or maybe they don’t actually cache (fully) but lie and just don’t charge the user right now. at least half the users, who are probably also using the most similar tokens / prompts, wouldn’t really know the difference in latency (or care)
If it actually cost that much RAM, they would almost certainly add extra things to the API to manage cache lifetime. Ie. A 'please cache this for X minutes' flag, or a setting for a single re-use cache (the most common use case)
> credit card itself can’t be used to ad targeting
Incorrect.
Credit card networks / issuers explicitly describe using payment, spending, and your personal data,
for marketing, personalization, audience segmentation, and advertising.
Mastercard’s privacy notice states that it may use personal and transaction-related information to:
“Provide you with personalized services and recommendations”
“Offer and support loyalty programs”
“Provide content and advertising tailored to your individual interests”
“Analyze spending behavior to improve the effectiveness of marketing programs and advertising.”
Visa has also historically offered an opt-out specifically for using card transaction data…
If only I could get rich, structured data access to my spending data... but many banks only allow pdf statement downloads, in inconvenient ways, and their UIs for drilling down into data...
Because Jane Street is unabashed about greed, and yet they do not let that greed lead them into attempting to pollute and derive us of our attention every day.
Isn’t this sort of just “chain of thought” (i.e. the seminal https://arxiv.org/abs/2201.11903 ) where the user is helping the model 1-shot or k-shot the solution instead of 0-shot? I’ve used a similar technique to great effect. I feel things are so new / moving so fast that it’s hard to have common lingo. So very helpful to have a blog / example! But I wonder if the phenomena has been seen / understood before and just in smaller circles / different name.
While I like that you debunked the article . . . I want to hear an argument for where the SWE job market can grow in a post-Claude world. I might expect something like: “CEOs are naturally greedy. So after trimming the team, they then recognized (versus “replacing” people with AI) they could actually accomplish _more_ with more engineers, each empowered with AI.
But I do like folks calling out the OP for being AI spam.
I'm not sure whether it's AI spam, or somebody at an investment company who actually writes like that. It's an exaggerated version of the style in McKinsey reports.
They're addressing a very important question, and one for which there is surprisingly little hard data. It's too soon to try to see a trend from low-quality data. Three years of this data might be meaningful.
I don't work in IT but I use and love Claude code. What strikes me is maybe the overall software job market can not grow to surpass the post covid peak but any current professional software engineer has immensely valuable skills that can no longer be gained in the same way, if at all.
I would think the counter argument to the greedy CEO argument is that AI breaks the former economy of scale in the opposite direction towards hyper specialization in business with small teams. In that scenario, as the economy grows with more and more business, the current software engineers are the substrate for a new type of off brand bargain CTO as opposed to the current , luxury brand CTO sitting at the top of oversized companies.The bull market becomes at the higher level that current software engineers step into.
Most likely though, none of this is true and 15 years from now it all shakes out in a way that none of us could have really predicted from our vantage point because the prediction would sound ridiculous with the information at hand.
Computing cost and reliability remains the bottleneck. AI agents are nowhere near smart enough to carry out tasks on their own. Combined with the fact, 95% of gen-AI pilots "failed" [1], at least failed to improve the bottom line. Layoffs were never about AI, they were almost always about capex, and correcting the pre-2022 overhiring. All CEOs are hearing in 2026, "I didn't get anything done, but the model hit the limit".
However, if there will be, locally deployable, meaningfully capable AI models that can change the computing cost equation.
It really depends on how you define a software engineer. If you mean software engineers doing what we do today, the market probably won’t.
If you just mean “people who make software in any capacity”, it will probably grow (or has already grown) via product, marketing, etc folks making internal tools with AI (which may not work out, we’ll see).
Presuming we keep seeing LLM improvements, SWE will move up the stack like they did in the past. They used to work directly with hardware and software. Ops folks sprung up to do the hardware, and SWEs do basically all software using abstractions over hardware. This will be another step up where SWEs no longer work directly on software, but rather on the tooling that writes software which they hand over to marketing, HR, etc.
Again, presuming this all works out the way the AI folks plan.
The world runs on software. AI makes it easier to create more software, but it still requires humans to keep running and decide what to do. Maybe each individual project will need less pure coders, but there might be a lot more projects?
As long as software engineers are needed to leverage AI (they can manage the output, refine the prompts, check the BS), there is plenty of software to write and not having SWEs still means you will have to write less of it.
It’s not cutting corners. Apple does most of their testing using strictly internal resources, like secret “mini malls” in the Silicon Valley area. They fail because this testing biases their sampling; users must sign draconian NDAs to participate, among other things. These samples are effectively biased due to Apple’s corporate culture regarding secrecy and competition. So, Apple actually works very hard. It’s just they culturally prefer a lot of techniques that their competitors (e.g. Google and Facebook) have throughly proven as inferior.
But is Google better? Not really, they killed a lot of good products like Reader.
But is Facebook better? Not really, Cambridge Analytica and Metaverse and .. facebook products are disposable.
But I think these Apple UX bugs are misdiagnosed. Yes they are atrocious. But think about how atrocious and non-representative and non-competitive Apple’s testing population is.
This all is pretty curious! But my point is that every developer involved would notice how crazy the end result is. No need for a focus group to demonstrate that emperor's new clothes barely cover the body, and don't match the body parts.
But nobody from likely hundreds of people inside Apple involved in the project was able to effect a change towards sanity. I'm afraid many just didn't feel like speaking.
In the spirit of not being intimidated, I am going to just say what I’ve been wondering; if this could be a result of the oppressive nature of all the “DEI” stuff at Apple having turned into a kind of intimidation cudgel. Are you going to speak out and point out the emperor has no clothes if doing so will have your head?
The circular self-congratulation of DEI introduces an intimidation factor where the objective and scientific truth is inherently no longer the basis for decision making because there are multiple layers of a kind of aristocratic privilege that cannot be questioned, let alone criticized, because critique of their actions equals critique of their divinity, i.e., becomes heresy.
So we end up with this point where no one pointed out the increasingly ridiculous reductions of the emperor’s clothes, only ever cheering on with positive affirmations, to the point that everyone’s intimidated to even point out the emperor is walking around stark naked.
I could see how a combination of the DEI intimidation tactics with the advent of AI, the hash economic factors, and general desire to not rock the personal benefit boat could have resulted in institutional paralysis.
Is there anyone with a force of personality left at Apple? Ultimately, this is on Cook as the Chief Executive Officer poorly executing. It really makes you wonder if the leadership doesn’t actually use any of their own company’s products. How do you not notice these glitches immediately like everyone else if you are using them? I could see Cook not having even regularly used an iPhone or actively interacted with any Apple product himself in years as his real life Siris around him do every single thing for him every day all day, besides maybe giving him briefs on screens that happen to be iPhones and iPads. At that level you actively have to make choices to remain connected to the ground. I doubt Cook finds being grounded comes easy.
I didn't immediately jump to it, but here's why I mentioned it. DEI is essentially nothing more than "brown nosing", as you put it; manipulation of various factors for personal gain.
In DEI type con jobs, it is just administered by an odd and even contradictory hodgepodge of people/identities who are hijacking different characteristics, or more accurately, maybe manipulating characteristics differently.
Where brown nosing also manipulates things like flattery, currying favor, narcissistic positioning and sabotage; DEI manipulates things more like sympathy, graciousness, generosity, and empathy. At the same time is also employs psychological and emotional coping mechanisms, like gratuitous pride and affirmation, while also making heavy use of rather harmful personality traits like shaming, blaming, blame shifting, cooption, purloining, appropriation, and emotionally abuses people generally.
It's all very common and typical of extreme and malignant narcissism, including the put on, fake self-congratulation you often see the DEI type crowd engaging in where they lay on the affirmation of equality and equity so heavily that it usually just highlights the contradiction with reality most people experience.
Appreciate the nature and scale of the internet... and also how it's changing though, yeah?
While I agree with much of the article's thesis, it sadly appears to ignore the current impact of LLMs ...
> it’s never been easier to read new ideas, experiment with ideas, and build upon & grow those ideas with other strong thinkers on the web, owning that content all along.
But, "ownership" ? Today if you publish a blog, you don't really own the content at all. An LLM will come scrape the site and regenerate a copyright-free version to the majority of eyeballs who might otherwise land on your page. Without major changes to Fair Use, posting a blog is (now more than ever) a release of your rights to your content.
I believe a missing component here might be DRM for common bloggers. Most of the model of the "old" web envisions a system that is moving copies of content-- typically verbatim copies-- from machine to machine. But in the era of generative AI, there's the chance that the majority of content that reaches the reader is never a verbatim copy of the original.
1) Assume the buyer/seller holds capital from sources that the majority of the market considers “illicit” and/or is legally sanctioned and/or physically frozen or restricted. Aka the capital can never be called (or at a discount that is unknowable) or the transaction could be later legally reversed or nullified by one or more legal entities. But of course the StableCoin market maker fails to communicate this risk. Therefore the real value of either side of the trade could be zero despite the non-zero StableCoins being transferred. Thus that’s not really a “trade” because there are hidden substantial risks.
2) Along the lines of Matt Levine “Stablecoin treasury strategy?” Consider that the buyer is a publicly listed company, and they fundraise based upon purchase of the digital asset. Then you are doing what most banks consider is not trading but fueling speculation (and normally you can’t expose average retail investors to these risks).
The innovation of StableCoins is much less about Capitalism and much more about re-packaging fraud. And given how lax the prosecution of fraud was during the Financial Crisis, there’s a big meta-bet that StableCoin “traders” will never face losses.
>Assume the buyer/seller holds capital from sources that the majority of the market considers “illicit” and/or is legally sanctioned and/or physically frozen or restricted
This is not feasible legally, and is where your claim falls apart.
From the now-passed GENIUS act [0] which regulates the stablecoin issuer:
- "Permitted payment stablecoin issuers must maintain reserves backing outstanding payment stablecoins on at least a one-to-one basis, consisting only of certain specified assets, including US dollars and short-term Treasuries."
Their point is that if the money held in reserve are proceeds from criminal activity, it is possible for the assets to be seized or frozen by the feds (which would render them no longer backed 1-to-1 even if they were before then). The text of the law you quoted doesn't really change anything.
I see, I misread: that’s interesting. I would assume the issuer would still be liable to resolve the backing, but yeah I could see how that poses systemic risk.
I also don’t think such a risk could realistically remain hidden - this is still going to be heavily regulated and audited, and industry will wise up to the sorts of risk that emerge.
uv can also run even a beefy linux desktop out of file descriptors for larger projects. And does not have deterministic / reproducible installs. Still needs maturity.
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