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North American Leadership

Apr. 21st, 2026 10:30 pm
[syndicated profile] digby_feed

Posted by digby

It isn’t us

On Carney’s speech:

 Canadian Prime Minister Mark Carney said in a video address released Sunday that Canada’s strong economic ties to the United States were once a strength but are now a weakness that must be corrected.

In the 10-minute address, Carney spoke about his government’s efforts to strengthen the Canadian economy by attracting new investments and signing trade deals with other countries. The world is more dangerous and divided,” Carney said. “The U.S. has fundamentally changed its approach to trade, raising its tariffs to levels last seen during the Great Depression.

“Many of our former strengths, based on our close ties to America, have become weaknesses. Weaknesses that we must correct.”

Carney said tariffs imposed by U.S. President Donald Trump have affected workers in the auto and steel industries. He added that businesses are holding back investments “restrained by the pall of uncertainty that’s hanging over all of us.” Many Canadians have also been angered by Trumps comments suggesting Canada become the 51st state.

Carney said he plans to give Canadians regular updates on his government’s efforts to diversify away from the U.S.

“Security can’t be achieved by ignoring the obvious or downplaying the very real threats that we Canadians face,” he said. “I promise you I will never sugarcoat our challenges.”

He’s right to do it. The US has chosen (barely) to become a rogue nation. Other countries, even — especially — our allies have to protect themselves.

Carney is what a smart, mature, strong person( as opposed to a stupid, infantile bully) sounds like. I’m worried that too many of us have lost the ability to tell the difference.

james_davis_nicoll: (Default)
[personal profile] james_davis_nicoll
And I know 700 pages PDFs are a vote-loser.

Any of my reviews from 2025 that people especially liked?
[syndicated profile] wheresyouredat_feed

Posted by Ed Zitron

Executive Summary: 

  • Anthropic appears to have removed access to Claude Code for its $20-a-month "Pro" Plans.
  • Current Pro users appear to still have access via the Claude web app.
  • Claude Code support documents exclusively refer to accessing Claude Code via "your Max Plan," after previously saying you could access "with your Pro or Max Plan."

In developing news, Anthropic appears to have removed access to AI coding tool Claude Code from its $20-a-month "Pro" accounts. This is likely another cost-cutting move that follows a recent change (per The Information) that forced enterprise users to pay on a per-million-token based rate rather than having rate limits that were, based on researchers' findings, often much higher than the cost of the subscription.

Update: Anthropic's Amol Avasare claims that it is "...running a small test on ~2% of new prosumer signups. Existing Pro and Max subscribers aren't affected." This does not really make sense given the fact that all support documents and the Claude website reflect that Pro users do not have access to Claude Code.

I am waiting for further comment.

Previously, users were able to access Claude using their Pro subscriptions via a command-line interface and both the web and desktop Claude apps. Users were, instead of paying on a per-million-token basis, allowed to use their subscription to access Claude Code, but will likely now have to pay for API access.

Anthropic's Claude Code support documents (as recently as this April 10th archived page) previously read "Using Claude Code with your Pro or Max plan." The page now reads "Using Claude Code with your Max plan."

Pricing on Anthropic's website reflects the removal of Claude Code on both mobile and desktop.

alt
alt

Some Pro users report that they are still able to access Claude Code via the web app and Command-Line Interface.

It is unclear at this time whether this change is retroactive or for new Pro subscribers, or whether Anthropic intends to entirely remove access to Claude Code (without paying for API tokens) from every Pro customer.

I have requested a comment from Anthropic, and will update this piece when I receive it, or if Anthropic confirms this move otherwise.


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It’s $70 a year, or $7 a month, and in return you get a weekly newsletter that’s usually anywhere from 5,000 to 18,000 words, including vast, detailed analyses of NVIDIA, Anthropic and OpenAI’s finances, and the AI bubble writ large. I recently put out the timely and important Hater’s Guide To The SaaSpocalypse, another on How AI Isn't Too Big To Fail, a deep (17,500 word) Hater’s Guide To OpenAI, and just last week put out the massive Hater’s Guide To Private Credit.

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Hugo Finalist Votes 2022 - 2026

Apr. 21st, 2026 06:30 pm
james_davis_nicoll: (Default)
[personal profile] james_davis_nicoll
                  2022   2024   2025   2026   
Novel             1151   1420   1078   1153
Novella            807    962    739    807
Novelette          463    755    394    414  
Short Story        632    720    610    507
Series             707    677    621    687
Graphic/Comic      340    457    265    362
Related            453    775    431    479
Dramatic, Long     597    763    610    650
Dramatic, Short    386    490    451    471
Game               --     334    298    357
Editor, Short      319    530    322    305
Editor, Long       182    254    162    234
Pro Artist         233    270    214    228
Semiprozine        312    338    334    324
Fanzine            243    286    243    224
Fancast            384    693    376    370
Fan Writer         368    363    329    308
Fan Artist         230    180    186    176
Poem                --     --    219    202
Lodestar           451    345    268    244
Astounding         416    349    341    290

[ SECRET POST #7046 ]

Apr. 21st, 2026 05:39 pm
case: (Default)
[personal profile] case posting in [community profile] fandomsecrets

⌈ Secret Post #7046 ⌋

Warning: Some secrets are NOT worksafe and may contain SPOILERS.


01.


More! )


Notes:

Secrets Left to Post: 01 pages, 20 secrets from Secret Submission Post #1006.
Secrets Not Posted: [ 0 - broken links ], [ 0 - not!secrets ], [ 0 - not!fandom ], [ 0 - too big ], [ 0 - repeat ].
Current Secret Submissions Post: here.
Suggestions, comments, and concerns should go here.

Oops

Apr. 21st, 2026 09:00 pm
[syndicated profile] digby_feed

Posted by digby

Krugman on “the vindication of Bidenomics”:

Consumer sentiment, which fell off a cliff in 2022, has declined further under Trump II. Indeed, according to the venerable Michigan Survey, it is at the lowest level ever recorded. Other measures, like the index of consumer confidence produced by the Conference Board, are somewhat less dismal but also show that Americans feel worse now than they did during the Biden years. And as the chart above shows, Americans — a crucial segment of whom voted for Trump because they believed his fabulist promises to bring prices down “on Day One” — are now saying that the Biden economy was better than the Trump II economy.

[…]

Let me address three issues in particular: Purchasing power, inequality, and the labor market.

Purchasing power: Biden had the misfortune of being president when there was a large jump in prices, a jump that was out of his control and happened around the world. This came as a shock to Americans after decades of low, stable inflation This price jump clearly depressed consumer sentiment. However, it’s often asserted that the jump in prices from 2021 through 2022 left most Americans substantially poorer. And that just isn’t true…Using the eve of the pandemic as a baseline, we see that large increases in consumer prices were more than matched by large increases in wages:

Aaaaand he says that thing that nobody wants to hear when they are pointing out that people were hurting nonetheless:

[T}hroughout the past 5 years many millions of Americans have had a hard time making ends meet. But this is always true, in good times and bad. It was actually less true than usual during the Biden years, a period in which wages at the bottom rose more rapidly than wages at the top.

That was a stunning reversal of everything that was happening before or since.

People were traumatized by the pandemic and prices were higher and everything was upsetting. It’s the main reason every country in the world was tossing out their incumbents. We just had the misfortune of having the worst president in history still owning one of the parties and determined to take another bite of the apple.

On inequality:

The economist Peter Atwater coined the term “K-shaped economy” in 2020, to describe an economy in which those at the top get ahead while those at the bottom fall behind. The phrase has stuck, as has the narrative.

But what actually happened during the Biden years, at least in terms of wages, was the opposite. In 2023 and in subsequent work, David Autor, Arindrajit Dube, and Annie McGrew documented that there had in fact been an “unexpected compression” in which the wage gap between the highly paid and the less well paid suddenly narrowed.

;…]

[D]uring the Biden years, real wages for the bottom 80 percent of workers grew substantially faster than they had over the previous 40 years. Moreover, growth was especially high at the very bottom of the wage distribution. This was the “unexpected compression”: because low-earning workers experienced faster wage growth than those with higher pay, the wage gap between low income workers and high income workers was squeezed during the Biden years.

Then he talks bout the labor market:

Dube’s thesis is that a tight labor market – one in which workers find it easy to get jobs and employers find it hard to get workers — is essential to wage growth, especially among the low paid.

And for much of the Biden era the U.S. job market was very tight. For evidence, look at the Conference Board’s “labor market differential” — the difference between the percentage of people saying that jobs are plentiful and those saying that jobs are hard to get. That number is usually positive — we are an optimistic nation — but it was exceptionally positive during the Biden years:

He concludes:

So, why is it important to set the record straight about the Biden economy? We can’t rerun the 2024 election (although if we could, Kamala Harris would win.) But misperceptions about that economy may prevent us from appreciating policies — especially the strong response to the pandemic — that were actually very good, and which we should be prepared to emulate in future crises.

Isn’t it pretty to think so? But Biden was old and eggs were expensive so… never again?

I urge you to read the whole thing because he goes into much greater detail than I’ve excerpted here and makes a much more in-depth argument. But the upshot is that Biden’s policies were actually very good for the average American and it’s just a terrible shame that he and Harris were run out of office before they could take the next steps to make them stick. Trump’s only real political strategy is to be a bully and do the opposite of whatever his predecessors did and that’s exactly what he’s done.

Sinking Like A Stone

Apr. 21st, 2026 07:30 pm
[syndicated profile] digby_feed

Posted by digby

Aaaaand:

Update — another one:

Meanwhile:

Updated list of US House GOP bills that would honor Trump

1) Carve his face into Mt. Rushmore

2) Rename Palm Beach airport after Trump

2a) Rename Dulles airport after Trump

3) Require State Dept to award a “Trump Peace Prize”

4) Declare Trump’s birthday a federal holiday

5) Award Trump a Congressional Gold Medal

6) Mint a $250 bill in US currency w/ Trump’s image

7) Several resolutions urging Trump be given Nobel Prize

8) Directing N.I.H. to conduct research on “Trump Derangement Syndrome”

a happy Monday

Apr. 21st, 2026 08:54 pm
[personal profile] cosmolinguist

Yesterday ended up so unexpectedly nice, I wanted to record it.

D messaged me mid-afternoon to say that circuits was happening again that evening. I used to love transgym circuits, I did that as well as lift club almost every week and I've never been happier. But then our usual awesome trainer stopped doing circuits, which is fair enough but I was/am so used to their style and so comfy with it, and then the replacement started doing more of a boxing style fitness class, which was not to my taste (or accessibility needs: my lack of depth perception was posing too much of a problem) and then I kept being busy on those nights or whatever and I just stopped going some time last fall I think.

But I've really missed circuits; I love circuits. It feels like such a good workout for me: I can do even exercises I hate for a minute or two at a time, I never get bored, and I feel at the end like I've really Done Something. I used to have to bring bandanas to tie around my head to keep from getting too much sweat in my eyes, and I forgot to do that last night and really missed it! Because it's hard work.

And most of the people there weren't our usual old circuits people but people I knew from lift club who hadn't been to circuits before (or, did it like once a very long time ago or whatever). Including one of my favorites, who I said I'd meet outside and go in with together. I was really excited for him because I thought he'd love circuits and he did.

And, when I suddenly found myself with plans to be out for the evening I thought I'd start dinner prep right after work -- i did this last Friday when I went to yoga. But as I was still peeling sweet potatoes, D came downstairs, having finished work earlier than usual, and offering to help. So we just made all of my very easy plan for dinner (bangers and mash) and I had plenty of time to eat before going to the gym. It was lovely to spend the time together, it made an easy thing easier but also just so much more fun: being silly together in the nice sunny kitchen (I'm still not used to it being that bright at dinner time! it wasn't totally dark when I was getting showered after the gym, at about 9pm! bliss).

And I'm very glad I was able to eat beforehand: even with V warning me as I left the house "take it easy! you're out of practice!", even though I did take it easy, I was so sore by the time I got home. I knew not to sit down before I got upstairs and in the shower because I'd never stand up again. But I was so happy, too -- and it wasn't just the endorphins making me think that.

All I want to say about this

Apr. 21st, 2026 08:38 pm
[personal profile] cosmolinguist

Tomorrow, I'm having an initial video consultation with a clinic that doesn't rule people out because of BMI.

I really didn't want to have to travel for surgery (it makes what's already an indescribably big deal so much bigger), but it's looking like this is my only option.

Rejoice, we triumph, sort of

Apr. 21st, 2026 08:15 pm
oursin: Brush the Wandering Hedgehog by the fire (Default)
[personal profile] oursin

That is, I have finally knocked off a review that has been hanging over me for months, probably needs a little more fiddling with but it was very much I had got to the stage of 'just sit down and write the bloody thing' and did it. It's a book I'm fairly lukewarm about, doing fairly useful work with what it does but it feels a bit all over the place and hard to get a proper grip on.

Also, yay, am feeling rather less washed out than the past few days following vaxx.

We have appointment to see solicitor about our Testamentary Dispositions next week - finally found one in the fairly close vicinity through the Law Society Find a Solicitor facility.

Have just been getting Documentation from the local authority who are actually paying me to go and talk about johnnies in their collections in just under two months, so I guess that's sort of the next thing on my agenda.

Though am gradually making my way through ms by deceased colleague, though there is not major urgency on this as my collaborator is still in academic life and overwhelmed with the responsibilities of that at present.

Postcard of the Day

Apr. 21st, 2026 03:13 pm
fflo: (Default)
[personal profile] fflo


 
Look, I'm here on a Tuesday.

Been going through my physical postcards lately, and plan to scan some of those, plus am looking at procuring more, if the site I'm going through gets its payment act together.

Happy no bow tie Tuesday.

A Bad Penny

Apr. 21st, 2026 05:30 pm
[syndicated profile] digby_feed

Posted by digby

Sometimes it feels as if Donald Trump reinvented politics in whole cloth when he descended the Trump Tower escalator in 2015, and the world turned upside down. Here we are, 11 years later, still living in the surreality we first experienced on that day — like a nightmare from which we can’t awaken. The truth is that the wheels were coming off our political culture long before Trump came on the scene, and every once in a while we’re reminded of it. 

On Saturday the New York Times reported the Department of Justice has hired Joseph diGenova, an 81-year-old former U.S. attorney and political commentator, to head the “grand conspiracy” investigation targeting the president’s perceived enemies that is underway in the Southern District of Florida under the leadership of U.S. attorney — and Trump loyalist — Jason A. Reding Quiñones. DiGenova brings with him decades of experience; he’s been carrying out GOP vendetta since the days when the president was a tabloid joke and running around with Jeffrey Epstein in New York more than 30 years ago. 

News of diGenova’s appointment comes on the heels of a prosecutor withdrawing from the case, apparently due to doubts she had about prosecuting former CIA director John O. Brennan. Maria Medetis Long reportedly expressed concern that the evidence in the matter didn’t merit moving forward with an indictment, and as a career prosecutor, she should know. But diGenova does not have such lengthy experience. Although he was once a federal prosecutor during the Reagan administration, he has since made a career as a conservative commentator and operative whose most recent political activity came as a member of the so-called “elite strike force team” assembled by Rudy Giuliani to contest the 2020 election. (DiGenova appeared alongside the former New York City mayor at the infamous press conference held at the Four Seasons Landscaping Company where Giuliani spoke with black rivulets dripping down his face like a Real Housewife on a crying jag.)

A Trump loyalist, diGenova has been a GOP hit man since the 1990s when he and his wife, Victoria Toensing, made their names appearing on television to torment Bill and Hillary Clinton. They were the toast of the town, inspiring glowing profiles in the mainstream press in which they were characterized as savvy operators, a distinction that, in the words of the Washington Post’s then-media critic Howard Kurtz, “gives them access to juicy information, which gets them on television, which generates legal business.” In his 1998 profile titled “The Power Couple at Scandal’s Vortex,” Kurtz approvingly noted that diGenova and Toensing had been quoted or appeared on television more than 300 times in the month since news about Bill Clinton’s affair with White House intern Monica Lewinsky had broken. The media critic quoted Geraldo Rivera, who was then a host on CNBC, characterizing diGenova as “a strong, principled guy who doesn’t back down. If I played any part in making him a media star, I gloat with pleasure.”

Such was the relationship between right-wing character assassins and the mainstream media during that period — and nobody was more adept at it than diGenova. Although he and Toensing were not the only lawyer pundits on television at the time, they nonetheless pioneered the practice of representing clients involved in the cases on television in an effort to push the scandals into the mainstream, something that remains commonplace today. 

The couple kept a lower profile during the Bush years, raising their heads to defend Dick Cheney’s right-hand man, Scooter Libby. The Obama administration didn’t offer much red meat in the scandal department. But from the moment in April 2015 that Hillary Clinton announced her candidacy for president, they were off and running again. 

Toensing defended a number of clients who were involved in peripheral cases such as Uranium One, the absurd charge that Clinton had sold enriched uranium to Russia in exchange for donations to the Clinton Foundation. But it was diGenova who came up with the initial right-wing broadside against one of the first people who would land on Trump’s enemies list in the weeks after he assumed office in 2017: James Comey. Even before the 2016 election, Trump was out there with a talking point that persists to this day, telling Laura Ingraham that “Comey’s a dirty cop. And if there’s one thing a prosecutor hates worse than a criminal, it’s a dirty cop… He threw this case. He did it for political reasons.” 

By the time Trump’s first impeachment came along, diGenova and Toensing were up to their old tricks. Already part of Giuliani’s back-channel foreign policy — which held that it was actually the Ukrainians who interfered in the 2016 election to help Hillary Clinton — the couple hit the airwaves like it was 1998 again in what Roll Call dubbed “The Vicki and Joe Show.” DiGenova came out swinging on behalf of Trump, saying, “what you’re seeing is regicide, this is regicide, by another name, fake impeachment.” The whistleblowers who raised concerns about Trump’s conduct were “suicide bombers,” he said. Without citing any evidence, he also called the paid Democratic operatives

Trump noticed, and he tapped diGenova and Toensing to join the team defending him in the Russia probe. But reports claimed the “chemistry” just wasn’t there, and the couple was not hired after all. Still, the president must have liked what he had heard. DiGenova was the one who had insisted from the very beginning that “a group of FBI and DOJ people were trying to frame Donald Trump of a falsely created crime… they were going to exonerate Hillary and they were going to frame Donald Trump.” That has formed the basis of Trump’s ongoing attacks against the Russia investigation. 

This was diGenova’s beat during the president’s first term. When Attorney General Bill Barr tasked Special Prosecutor John Durham with investigating the Russia investigation, diGenova was on it. “This is now big time, telling Fox News’ Laura Ingraham, “This is now big time. This is where Brennan needs five lawyers. Comey needs five lawyers.” The whole Obama administration, he declared, was on the hook for framing Donald Trump in the Russia probe. 

And the one person who counted was apparently listening.

Durham, of course, failed to turn up anything. Now Trump’s Justice Department is pursuing another full-fledged investigation using the same case theory diGenova has been pushing for years. Quiñones is a hard-core Trump supporter, and the grand jury involved in the probe is being overseen by Judge Aileen Cannon, who tanked the Mar-a-Lago documents case. With diGenova, the man who created the case’s very origin story, they have their dream team in place.

DiGenova has been given the title of “counselor to the attorney general,” along with free rein to turn his narrative into reality. Can the TV hit man do what none of the other Trump lawyers before him have been able to do: put the president’s enemies behind bars? Stay tuned.

Salon

A Good Grade in Dentistry

Apr. 21st, 2026 12:58 pm
soc_puppet: Pixelated Habitica avatar decked out in full Mushroom Druid wear, riding a Dusk Badger mount through a forest with a pet Base Snake (Meme Warrior)
[personal profile] soc_puppet
Finally made an appointment for my "spring" dental cleaning!

So I go to the local dental school, because that's what my insurance covers, but I also think it's kind of fun and neat to be helping dental students learn. I also take fairly good care of my teeth (thank you, Habitica, for making me a regular flosser!). Apparently, I'm such an easy patient that I qualify for first year dental students to practice on! Which I, at least, think is pretty cool and a neat way to affirm that I keep my teeth in relatively good condition. A fun little (sugar-free 😜) treat for the day!

TV Tuesday: Long Term Preservation

Apr. 21st, 2026 12:41 pm
yourlibrarian: LibraryGeek-eyesthatslay (BUF-LibraryGeek-eyesthatslay)
[personal profile] yourlibrarian posting in [community profile] tv_talk

Laptop-TV combo with DVDs on top and smartphone on the desk



[personal profile] aurumcalendula reported last month that a set of Wiseguy DVDs had a non-working disc. And apparently Warner Bros DVDs made in 2006-2008 will all stop working. Earlier laser disc recordings also had similar issues.

Do you have a lot of DVDs? How long have you been collecting them? Have you run into problems with them? Is it important for you to preserve particular shows?

Four Horsemen of the AIpocalypse

Apr. 21st, 2026 04:28 pm
[syndicated profile] wheresyouredat_feed

Posted by Ed Zitron

If you liked this piece, please subscribe to my premium newsletter. It’s $70 a year, or $7 a month, and in return you get a weekly newsletter that’s usually anywhere from 5,000 to 18,000 words, including vast, detailed analyses of NVIDIA, Anthropic and OpenAI’s finances, and the AI bubble writ large. I recently put out the timely and important Hater’s Guide To The SaaSpocalypse, another on How AI Isn't Too Big To Fail, a deep (17,500 word) Hater’s Guide To OpenAI, and just last week put out the massive Hater’s Guide To Private Credit.

Subscribing to premium is both great value and makes it possible to write these large, deeply-researched free pieces every week. 


Soundtrack — Megadeth — Hangar 18 (Eb Tuning)

For the best part of four years I’ve been wrapped up in writing these massive, sprawling narratives about the AI bubble and the tech industry at large. I still intend to write them, but today I’m going to do what I do best — explaining all the odd shit that’s happening in the tech industry and explaining why it’s concerning to me. 

And because I love a good bit, I’m tying these stories to my pale horses of the AIpocalypse — signs that things are beginning to unwind in the most annoying bubble in history.  

Anyway, considering that the newsletter and the podcast are now my main form of income, I’m going to be experimenting with the formats across the free and premium to keep things interesting and varied. 

Anthropic’s Products Are Constantly Breaking Because It Doesn’t Have Enough Capacity, And Opus 4.7 Is Both Worse and Burns More Tokens

Pale Horse: Any further price increases or service degradations from Anthropic and OpenAI are a sign that they’re running low on cash.

Let’s start with a fairly direct statement: Anthropic should stop taking on new customers until it works out its capacity issues.

So, generally any service — Netflix, for example — you use with any regularity has the “four nines” of availability, meaning that it’s up 99.99% of the time. Once a company grows beyond a certain scale, having four 9s is considered standard business practice…

unless you’re Anthropic!

As of writing this sentence, Anthropic’s availability for its Claude Chatbot has 98.79% uptime, its platform/console is at 99.14%, its API is at 99.09%, and Claude Code is at 99.25% for the last 90 days. 

Let me put this into context. When you have 99.99% uptime, a service is only down for a minute (and 0.48 of a second) each week. If you’re hitting 98.79% uptime, as with the Claude chatbot, your downtime jumps to two hours, one minute, and 58 seconds. 

Or, put another way, 98.79% uptime equates to nearly four-and-a-half days in a calendar year where the service is unavailable.

More-astonishingly, Claude for Government sits at 99.91%. Government services are generally expected to be four 9s minimum, or 5 (99.999%) for more important systems underlying things like emergency services. 

This is a company that recently raised $30 billion dollars and gets talked about like somebody’s gifted child, yet Anthropic’s services seem to have constant uptime issues linked to a lack of capacity. 

Per the Wall Street Journal:

Since mid-February, outages for systems across Anthropic have become so common that some of its enterprise clients are switching to other AI model players. 
David Hsu, founder and CEO of software development platform Retool, said he prefers to use Anthropic’s Opus 4.6 model to power his company’s AI agent tool because he believes it is the best model for enterprise. He recently changed to OpenAI’s model to power his company’s agent. “Anthropic has just been going down all the time,” he said.

The reliability of core services on the internet is often measured in nines. Four nines means 99.99% of uptime—a typical percentage that a software company commits to customers. As of April 8, Anthropic’s Claude API had a 98.95% uptime rate in the last 90 days. 

Yet Anthropic’s problems go far further than simple downtime (as I discussed last week), leading to (deliberately or otherwise) severe performance issues with Opus 4.6

One of the most detailed public complaints originated as a GitHub issue filed by Stella Laurenzo on April 2, 2026, whose LinkedIn profile identifies her as Senior Director in AMD’s AI group.

In that post, Laurenzo wrote that Claude Code had regressed to the point that it could not be trusted for complex engineering work, then backed that claim with a sprawling analysis of 6,852 Claude Code session files, 17,871 thinking blocks and 234,760 tool calls.

The complaint argued that, starting in February, Claude’s estimated reasoning depth fell sharply while signs of poorer performance rose alongside it, including more premature stopping, more “simplest fix” behavior, more reasoning loops, and a measurable shift from research-first behavior to edit-first behavior.

While Anthropic claims that it doesn’t degrade models to better serve demand, that doesn’t really square with the many, many users complaining about the problem. Anthropic’s response has, for the most part, been to pretend like nothing is wrong, with a spokesperson waving off Carl Franzen of VentureBeat (who has a great article on the situation here) by pointing him to two different Twitter posts, neither of which actually explain what’s going on.

Things only got worse with last week’s launch of Opus 4.7, which appears to have worse performance and burn more tokens. 

Per Business Insider:

One Reddit post titled, "Claude Opus 4.7 is a serious regression, not an upgrade," has 2,300 upvotes. An X user's suggestion that Opus 4.7 wasn't really an improvement over Opus 4.6 got 14,000 likes. In one informal but popular test of AI intelligence, Opus 4.7 appears to say that there were two Ps in "strawberry." Another user screenshot shows it saying that it didn't cross reference because it was "being lazy." Some Redditors found that Opus 4.7 was rewriting their résumés with new schools and last names. Multiple X users posited that Opus 4.7 had simply gotten dumber.

Some X users have suggested the culprit is the AI model's reasoning times. Anthropic says the new "adaptive reasoning" function lets the model decide when to think for longer or shorter periods. One user wrote that they couldn't "get Opus 4.7 to think." Another wrote that it "nerfs performance."

"Not accurate," Anthropic's Boris Cherny, the creator of Claude Code, responded. "Adaptive thinking lets the model decide when to think, which performs better."

I think it’s deeply bizarre that a huge company allegedly worth hundreds of billions of dollars A) can’t seem to keep its services online with any level of consistency, B) appears to be making its products worse, and C) refuses to actually address or discuss the problem. Users have been complaining about Claude models getting “dumber” going back as far as 2024, each time faced with a tepid gaslighting from a company with a CEO that loves to talk about his AI products wiping out half of white collar labor.

Anthropic Has No Good Solutions To Its Capacity Issues And Shouldn’t Be Accepting New Customers — And More Capacity Will Only Lose It Money

Some might frame this as Anthropic having “insatiable demand for its products,” but what I see is a terrible business with awful infrastructure run in an unethical way. It is blatantly, alarmingly obvious that Anthropic cannot afford to provide a stable and reliable service to its customers, and its plans to expand capacity appear to be signing deals with Broadcom that will come online “starting in 2027,” near-theoretical capacity with Hut8, which does not appear to have ever built an AI data center, and also with CoreWeave, a company that is yet to build the full capacity for its 2025 deals with OpenAI and only has around 850MW of “active power capacity” — so around 653MW of actual compute capacity — as of the end of 2025, up from 360MW of power at end of 2024.   

Remember: data centers take forever to build, and there’s only a limited amount of global capacity, most of which is taken up by Microsoft, Google, Amazon, Meta and OpenAI, with the first three of those already providing capacity to both Anthropic and OpenAI.

We’re likely hitting the absolute physical limits of available AI compute capacity, if we haven’t already done so, and even if other data centers are coming online, is the plan to just hand them over to OpenAI or Anthropic in perpetuity?

It’s also unclear what the goal of that additional capacity might be, as I discussed last week:

Yet it’s unclear whether “more capacity” means that things will be cheaper, or better, or just a way of Anthropic scaling an increasingly-shittier experience. 

To explain, when an AI lab like Anthropic or OpenAI “hits capacity limits,” it doesn’t mean that they start turning away business or stop accepting subscribers, but that current (and new) subscribers will face randomized downtime and model issues, along with increasingly-punishing rate limits. 

Neither company is facing a financial shortfall as a result of being unable to provide their services (rather, they’re facing financial shortfalls because they’re providing their services to customers), and the only ones paying that price because of these “capacity limits” are the customers.

What’s the goal, exactly? Providing a better experience to its current customers? Securing enough capacity to keep adding customers? Securing enough capacity to support larger models like Mythos? When, exactly, does Anthropic hit equilibrium, and what does that look like? 

There’s also the issue of cost. 

Anthropic is currently losing billions of dollars a year offering a service with amateurish availability and oscillating quality, and continues to accept new subscribers, meaning that capacity issues are not affecting its growth. As a result, adding more capacity simply makes the product work better for a much higher cost.

Anthropic’s Growth Story Is A Sham Based on Subsidies and Sub-par Service

Anthropic’s growth story is a sham built on selling subscriptions that let users burn anywhere from $8 to $13.50 for every dollar of subscription revenue and providing a brittle, inconsistent service, made possible only through a near-infinite stream of venture capital money and infrastructure providers footing the bill for data center construction.

Put another way, Anthropic doesn’t have to play by the rules. Venture capital funding allows it to massively subsidize its services. The endless, breathless support from the media runs cover for the deterioration of its services. A lack of any true regulation of tech, let alone AI, means that it can rugpull its customers with varying rate limits whenever it feels like

If Anthropic were forced to charge its actual costs — and no, I don’t believe its API is profitable no matter how many people misread Dario Amodei’s interview — its growth would quickly fall apart as customers faced the real costs of AI (which I’ll get to in a bit). If Anthropic was forced to provide a stable service, it would have to stop accepting new customers or massively increase its inference costs. 

Anthropic is a con, and said con is only made possible through endless, specious hype. Everybody who blindly applauded everything this company did is a mark.

Claude Mythos Was Held Back Due To Capacity Constraints, Not Fears Around Capabilities

Congratulations to all the current winners of the “Fell For It Again Award.” Per the Financial Times:

Anthropic has said it will hold off on a wider release of the model until it is reassured that it is safe and cannot be abused by bad actors. The company also has a finite amount of computing power and has suffered outages in recent weeks.

Multiple people with knowledge of the matter suggested Anthropic was holding back from a wider release until it could reliably serve the model to customers.

So, yeah, anyone in the media who bought the line of shit from Dario Amodei that this was “too dangerous to release” is a mark. Cal Newport has an excellent piece debunking the hype, but my general feeling is that if Mythos was so powerful, how did Claude Code’s source code leak

Did… Anthropic not bother to use its super-powerful Mythos model to check? Or did it not find anything? Either way, very embarrassing for all involved. 

AI Compute Demand Is Being Inflated By Anthropic and OpenAI, With More Than 50% of AI Data Centers Under Construction Built For Two Companies, and Only 15.2GW of Capacity Under Construction Through The End of 2028

Pale Horse: data center collapses, misc.

As I’ve discussed in the past, only 5GW of AI compute capacity is currently under construction worldwide (based on research from Sightline Climate), with “under construction” meaning everything from a scaffolding yard with a fence (as is the case with Nscale’s Loughton-based data center) to a building nearing handoff to the client. 

I reached out to Sightline to get some clarity, and they told me that of the 114GW of capacity due to come online by the end of 2028, only 15.2GW is under construction, including the 5GW due in 2026. 

That’s…very bad. 

It gets worse when you realize that the majority of that construction is for two companies:

Sidenote: I’ll also add that Anthropic has agreed to spend $100 billion on Amazon Web Services over the next decade as part of its $5 billion (with “up to $20 billion” more in the future, and no, there’s no more details than that) investment deal with Amazon, with Anthropic apparently securing 5GW of capacity and bringing “nearly 1GW of Trainium2 and 3 capacity online by the end of the year,” which I do not believe, but whatever.These deals shouldn’t be legal.

So, to summarize, at least 4.6GW of the 15.2GW of data center capacity under construction is for OpenAI, with at least another 4GW of that reserved for Anthropic through partners like Microsoft, Google and Amazon. In truth, the number could be much higher. 

This is a fundamentally insane situation. OpenAI and Anthropic both burn billions of dollars a year, with The Information reporting that Anthropic expects to burn at least $11 billion and OpenAI $25 billion in 2026. The only way that these companies can continue to exist is by raising endless venture capital funding or, assuming they make it to IPO, endless debt offerings or at-the-market stock sales.

NVIDIA Claims To Have $1 Trillion In Sales Visibility Through 2027, But Only $285 Billion GPUs Worth Of Data Centers Are Under Construction — NVIDIA Is Selling Years’ Worth of GPUs In Advance And Warehousing Them

It’s also very concerning that only such a small percentage of announced compute capacity is being built, especially when you run the numbers against NVIDIA’s actual sales.

Last year, Jerome Darling of TD Cowen estimated that it cost around $30 million per megawatt in critical IT (GPUs, servers, storage, and so on) and $12 million to $14 million per megawatt to build a data center, making critical IT around 68% (at the higher end of construction) of the total cost-per-megawatt.

Now, to be clear, those gigawatt and megawatt numbers for data centers refer to the power rather than critical IT, and if we take an average PUE (power usage efficiency, a measurement of how efficient a data center’s power is) of 1.35, we get 11.2GW of critical IT hardware, with the majority (I’d say 90%) being GPUs, bringing us down to around 10.1GW of GPUs.

If we then cut that up into GB200 or GB300 NVL72 racks with a power draw of around 140KW, that’s around 71,429 racks’ worth of hardware at an average of $4 million each, which gives us around $285.7 billion in revenue for NVIDIA.

NVIDIA claims it had a combined $500 billion in orders between 2025 and 2026, and $1 trillion of sales through 2027, and it’s unclear where any of those orders are meant to go other than a warehouse in Taiwan. 

At this point, I think it’s fair to ask why anyone is buying more GPUs, as there’s nowhere to fucking put them. Every beat-and-raise earnings from NVIDIA is now deeply suspicious. 

AI Is Really Expensive, With Companies Spending As Much As 10% Of Headcount Cost On LLM Tokens, And May Reach 100% of Headcount Cost In The Next Few Quarters

New Pale Horse: Any and all signs that companies are facing the economic realities of AI, including any complaints around or adaptations to deal with the increasing costs of AI.

Last week, a report from Goldman Sachs revealed that (and I quote) “...companies are overrunning their initial budgets for inference by orders of magnitude (we heard one industry datapoint on inference costs in engineering now approaching about 10% of headcount cost, but could be on track to be on par with headcounts costs in the next several quarters based on current trajectories.” 

To simplify, this means that some companies are spending as much as 10% of the cost of their employees on generative AI services, all without appearing to provide any stability, quality or efficiency gains, or (not that I want this) justification to lay people off. 

The Information’s Laura Bratton also reported last week that Uber had managed to blow through its entire AI budget for the year a few months into 2026: 

Uber’s surging use of AI coding tools, particularly Anthropic’s Claude Code, has maxed out its full year AI budget just a few months into 2026, according to chief technology officer Praveen Neppalli Naga.

“I'm back to the drawing board because the budget I thought I would need is blown away already,” Neppalli Naga said in an interview.



He wouldn’t disclose exact figures of the company’s software budget or what it spends on AI coding tools. Uber’s research and development expenses, which typically reflect companies’ costs of developing new AI products, rose 9% to $3.4 billion in 2025 from the previous year, and the firm said in a recent securities filing it expects that cost will continue rising on an absolute dollar basis.

Uber’s CTO also added that about “...11% of real, live updates to the code in its backend systems are being written by AI agents primarily built with Claude Code, up from just a fraction of a percent three months ago.” Anyone who has ever used Uber’s app in the last year can see how well that’s going, especially if they’ve had to file any kind of support ticket.

Honestly, I find this all completely fucking insane. The whole sales pitch for generative AI is that it’s meant to be this magical, efficiency-driving panacea, yet whenever you ask somebody about it the answer is either “yeah, we’re writing all the code with it!” without any described benefits or “it costs so much fucking money, man.” 

Let’s get practical about these economics, and use Spotify as an example because its CEO proudly said that its “top engineers” are barely writing code anymore, though to be clear, the Goldman Sachs example didn’t specifically name any one company.

For the sake of argument, let’s say that the company has 3000 engineers — one of its sites claims it has 2700, but I’ve seen reports as high as 3500. Let’s also assume, based on the Spotify Blind (an anonymous social media site for tech workers), that these engineers make a median salary of 192,000 a year.

In the event that Spotify spent 10% of its engineering headcount (around $576 million) on AI inference, it would be spending roughly $57.6 million, or approximately 4.1% of its $1.393 billion in Research and Development costs from its FY2025 annual report. Eager math-doers in the audience will note that 100% of headcount would be nearly half of the R&D budget, or around a quarter of its $2.2 billion in net income for the year.

Now, to be clear, these numbers likely already include some AI inference spend, but I’m just trying to illustrate the sheer scale of the cost. 

While this is great for Anthropic (and to a lesser extent OpenAI), I don’t see how it works out for any of its customers. A flat 10% bump on the cost of software engineering is the direct opposite of what AI was meant to do, and in the event that costs continue to rise, I’m not sure how anybody justifies the expense much further. 

And we’re going to find out fairly quickly, because the world of token subsidies is going away.

The Subprime AI Crisis Continues, With Microsoft Starting Token-Based Billing For GitHub Copilot Later This Year, And Anthropic Already Moving Enterprise Customers To API Rates

Pale Horse: Any further price increases or service degradations from AI startups, and yes, that’s what I’d call GitHub Copilot, in the sense that it loses hundreds of millions of dollars and makes fuck-all revenue. 

As I reported yesterday, internal documents have revealed that Microsoft plans to temporarily suspend individual account signups to its GitHub Copilot coding product, tighten rate limits across the board, remove Opus models from its $10-a-month Pro subscription, and transition from requests (single interactions with GitHub Copilot) towards token-based billing some time later this year, with Microsoft confirming some of these details (but not token-based billing) in a blog post.

This is a significant move, driven by (per my own reporting) Microsoft’s week-over-week costs of running GitHub Copilot nearly doubling since January. 

An aside/explainer: if you’re confused as to what “token-based billing” means, know that the vast majority of AI services currently subsidize their subscriptions, using another measure (such as “requests” or “rate limits”) to meter out how much a user can use the service. Nevertheless, these services still burn tokens at whatever rate that it costs to pay for them — for example, $5 per million input and $25 per million output for Opus 4.7, as I mentioned previously — meaning that the company almost always loses money unless a person doesn’t use the subscription very much.

Companies did this to grow their subscriber numbers, and I think they assumed things would get cheaper somehow. Great job, everyone! 

The move to token-based billing will see GitHub users charged based on their usage of the platform, and how many tokens their prompts consume — and thus, how much compute they use. It’s unclear at this time when this will begin, but it significantly changes the value of the product.

I’ll also say that the fact that Microsoft has stopped signing up new paid GitHub Copilot subscriptions entirely is one of the most shocking moves in the history of software. I’ve literally never seen a company do this outside of products it intended to kill entirely, and that’s likely because — per my source — it intends to move paid customers over to token-based-billing, though it’s unclear what these tiers would look like, as the $10-a-month and $39-a-month subscriptions are mostly differentiated based on the amount of requests you can use. 

What’s remarkable about this story is that Microsoft is one of the few players capable of bankrolling AI in perpetuity, with over $20 billion a quarter in profits since the middle of 2023

Its decision to start cutting costs around AI suggests that said costs have become unbearable — The Information reported back in January that it was on pace to spend $500 million a year with Anthropic alone, and if that amount has doubled, it likely means that Microsoft is spending upwards of ten times its GitHub Copilot revenue, as I can report today that at the end of 2025, GitHub Copilot was at around $1.08 billion, with the majority of that revenue coming from its CoPilot Business and Enterprise subscriptions. 

The Information also reported a few weeks ago that GitHub had recently seen a surge of outages attributed to “spiking traffic as well as its effort to move its applications from its own servers to Microsoft’s Azure cloud”:

“Since January, every month, every week almost now has some new peak stat for the highest [usage] rate ever,” [GitHub COO Kyle] Daigle said. He attributed the growth to “both agents and humans,” and also noted that the rise of AI coding tools has led to a rise in humans without deep coding knowledge starting to use GitHub’s platform more.

“Agents” in this case could refer to just about anything — OpenAI’s Codex, Anthropic’s Claude Code, or even people plugging in the wasteful, questionably-useful OpenClaw to their GitHub Copilot account, and if that’s what happened, it’s very likely behind the move to Token-Based Billing and rate limits.

In any case, if Microsoft’s making this move, it means that CFO Amy Hood — the woman behind last year’s pullback on data center construction — has decided that the subsidy party is over. Though Microsoft is yet to formally announce the move to Token-Based Billing, I imagine it’ll be sometime this week that it rips off the bandage.

Two weeks ago, Anthropic did the same with its enterprise customers, shifting them to a flat $20-a-seat fee and otherwise charging the per-token rate for whatever models they wanted to use. 

I’m making the call that by the end of 2026, a majority of AI services will move some or all of their customers to token-based billing as they reckon with the true costs of running AI models. 

This Is The Era of AI Hysteria

I kept things simple today both to give myself a bit of a break and because these were stories I felt needed telling. 

Nevertheless, I do have to remark on how ridiculous everything has become.

Everywhere you turn, somebody is talking about “agents” in a way that doesn’t remotely match with reality, like Aaron Levie’s epic screeds about how “AI agents make it so every other company on the planet starts to create software for bringing automation to their workflows in a way that would be either infeasible technically or unaffordable economically,” a statement that may as well be about fucking unicorns and manticores as far as its connections to reality. 

I feel bad picking on Aaron, as he doesn’t seem like a bad guy. He is, however, increasingly-indicative of the hysterical brainrot of executive AI hysteria, where the only way to discuss the industry is in vaguely futuristic-sounding terms about “agents” and “inference” and “tokens as a commodity,” all with the intent of obfuscating the ugly, simple truth: that generative AI is deeply unprofitable, doesn’t seem to provide tangible productivity benefits, and appears to only lose both the business and the customer money. 

Though my arguments might be verbose, they’re ultimately pretty simple: AI does not provide even an iota of the benefits — economic or otherwise — to justify its ruinous costs. Every new story that runs about cost-cutting or horrible burnrates increasingly validates my position, and for the most part, boosters respond by saying “well LOOK at how BIG the REVENUES are.”

It isn’t! AI revenues are dogshit. They’re awful. They’re pathetic. The entire industry — including OpenAI and Anthropic’s theoretical revenues of $13.1 billion and $4.5 billion — hit around $65 billion last year, and that includes the revenues from providing compute generated by neoclouds like CoreWeave and hyperscalers like Microsoft.

I’m also just gonna come out and say it: I think the AI startups are misleading their investors and the general public about their revenues. My reporting from last year had OpenAI’s revenues at somewhere in the region of $4.3 billion in the first three quarters of 2025, and Anthropic CFO Krishna Rao said in an an affidavit that the company had made revenue “exceeding” (sigh) $5 billion through March 9, 2026, which does not make sense when you add up all the annualized revenue figures reported about this company. 

Cursor is also reportedly at $6 billion in annualized revenue (or around $500 million a month) and “gross margin positive” — which I also doubt given that it had to raise over $3 billion last year and is apparently raising another $2 billion this year.

Even if said numbers were real, the majority of OpenAI, Cursor and Anthropic’s revenues come from subsidized software subscriptions. Things have gotten so dire that even Deidre Bosa of CNBC agrees with me that AI demand is inflated by token-maxxing and subsidized services.

Otherwise, everybody else is making single or double-digit millions of dollars and losing hundreds of millions of dollars to get there. And per founder Scott Stevenson, overstating annualized revenues is extremely common, with AI startups booking “three-year-long” enterprise deals with the first year discounted and a twelve-month out:

The reason many AI startups are crushing revenue records is because they are using a dishonest metric

The biggest funds in the world are supporting this and misleading journalists for PR coverage.

The setup: Company signs 3-year enterprise deals. Year 1 is discounted (say $1M), Year 2 steps up ($2M), Year 3 is full price ($3M). 

They report $3M as “ARR” — even though they’re only collecting $1M right now.

The worst part: The customer has an opt-out option at 12 months! It’s not actually a 3 year contract.

While it’s hard to say how widespread this potential act of fraud might be, Stevenson estimates that more than 50% of enterprise AI startups are using “contracted ARR” to pump their values. One (honest) founder responded to Stevenson saying that his company has $350,000 in contracted ARR but only $42,000 of ARR, adding that “next year is gonna be awesome though,” which I don’t think will be the case for what appears to be a chatbot for finding investors.

This industry’s future is predicated entirely on the existence of infinite resources, and most AI companies are effectively front-ends for models owned by Anthropic and OpenAI, two other companies that rely on infinite resources to run their services and fund their infrastructure.

And at the top of the pile sits NVIDIA, the largest company on the stock market, which is selling more GPUs than can be possibly installed, and very few people seem to notice or care. 

I’m talking about hundreds of billions of dollars of GPUs sitting in warehouses that aren’t being installed, with it taking six months to install a single quarter’s worth of GPU sales. The assumption, based on every financial publication I’ve read, appears to be “it will keep selling GPUs forever, and it will all be so great.”

Where are you going to put them, Jensen? Where do the fucking GPUs go? There isn’t enough capacity under construction! If, in fact, NVIDIA is actually selling as many GPUs as it says, it’s likely taking liberties with “transfers of ownership” where NVIDIA marks a product as “sold” to somebody that has yet to actually take it on.

Sidenote: There’re already signs that GPUs are beginning to pile up. 

You see, when a hyperscaler buys an AI server, what actually happens is an ODM — original design manufacturer — buys the GPUs from NVIDIA, builds the server, and then ships it to the data center, which, to be clear, is all above board and normal. These ODMs also book the entire value of the NVIDIA GPU as revenue, which is why revenues for companies like Foxconn, Wystron and Quanta Computing have all spiked during the AI bubble.

Oh, right, the signs. Per Quanta Computing’s fourth quarter financial results, inventory — as in stuff that’s sitting waiting to go somewhere — has spiked from $10.54 billion in Q3 2025 to $16.3 billion 2025, and nearly doubled year-over-year ($8.33 billion) as gross profit dropped from 7.9% in Q4 2024 to 7% Q4 2025. While this isn’t an across-the-board problem (Wistron’s inventories dropped quarter-over-quarter, for example), Taiwanese ODMs are going to be one of the first places to watch for inventory accumulation.

In any case, I keep coming back to the word “hysteria,” because it’s hard to find another word to describe this hype cycle. The way that the media, the markets, analysts, executives, and venture capitalists discuss AI is totally divorced from reality, discussing “agents” in terms that don’t match with reality and AI data centers in terms of “gigawatts” that are entirely fucking theoretical, all with a terrifying certainty that makes me wonder what it is I’m missing.

But every sign points to me being right, and if I’m right at the scale I think I’m right, I think we’re about to have a legitimacy crisis in investing and mainstream media, because regular people are keenly aware that something isn’t right, in many cases, it’s because they’re able to count.