Increased complexity of your systems.
Increased pipelines of your system.
You might reduce the likelihood of errors, but at an overproportinal cost of time it takes to complete (which some might argue is irrelevant, but has the cost of human context), and with an way higher time and focus needed for all bugs that the system doesnt work.
You’ll have to fix adapt and maintain all your verification layers, because just because you set them up they are not perfect.
Your testing pipeline becomes incredible slow and you need to maintain it as well.
It’s tremendously weaker than a hands-on approach.
I’ve written this exact same article in January and since then completely switched my position.
Good luck on everyone trying this. You shuffling your own grave and waste time.
Now what percentage of the 200$ have been used on the useful stuff and how much on exploration or other stuff.
How long would it taken you to do it yourself? How much longer will the next task take you, compared to when you would’ve written the code yourself. How is the mental model compared to when you would’ve written it yourself?.
I’m not saying you’re wrong, again there are use cases. But the calculation is not plain and simple it goes deep into our perception, perceived productivity versus actual productivity.
I’ve 2 months maxxed out all 6k of Claude Code and bought Antigravity on top. My codebase became 140k lines. I introduced tons of bugs and spent another 2 months, deleting 80k of code. I wish I would’ve just chatted with AI and not let agents touch my codebase. I would’ve saved approx 300$ subscription prices a month and 2 months of my life.
I had that experience back in January! I used it for a joke in a talk recently... did anyone really need a half-finished buggy slow implementation of a JavaScript interpreter in Python? They did not.
https://github.com/simonw/micro-javascript
It's taken me the best part of this year to readjust and find a pace and level of ambition that fits.
It was challenging for me as well, but my pace and level is now that I use it for these cases at the moment:
New language, infrastructure, general level of understanding of something I barely have an idea of.
Rubber duck debugging, if i dont know the correct solution
Checking my code for issues and bugs.
But not for:
- writing my code
- agentic coding (help me)
The inference has reduced drastically. It’s basically just chatting. I don’t let it write anything, but sometimes I purposely use the browser window instead of them sitting in my codebase, because I know it gets things subtly wrong and migth focus on the wrong things.
The same way people used to say don’t copypaste code at least write it out I think it’s still true. It helps to buidl the mental model and to find the right abstractions.
I know everything you’ve done for the tech community, but I please you to take some time off and reflect on this article. It’s not on par with ur usual level, but the tendency has been visible from the last couple of articles.
I thought this was one of my best pieces of writing this year.
(In case you missed it, the title was meant as a subtle burn on those two companies - it's pretty absurd for them to only just be finding product-market fit when they're already valued at over a trillion dollars.)
- The first argument about your subscription price, doesn’t has anything to do with the overall claim of the article. It would if at all be a weak argument to support the opposite. Subsidizing prices signals a lack of PMF.
- That you hire sales people after you had a billions of funding is nothing surprising and doesn’t indicate PMF or not.
- AI Implementations are fresh and of course AI Failures are thin, but so are AI successes. I haven’t seen any companies creating billions of shareholder value because they’ve massively invested in AI and their competitiors didn’t You really can look at these things in 5 to 10 years and it is multi-faceted including cultural acceptance.
- That they need to buy more compute to satisfy the requests is probably the strongest argument in the artical, but don’t conclusive. The product is been sold heavily subsidized and in hype cycle. And again both OPENAI and Anthropic have to show growth in order to justify the IPO.
- Regarding the part about revenue I refer to the linkedm article above, as it does explain it very well.
The conclusion is reasonable given the arguments, but not the title.
However it is missing all the real discussion points that are actually in observation at the moment.
Local models as alternatives, IPO finanical engineering, how AI implementation actually will perform over years... Let’s all not forget crypto. It’s been full of "use cases" just a bunch of years ago. I like the idea of crypto(btc,eth) and I’m still invested, but 99.99% of coins have died on promies.
So this is not a piece of critical thinking, but this reads like a twitter thread to sell me a course :/
I have to give them kudos. This whole thing is the greatest swindle of all time.
AI has some use cases, but not at the price it’s currently priced at. I’ve been on AI since GPT-2 with a lot of heavy users. Every user has the same story, curiosity, surprise, hype, hate, realization. Enterprise is usually a bit behind and are right now at hype cycle, that’s where they sold all the deals and do the IPO.
It’s really a VC masterclass.
Don’t get me wrong there is are useful cases of AI, but not the way the want it to be. Quite similar to Blockchain. The idea of decentralized money has right to exist. 99% of other coins not.
AI is a faster, but still less accurate search engine. AI is great in finding bugs, it’s great at ruber duck debugging.
The reason I call it a swindle is, because along with the marketing it gives tons of people in the world the impression, they can now build their own startup, game, infra etc without the need to learn it themselves. This leads to millions of abandoned and low qualiy projects and products, because the vast majority has never built the mental modal necessary to solve the problem thoroughly. In the end they’ve wasted months and money (but burnt tokens). This is what I call a swindle.
All early adaptors I know have not drastically winded down their usage, not because of money, but because there is no new case. If you want to explore a new project you can get onboarded quickly learn a lot and then switch to documentation and live testing. For me usage is the lowest it has been the last 2 years.
I would not let AI touch my code. I have anxiety around it, because it will gripple back up. I will let it read my code and let me know what I did wrong so I’m sharpening myself.
100s of companies including open source solution can offer that for me.
All my non-tech friends are now in hype cycle and share their hype and fore forseeable frustration with me.
I have to say I’m in a way impressed in how AI has been rigorously vc-utilized (conciously or not-conciously) to generate these vast companies with the whole world watching.
Trying to parse the raw claims here maybe you can help me out
- it’s a swindle because ROI of tokens for coding models is not positive? As in it doesn’t bring enough value to charge like the $100/mo?
- enterprise customers are too dumb to see this
- IPO to max out the CEO profits for what is ultimately blockchain vaporware
Am I getting that right? Or am I putting words in your mouth?
> it gives tons of people in the world the impression, they can now build their own startup, game, infra etc without the need to learn it themselves.
I can’t speak for peoples beliefs and motivations, but this seems to be strawmanning, no? AI is a powerful tool to force multiply people. You can’t just prompt “build me an enterprise SaaS app worth $1B” or “build me GTA6 and don’t hallucinate” but is that your impression of what’s happening? Dario and Sam are saying “if you buy our coding agent subscription you can build a game with zero skill and one shot and then be rich”?
If you don’t find value in AI agents I can see reasons why that could easily be true today. Also if it just gives you the heebie-jeebies. But to say it’s a swindle on par with the blockchain I think that contradicts an enormous amount of signals and also the actual dialogue (not just headline sound bytes) around what these systems are capable of today and what we expect them to do say at the end of the year.
You kind of got it right, but the biggest loser of them all are the investors especially the index investors. They don’t even decide what they invest in but the savings that goes in funds need to invest in these stocks.
It’s quite an elaborate swindle obviously. But you generate hype with underselling your core product, you claim way more usability then there is. Users will experience usability initially. Everything multiplies with each other and then you put it on the market. Everybody involved makes money and you’ve succesfully extracted money from everyone who’s invested in NASDAQ index funds at the very least.
> Dario and Sam are saying “if you buy our coding agent subscription you can build a game with zero skill and one shot and then be rich”?
That’s Anthropics marketing, yes.
Also their offering is not uniqe that justifies a 1 trillion valuation. The first companies are already rowing back. It’s a really certain time window that they are about to hit now with their IPOs
The companies that have signed these enterprise deals haven’t done a ROI analysis. They had Fomo.
> you generate hype with underselling your core product, you claim there’s way more usability than there is
Isn’t this a contradiction?
> Everything multiplies with each other and then you put it on the market. Everybody involved makes money and you’ve succesfully extracted money from everyone who’s invested in NASDAQ index funds at the very least.
Sorry I may have totally missed what you’re saying here. Anyone in S&P has already made a lot of money thanks to effects from these companies. No one has to invest in an index fund. Markets have risk…
> That’s Anthropics marketing, yes.
Show me.
> Also their offering is not uniqe that justifies a 1 trillion valuation. The first companies are already rowing back.
That there is competition doesn’t imply they aren’t worth 1 trillion.
> The companies that have signed these enterprise deals haven’t done a ROI analysis. They had Fomo.
Also…wrong. I have seen the data at my company, everyone at scale tracks this.
I don’t remember ever hearing Dario or Sam recommend replacing people. Rather they say that smaller groups of people can do more work, so hiring will slow because small teams can do more.
The only times when people talk about actual full replacement of people is always when they are talking about some “future AGI” that is far more capable than the tools we have today.
That happened to my project as well. The main issue hasn’t beet that ai couldn’t solve the problem, but it became so slow and you need more and more verification layers and CI/CD that at one point you wish a simpler codebase back, with reasonable tests, with storylines in codes and so on.
Not a recommendation per se but I used to use Amphetype on Gutenberg texts to practise touch-typing. There's something about writing out a book that hits differently to reading it. You skip less, odd parts stick with you.
I think the last one I tried was The Island of Dr Moreau.
This will go down in history as the biggest mistake of software engineering of all time.
Bun is the runtime of Claude Code, which is the core product of a trillion dollar company, which now sits on a vibe-coded app, where not a single person in the world has a proper mental model of.
Claude Code itself is purely vibecoded, both CC and Bun leads are saying that humans are not writing code at Anthropic anymore. It is amazing how much money they intend to squander, because it's all funny money to them, investors just give it to them hand over fist for them to burn. Developing wrappers around the model isn't even the hard part and yet they're going to burn themselves to the ground getting high on their own supply.
> Claude Code itself is purely vibecoded [...] money they intend to squander [...] going to burn themselves to the ground getting high on their own supply.
This really really really isn't the burn you think it is. Going from 0 to 2B+ in revenue from a "purely vibecoded" thing is what they've said they're doing, and what they've actually done. Like in already done. It's not going back, no matter how many nuh nuh people write. They've already shown this can be done.
People will continue to think that this is some sort of a gotcha. But it's actually precisely what they've done: they showed that dogfooding works. If this works, why not x y z?
2B+ in revenue on hundreds of billions in investments and future commitments is completely worthless. Anybody can turn $100b into $2b, that's not a fucking accomplishment. And to the extent that something is driving any revenue, it is the model, not the TUI. Any success Claude is having is despite the godawful TUI, not because of it.
claude.ai (their chatgpt equivalent) was nowhere before cc came about. CC was coded in a few weeks by people, then a few months by people + cc, then mostly cc take the wheel. It is without a doubt the main reason why they're successful. It is also the main reason why their coding models are as good as they are. They've incorporated the early data into their training recipes, and evolved model + harness together.
They appear to be lining up a funding round at a $900 billion dollar valuation. Or to be more conservative they already raised at $380 billion. A long way from worthless.
Yeah are we all forgetting that VC valuations are based on hope and unicorn farts? Just because you give a company $100 billion doesn't turn it into a $900 billion company. Especially when said company has only generated $5billion in total revenue:
I really wish I could tell people my LLC is worth $100 million because I sold a 0.0001% stake for $10k but I would be called a fraud; however if I was to gamble with pension funds and make the same claim suddenly I'm a visionary?
Good lord, no wonder people want to torch data centers.
Maybe this is the best marketing trick for Claude Code ever. Maybe there was pressure from Anthropic to do this and prove the value. Even partial success is enough to prove the value, justify the value and usage, and AI dependency even further.
Running the rust version in their prod for two weeks should be long enough to catch the biggest crashes and fix them. I'll be up to bug bounty hunters to find the big one that crashes all their app servers at once.
My initial reaction was that this is pure insanity but in fairness this is a fairly 1:1 port of existing code, so the developer's mental model of it should still match fairly well.
I did pick that at random but it does look like the best case. I skimmed through a lot of the Rust code and there's a surprisingly small amount of `unsafe`.
Still pretty insane to merge this in such a short time with so little testing, but I can easily think of bigger software engineering mistakes. Hell it's not like Bun even needs to be commercially successful any more.
Well, realistically as well, humans gave us softwares that are full of security holes (and bugs), which one have you seen that a human perfected on the first time around? Give AI some time as well to be fair.
Increased complexity of your systems. Increased pipelines of your system.
You might reduce the likelihood of errors, but at an overproportinal cost of time it takes to complete (which some might argue is irrelevant, but has the cost of human context), and with an way higher time and focus needed for all bugs that the system doesnt work.
You’ll have to fix adapt and maintain all your verification layers, because just because you set them up they are not perfect.
Your testing pipeline becomes incredible slow and you need to maintain it as well.
It’s tremendously weaker than a hands-on approach.
I’ve written this exact same article in January and since then completely switched my position.
Good luck on everyone trying this. You shuffling your own grave and waste time.
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