>If you haven't spent at least $1,000 on tokens today per human engineer, your software factory has room for improvement
…What am I even reading? Am I crazy to think this is a crazy thing to say, or it’s actually crazy?
>If you haven't spent at least $1,000 on tokens today per human engineer, your software factory has room for improvement
…What am I even reading? Am I crazy to think this is a crazy thing to say, or it’s actually crazy?
The margins on software are incredibly high and perhaps this is just the cost of having maintainable output.
Also I think you have to consider development time.
If someone creates a SaaS product then it can be trivially cloned. So the moat that normally exists becomes non existent. Therefore to stay ahead or to catch up it’s going to cost money.
In a way it’s similar to the way FAANG was buying up all the good engineers. It starves potential and lower capitalised but more nimble competitors of resources that it needs to compete with them.
I am not sure why people are getting hung on the price, i.e. this: "They have the gaul to pitch/attention seek a 1$/day with possibly little/no product". The price can drop TBH and while there is some correlation on $/capita output.
The more nuanced "outrage" here, how taking humans out of the agent loop is, as I have commented elsewhere, quite flawed TBH and very bold to say the least. And while every VC is salivating, more attention should instead be given to all the AI Agent PMs, The Tech lead of AI, or whatever that title is on some of the following:
- What _workflow_ are you building? - What is your success with your team/new hires in having them use this? - What's your RoC for investment in the workflow? - How varied is this workflow? Is every company just building their own workflows or are there patterns emerging on agent orchestration that are useful.
$1k per day, 50 work weeks, 5 day a week → $250k a year. That is, to be worth it, the AI should work as well as an engineer that costs a company $250k. Between taxes, social security, and cost of office space, that engineer would be paid, say, $170-180k a year, like an average-level senior software engineer in the US.
This is not an outrageous amount of money, if the productivity is there. More likely the AI would work like two $90k junior engineers, but without a need to pay for a vacation, office space, social security, etc. If the productivity ends up higher than this, it's pure profit; I suppose this is their bet.
The human engineer would be like a tech lead guiding a tea of juniors, only designing plans and checking results above the level of code proper, but for exceptional cases, like when a human engineer would look at the assembly code a compiler has produced.
This does sound exaggeratedly optimistic now, but does not sound crazy.
It’s a $90k engineer that sometimes acts like a vandal, who never has thoughts like “this seems to be a bad way to go. Let me ask the boss” or “you know, I was thinking. Shouldn’t we try to extract this code into a reusable component?” The worst developers I’ve worked with have better instincts for what’s valuable. I wish it would stop with “the simplest way to resolve this is X little shortcut” -> boom.
It basically stumbles around generating tokens within the bounds (usually) of your prompt, and rarely stops to think. Goal is token generation, baby. Not careful evaluation. I have to keep forcing it to stop creating magic inline strings and rather use constants or config, even though those instructions are all over my Claude.md and I’m using the top model. It loves to take shortcuts that save GPU but cost me time and money to wrestle back to rational. “These issues weren’t created by me in this chat right now so I’ll ignore them and ship it.” No, fix all the bugs. That’s the job.
Still, I love it. I can hand code the bits I want to, let it fly with the bits I don’t. I can try something new in a separate CLI tab while others are spinning. Cost to experiment drops massively.
$250k a year, for now. What's to stop anthropic for doubling the price if your entire business depends on it? What are you gonna do, close shops?
What’s to stop them? Competition.
From whom? OpenAI and Google? Who else has the sort of resources to train and run SOTA models at scale?
You just reduced the supply of engineers from millions to just three. If you think it was expensive before ...
> Who else has the sort of resources to train and run SOTA models at scale?
Google, OpenAI, Anthropic, Meta, Amazon, Reka AI, Alibaba (Qwen), 01 AI, Cohere, DeepSeek, Nvidia, Mistral, NexusFlow, Z.ai (GLM), xAI, Ai2, Princeton, Tencent, MiniMax, Moonshot (Kimi) and I've certainly missed some.
All of those organizations have trained what I'd class as a GPT-4+ level model.
Ah but I said "_... and running at scale_"
Of the list I gave you, at a guess:
Google, OpenAI, Anthropic, Meta, Amazon, Alibaba (Qwen), Nvidia, Mistral, xAI - and likely more of the Chinese labs but I don't know much about their size.
I guess where I was leading to is who owns the compute that runs those models. Mistral, for example, lists Microsoft and Google as subprocessors (1). Anthropic is (was?) running on GCP and AWS.
So, we have multiple providers, but for how long? They're all competing for the same hardware and the same energy, and it will naturally converge into an oligopoly. So, if competition doesn't set the floor, what does?
Local models? If you're not running the best model as fast as you can, then you'll be outpaced by someone that does.
1. https://trust.mistral.ai/subprocessors
A tri-opoly can still provide competitive pressure. The Chinese models aren’t terrible either. Kimi K2.5 is pretty capable, although noticeably behind Claude Opus. But its existence still helps. The existence of a better product doesn’t require you to purchase it at any price.
> The existence of a better product doesn’t require you to purchase it at any price
It does if it means someone using a better model can outpace you. Not spending as much as you can means you don't have a business anymore.
It's all meaningless, ultimately. You're not building anything for anyone if no one has a job.
that worked real well for cloud computing
aws and gcp's margins are legendarily poor
oh, wait
gcp was net negative until last year.
Big part of why clouds are expensive is not necessary hardware, but all software infra and complexity of all services.
All the big clouds are still in market share acquisition mode. Give it about 5 more years, when they're all in market consolidation and extraction mode.
cloud providers indeed could abuse vendor lock, but LLMs are not that easily vendor lockable.
By then perhaps it will be possible to continue with local LLMs
>> $170-180k a year, like an average-level senior software engineer in the US.
I hear things like this all the time, but outside of a few major centers it's just not the norm. And no companies are spending anything like $1k / month on remote work environments.
I mean, it's at best an average-level senior engineer salary, not some exorbitant L6 Googler salary.
Median salary for a software engineer in the US is ~$133k:
https://www.bls.gov/ooh/computer-and-information-technology/...
Define “senior engineer” though..
I think that is easy to understand for a lot of people but I will spell it out.
This looks like AI companies marketing that is something in line 1+1 or buy 3 for 2.
Money you don’t spend on tokens are the only saved money, period.
With employees you have to pay them anyway you can’t just say „these requirements make no sense, park for two days until I get them right”.
You would have to be damn sure of that you are doing the right thing to burn $1k a day on tokens.
With humans I can see many reasons why would you pay anyway and it is on you that you should provide sensible requirements to be built and make use of employees time.
OK, but who is saying that to the llm? Another llm?
We got feedback in this thread from someone who supposedly knows rust about common anti patterns and someone from the company came back with 'yeah that's a problem, we'll have agents fix it.'[0].
Agents are obviously still too stupid to have the meta cognition needed for deciding when to refactor, even at $1,000 per day per person. So we still need the buts in seats. So we're back at the idea of centaurs. Then you have to make the case that paying an AI more than a programmer is worth it.[1]
[0] which has been my exact experience with multi-agent code bases I've burned money on.
[1] which in my experience isn't when you know how to edit text and send API requests from your text editor.
That nobody wants to actually do it is already a problem, but some basically true thing is that somebody has to pay those $90k junior engineers for a couple years to turn them into senior engineers.
The seem to be plenty of people willing to pay the AI do that junior engineer level work, so wouldn’t it make sense to defect and just wait until it has gained enough experience to do the senior engineer work?
It doesn't say 1k per day. Not saying I agree with the statement per se, but it's a much weaker statement than that.
"If you haven't spent at least $1,000 on tokens today per human engineer, your software factory has room for improvement" - how exactly is that a weaker statement?
> 50 work weeks
What dystopia is this?
This is a simplification to make the calculation more straightforward. But a typical US workplace honors about 11 to 13 federal holidays. I assume that an AI does not need a vacation, but can't work 2 days straight autonomously when its human handlers are enjoying a weekend.
There are no human handlers. From the opening paragraph (emphasis mine):
> We built a Software Factory: non-interactive development where specs + scenarios drive agents that write code, run harnesses, and converge without human review.
[Edit] I don't know why I'm being downvoted for quoting the linked article. I didn't say it was a good idea.
I took it as a napkin rounding of 365/7 because that’s the floor you pay an employee regardless of vacation time (in places like my country you’d add an extra month plus the prorated amount based on how many vacation days the employee has), so, not that people work 50 weeks per year, it’s just a reasonable approximation of what the cost the hiring company.
It sounds exaggeratedly crazy.
Meanwhile, me
> $20/month Claude sub
> $20/month OpenAI sub
> When Claude Code runs out, switch to Codex
> When Codex runs out, go for a walk with the dogs or read a book
I'm not an accelerationist singularity neohuman. Oh well, I still get plenty done
The openrouter/free endpoint may make your dog unfit. You're welcome. Sorry doggo.
Different beasts on the API, the extra context left makes a huge difference. Unless there's something else out there I've missed, which at the speed things move these days it's always a possibility.
same (at least for now, Codex seems to be much more token efficient)
I'm one of the StrongDM trio behind this tenet. The core claim is simple: it's easy to spend $1k/day on tokens, but hard (even with three people) to do it in a way that stays reliably productive.
My favorite conspiracy theory is that these projects/blog posts are secretly backed by big-AI tech companies, to offset their staggering losses by convincing executives to shovel pools of money into AI tools.
They have to be. And the others writing this stuff likely do not deal with real systems with thousands of customers, a team who needs to get paid, and a reputation to uphold. Fatal errors that cause permanent damage to a business are unacceptable.
Designing reliable, stable, and correct systems is already a high level task. When you actually need to write the code for it, it's not a lot and you should write it with precision. When creating novel or differently complex systems, you should (or need to) be doing it yourself anyway.
Is it really a secret, when Anthropic posted a project of building a C compiler totally from scratch for $20k equivalent token spend, as an official article on their own blog? $20k is quite insane for such a self-contained project, if that's genuinely the amount that these tools require that's literally the best possible argument for running something open and leveraging competitive 3rd party inference.
An article over, these claims are exaggerated - they have dumped the tinycc compiler, not written one from scratch.
tinycc wasn't written in Rust.
Like this?
https://www.cnbc.com/2026/02/06/google-microsoft-pay-creator...
Provided the sponsored content is labelled "sponsored content" this is above board.
If it's not labelled it's in violation of FTC regulations, for both the companies and the individuals.
[ That said... I'm surprised at this example on LinkedIn that was linked to by the Washington Post - https://www.linkedin.com/posts/meganlieu_claudepartner-activ... - the only hint it's sponsored content is the #ClaudePartner hashtag at the end, is that enough? Oh wait! There's text under the profile that says "Brand partnership" which I missed, I guess that's the LinkedIn standard for this? Feels a bit weak to me! https://www.linkedin.com/help/linkedin/answer/a1627083 ]
There's about a hundred new posts on reddit every day that im sure are also paid for from this same pile of cash.
It feels like it really started in earnest around october.
I'm also convinced that any post in an AI thread that ends with "What a time to be alive!" is a bot. Seriously, look in any thread and you'll see it.
Slop influencers like Peter Steinberger get paid to promote AI vibe coding startups and the agentic token burning hype. Ironically they're so deep into the impulsivity of it all that they can't even hide it. The latest frontier models all continue to suffer from hallucinations and slop at scale.
https://github.com/steipete/steipete.me/commit/725a3cb372bc2...Secretly? Most blog posts praising coding agents put something like 'I use $200 Claude subscription' in bold in 2nd-3rd paragraph.
I don't think that's really a conspiracy theory lol. As long as you're playing Money Chicken, why not toss some at some influencers to keep driving up the FOMO?
Yeah, it's hard to read the article without getting a cringy feeling of second hand embarrassment. The setup is weird too, in that it seems to imply that the little snippets of "wisdom" should be used as prompts to an LLM to come to their same conclusions, when of course this style of prompt will reliably produce congratulatory dreck.
Setting aside the absurdity of using dollars per day spent on tokens as the new lines of code per day, have they not heard of mocks or simulation testing? These are long proven techniques, but they appear bent on taking credit for some kind revolutionary discovery by recasting these standard techniques as a Digital Twin Universe.
One positive(?) thing I'll say is that this fits well with my experience of people who like to talk about software factories (or digital factories), but at least they're up front about the massive cost of this type of approach - whereas "digital factories" are typically cast as a miracle cure that will reduce costs dramatically somehow (once it's eventually done correctly, of course).
Hard pass.
Yeah, getting strong Devin vibes here. In some ways they were ahead of their time in other ways agents have become commoditized and their platform is arguably obsolete. I have a strong feeling the same will happen with "software factories".
It's crazy if you're an engineer. It's pretty common for middle managers to quantify "progress" in terms of "spend".
My bosses bosses boss like to claim that we're successfully moving to the cloud because the cost is increasing year over year.
Growth will be proportional to spend. You can cut waste later and celebrate efficiency. So when growing there isn't much incentive to do it efficiently. You are just robbing yourself of a potential future victory. Also it's legitimately difficult to maximize growth while prioritizing efficiency. It's like how a body builder cycles between bulking and cutting. For mid to long term outlooks it's probably the best strategy.
Appropriate username.
This is some dumb boast/signaling that they're more AI-advanced than you are.
The desperation to be an AI thought leader is reaching Instagram influencer levels of deranged attention seeking.
It's not so much crazy as very lame and stupid and dumb. The moment has allowed people doing dumb things to somehow grab the attention of many in the industry for a few moments. There's nothing "there".