is a loop somewhere without a huge amount of damping then you have an issue. If you have ever been a human debugging in the middle of an agent it produces like so many commands and tests for you to do. Like way more than a human would. I'm pretty sure they do the same thing to each other. Like the loop will amplify the yapping.

      • seanmcdirmid · 12 hours ago

        If you can use as many as you want but only 1% productively, thats still potentially infinite productivity. Of course, the efficiency is not that great, but more tokens = more productive work. This is only a thing if your token budget is unconstrained, which isn’t sustainable and never lasts.

  • gradus_ad · 19 hours ago

    Tokenmaxxing is just the new pr-maxxing. Proxies truly are the root of all evil.

  • xpct · 18 hours ago

    I find it a bit comical. AI tools are so easy to pick up, and it's unlikely you've pushed some highly critical features which couldn't have waited for a few months.

    • iJohnDoe · 14 hours ago

      You make a good point. That’s why there is AI fatigue. People are moving at speeds that aren’t normal and it’s mentally taxing. If it’s not already a thing, it will be soon, the mental health aspects of all professions moving at unsustainable speeds and what that will do to people.

      • pdimitar · 14 hours ago

        No stakeholder will care, they're high on the illusion they can drain a batch of people and then replace them with fresh meat. Nobody will take care of us. Ever.

        • ponector · 9 hours ago

          But it is not illusion. Everyone knows about conditions at Amazon but they never had an issue to hire people.