Before you read this post, ask your­self a ques­tion: When was the last time you truly thought hard?

By “thinking hard,” I mean en­coun­ter­ing a spe­cific, dif­fi­cult prob­lem and spend­ing mul­ti­ple days just sit­ting with it to over­come it.

a) All the time. b) Never. c) Somewhere in be­tween.

If your an­swer is (a) or (b), this post is­n’t for you. But if, like me, your re­sponse is (c), you might get some­thing out of this, if only the feel­ing that you aren’t alone.

First, a dis­claimer: this post has no an­swers, not even sug­ges­tions. It is sim­ply a way to vent some­thing I’ve been feel­ing for the last few months.

I be­lieve my per­son­al­ity is built on two pri­mary traits:

The Builder (The de­sire to cre­ate, ship, and be prag­matic).

The Thinker (The need for deep, pro­longed men­tal strug­gle).

The builder is pretty self ex­plana­tory, it’s mo­ti­vated by ve­loc­ity and util­ity. It is the part of me that craves the tran­si­tion from “idea” to “reality.” It loves the dopamine hit of a suc­cess­ful de­ploy, the sat­is­fac­tion of build­ing sys­tems to solve real prob­lems, and the knowl­edge that some­one, some­where, is us­ing my tool.

To ex­plain the Thinker , I need to go back to my uni­ver­sity days study­ing physics. Every now and then, we would get home­work prob­lems that were sig­nif­i­cantly harder than av­er­age. Even if you had a de­cent grasp of the sub­ject, just com­ing up with an ap­proach was dif­fi­cult.

I ob­served that stu­dents fell into three cat­e­gories when fac­ing these prob­lems (well, four, if you count the 1% of ge­niuses for whom no prob­lem was too hard).

* Type 1: The ma­jor­ity. After a few tries, they gave up and went to the pro­fes­sor or a TA for help.

* Type 2: The Researchers. They went to the li­brary to look for sim­i­lar prob­lems or in­sights to make the prob­lem ap­proach­able. They usu­ally suc­ceeded.

I fell into the third cat­e­gory, which, in my ex­pe­ri­ence, was al­most as rare as the ge­nius 1%. My method was sim­ply to think. To think hard and long. Often for sev­eral days or weeks, all my non-I/​O brain time was re­lent­lessly chew­ing on pos­si­ble ways to solve the prob­lem, even while I was asleep.

This method never failed me. I al­ways felt that deep pro­longed think­ing was my su­per­power. I might not be as fast or nat­u­rally gifted as the top 1%, but given enough time, I was con­fi­dent I could solve any­thing. I felt a deep sat­is­fac­tion in that process.

That sat­is­fac­tion is why soft­ware en­gi­neer­ing was ini­tially so grat­i­fy­ing. It hit the right bal­ance. It sat­is­fied The Builder (feeling pro­duc­tive and prag­matic by cre­at­ing use­ful things) and The Thinker (solving re­ally hard prob­lems). Thinking back, the pro­jects where I grew the most as an en­gi­neer were al­ways the ones with a good num­ber of re­ally hard prob­lems that needed cre­ative so­lu­tions.

But re­cently, the num­ber of times I truly pon­der a prob­lem for more than a cou­ple of hours has de­creased tremen­dously.

Yes, I blame AI for this.

I am cur­rently writ­ing much more, and more com­pli­cated soft­ware than ever, yet I feel I am not grow­ing as an en­gi­neer at all. When I started med­i­tat­ing on why I felt “stuck,” I re­al­ized I am starv­ing The Thinker.

“Vibe cod­ing” sat­is­fies the Builder. It feels great to see to pass from idea to re­al­ity in a frac­tion of a time that would take oth­er­wise. But it has dras­ti­cally cut the times I need to came up with cre­ative so­lu­tions for tech­ni­cal prob­lems. I know many peo­ple who are purely Builders, for them this era is the best thing that ever hap­pened. But for me, some­thing is miss­ing.

I know what you might be think­ing: “If you can ‘vibe code’ your way through it, the prob­lem was­n’t ac­tu­ally hard.”

I think that misses the point. It’s not that AI is good for hard prob­lems, it’s not even that good for easy prob­lems. I’m con­fi­dent that my third man­ual rewrite of a mod­ule would be much bet­ter than any­thing the AI can out­put. But I am also a prag­ma­tist.

If I can get a so­lu­tion that is “close enough” in a frac­tion of the time and ef­fort, it is ir­ra­tional not to take the AI route. And that is the real prob­lem: I can­not sim­ply turn off my prag­ma­tism.

At the end of the day, I am a Builder. I like build­ing things. The faster I build, the bet­ter. Even if I wanted to re­ject AI and go back to the days where the Thinker’s needs were met by cod­ing, the Builder in me would strug­gle with the in­ef­fi­ciency.

Even though the AI al­most cer­tainly won’t come up with a 100% sat­is­fy­ing so­lu­tion, the 70% so­lu­tion it achieves usu­ally hits the “good enough” mark.

To be hon­est, I don’t know. I am still fig­ur­ing it out.

I’m not sure if my two halves can be sat­is­fied by cod­ing any­more. You can al­ways aim for harder pro­jects, hop­ing to find prob­lems where AI fails com­pletely. I still en­counter those oc­ca­sion­ally, but the num­ber of prob­lems re­quir­ing deep cre­ative so­lu­tions feels like it is di­min­ish­ing rapidly.

I have tried to get that feel­ing of men­tal growth out­side of cod­ing. I tried get­ting back in touch with physics, read­ing old text­books. But that was­n’t suc­cess­ful ei­ther. It is hard to jus­tify spend­ing time and men­tal ef­fort solv­ing physics prob­lems that aren’t rel­e­vant or state-of-the-art when I know I could be build­ing things.

My Builder side won’t let me just sit and think about un­solved prob­lems, and my Thinker side is starv­ing while I vibe-code. I am not sure if there will ever be a time again when both needs can be met at once.

“Now we have the right to give this be­ing the well-known name that al­ways des­ig­nates what no power of imag­i­na­tion, no flight of the bold­est fan­tasy, no in­tently de­vout heart, no ab­stract think­ing how­ever pro­found, no en­rap­tured and trans­ported spirit has ever at­tained: God. But this ba­sic unity is of the past; it no longer is. It has, by chang­ing its be­ing, to­tally and com­pletely shat­tered it­self. God has died and his death was the life of the world.”

- Philipp Mainländer

Today, we’re re­leas­ing Voxtral Transcribe 2, two next-gen­er­a­tion speech-to-text mod­els with state-of-the-art tran­scrip­tion qual­ity, di­ariza­tion, and ul­tra-low la­tency. The fam­ily in­cludes Voxtral Mini Transcribe V2 for batch tran­scrip­tion and Voxtral Realtime for live ap­pli­ca­tions. Voxtral Realtime is open-weights un­der the Apache 2.0 li­cense.

We’re also launch­ing an au­dio play­ground in Mistral Studio to test tran­scrip­tion in­stantly, pow­ered by Voxtral Transcribe 2, with di­ariza­tion and time­stamps.

Voxtral Mini Transcribe V2: State-of-the-art tran­scrip­tion with speaker di­ariza­tion, con­text bi­as­ing, and word-level time­stamps in 13 lan­guages.

Voxtral Realtime: Purpose-built for live tran­scrip­tion with la­tency con­fig­urable down to sub-200ms, en­abling voice agents and real-time ap­pli­ca­tions.

Best-in-class ef­fi­ciency: Industry-leading ac­cu­racy at a frac­tion of the cost, with Voxtral Mini Transcribe V2 achiev­ing the low­est word er­ror rate, at the low­est price point.

Open weights: Voxtral Realtime ships un­der Apache 2.0, de­ploy­able on edge for pri­vacy-first ap­pli­ca­tions.

Voxtral Realtime is pur­pose-built for ap­pli­ca­tions where la­tency mat­ters. Unlike ap­proaches that adapt of­fline mod­els by pro­cess­ing au­dio in chunks, Realtime uses a novel stream­ing ar­chi­tec­ture that tran­scribes au­dio as it ar­rives. The model de­liv­ers tran­scrip­tions with de­lay con­fig­urable down to sub-200ms, un­lock­ing a new class of voice-first ap­pli­ca­tions.

Word er­ror rate (lower is bet­ter) across lan­guages in the FLEURS tran­scrip­tion bench­mark.

At 2.4 sec­onds de­lay, ideal for sub­ti­tling, Realtime matches Voxtral Mini Transcribe V2, our lat­est batch model. At 480ms de­lay, it stays within 1-2% word er­ror rate, en­abling voice agents with near-of­fline ac­cu­racy.

The model is na­tively mul­ti­lin­gual, achiev­ing strong tran­scrip­tion per­for­mance in 13 lan­guages, in­clud­ing English, Chinese, Hindi, Spanish, Arabic, French, Portuguese, Russian, German, Japanese, Korean, Italian, and Dutch. With a 4B pa­ra­me­ter foot­print, it runs ef­fi­ciently on edge de­vices, en­sur­ing pri­vacy and se­cu­rity for sen­si­tive de­ploy­ments.

We’re re­leas­ing the model weights un­der Apache 2.0 on the Hugging Face Hub.

Average di­ariza­tion er­ror rate (lower is bet­ter) across five English bench­marks (Switchboard, CallHome, AMI-IHM, AMI-SDM, SBCSAE) and the TalkBank mul­ti­lin­gual bench­mark (German, Spanish, English, Chinese, Japanese).

Average word er­ror rate (lower is bet­ter) across the top-10 lan­guages in the FLEURS tran­scrip­tion bench­mark.

Voxtral Mini Transcribe V2 de­liv­ers sig­nif­i­cant im­prove­ments in tran­scrip­tion and di­ariza­tion qual­ity across lan­guages and do­mains. At ap­prox­i­mately 4% word er­ror rate on FLEURS and $0.003/min, Voxtral of­fers the best price-per­for­mance of any tran­scrip­tion API. It out­per­forms GPT-4o mini Transcribe, Gemini 2.5 Flash, Assembly Universal, and Deepgram Nova on ac­cu­racy, and processes au­dio ap­prox­i­mately 3x faster than ElevenLabs’ Scribe v2 while match­ing on qual­ity at one-fifth the cost.

Generate tran­scrip­tions with speaker la­bels and pre­cise start/​end times. Ideal for meet­ing tran­scrip­tion, in­ter­view analy­sis, and multi-party call pro­cess­ing. Note: with over­lap­ping speech, the model typ­i­cally tran­scribes one speaker.

Provide up to 100 words or phrases to guide the model to­ward cor­rect spellings of names, tech­ni­cal terms, or do­main-spe­cific vo­cab­u­lary. Particularly use­ful for proper nouns or in­dus­try ter­mi­nol­ogy that stan­dard mod­els of­ten miss. Context bi­as­ing is op­ti­mized for English; sup­port for other lan­guages is ex­per­i­men­tal.

Generate pre­cise start and end time­stamps for each word, en­abling ap­pli­ca­tions like sub­ti­tle gen­er­a­tion, au­dio search, and con­tent align­ment.

Like Realtime, this model now sup­ports 13 lan­guages: English, Chinese, Hindi, Spanish, Arabic, French, Portuguese, Russian, German, Japanese, Korean, Italian, and Dutch. Non-English per­for­mance sig­nif­i­cantly out­paces com­peti­tors.

Maintains tran­scrip­tion ac­cu­racy in chal­leng­ing acoustic en­vi­ron­ments, such as fac­tory floors, busy call cen­ters, and field record­ings.

Process record­ings up to 3 hours in a sin­gle re­quest.

Word er­ror rate (lower is bet­ter) across lan­guages in the FLEURS tran­scrip­tion bench­mark.

Test Voxtral Transcribe 2 di­rectly in Mistral Studio. Upload up to 10 au­dio files, tog­gle di­ariza­tion, choose time­stamp gran­u­lar­ity, and add con­text bias terms for do­main-spe­cific vo­cab­u­lary. Supports .mp3, .wav, .m4a, .flac, .ogg up to 1GB each.

Transcribe mul­ti­lin­gual record­ings with speaker di­ariza­tion that clearly at­trib­utes who said what and when. At Voxtral’s price point, an­no­tate large vol­umes of meet­ing con­tent at in­dus­try-lead­ing cost ef­fi­ciency.

Build con­ver­sa­tional AI with sub-200ms tran­scrip­tion la­tency. Connect Voxtral Realtime to your LLM and TTS pipeline for re­spon­sive voice in­ter­faces that feel nat­ural.

Transcribe calls in real time, en­abling AI sys­tems to an­a­lyze sen­ti­ment, sug­gest re­sponses, and pop­u­late CRM fields while con­ver­sa­tions are still hap­pen­ing. Speaker di­ariza­tion en­sures clear at­tri­bu­tion be­tween agents and cus­tomers.

Generate live mul­ti­lin­gual sub­ti­tles with min­i­mal la­tency. Context bi­as­ing han­dles proper nouns and tech­ni­cal ter­mi­nol­ogy that trip up generic tran­scrip­tion ser­vices.

Monitor and tran­scribe in­ter­ac­tions for reg­u­la­tory com­pli­ance, with di­ariza­tion pro­vid­ing clear speaker at­tri­bu­tion and time­stamps en­abling pre­cise au­dit trails.

Both mod­els sup­port GDPR and HIPAA-compliant de­ploy­ments through se­cure on-premise or pri­vate cloud se­tups.

Voxtral Mini Transcribe V2 is avail­able now via API at $0.003 per minute. Try it now in the new Mistral Studio au­dio play­ground or in Le Chat.

Voxtral Realtime is avail­able via API at $0.006 per minute and as open weights on Hugging Face.

If you’re ex­cited about build­ing world-class speech AI and putting fron­tier mod­els into the hands of de­vel­op­ers every­where, we’d love to hear from you. Apply to join our team.

The next chap­ter of AI is yours.

The FBI has been un­able to ac­cess a Washington Post re­porter’s seized iPhone be­cause it was in Lockdown Mode, a some­times over­looked fea­ture that makes iPhones broadly more se­cure, ac­cord­ing to re­cently filed court records.

The court record shows what de­vices and data the FBI was able to ul­ti­mately ac­cess, and which de­vices it could not, af­ter raid­ing the home of the re­porter, Hannah Natanson, in January as part of an in­ves­ti­ga­tion into leaks of clas­si­fied in­for­ma­tion. It also pro­vides rare in­sight into the ap­par­ent ef­fec­tive­ness of Lockdown Mode, or at least how ef­fec­tive it might be be­fore the FBI may try other tech­niques to ac­cess the de­vice.

There are many good places for ad­ver­tis­ing. A con­ver­sa­tion with Claude is not one of them.

Advertising dri­ves com­pe­ti­tion, helps peo­ple dis­cover new prod­ucts, and al­lows ser­vices like email and so­cial me­dia to be of­fered for free. We’ve run our own ad cam­paigns, and our AI mod­els have, in turn, helped many of our cus­tomers in the ad­ver­tis­ing in­dus­try.

But in­clud­ing ads in con­ver­sa­tions with Claude would be in­com­pat­i­ble with what we want Claude to be: a gen­uinely help­ful as­sis­tant for work and for deep think­ing.

We want Claude to act un­am­bigu­ously in our users’ in­ter­ests. So we’ve made a choice: Claude will re­main ad-free. Our users won’t see “sponsored” links ad­ja­cent to their con­ver­sa­tions with Claude; nor will Claude’s re­sponses be in­flu­enced by ad­ver­tis­ers or in­clude third-party prod­uct place­ments our users did not ask for.

When peo­ple use search en­gines or so­cial me­dia, they’ve come to ex­pect a mix­ture of or­ganic and spon­sored con­tent. Filtering sig­nal from noise is part of the in­ter­ac­tion.

Conversations with AI as­sis­tants are mean­ing­fully dif­fer­ent. The for­mat is open-ended; users of­ten share con­text and re­veal more than they would in a search query. This open­ness is part of what makes con­ver­sa­tions with AI valu­able, but it’s also what makes them sus­cep­ti­ble to in­flu­ence in ways that other dig­i­tal prod­ucts are not.

Our analy­sis of con­ver­sa­tions with Claude (conducted in a way that keeps all data pri­vate and anony­mous) shows that an ap­pre­cia­ble por­tion in­volve top­ics that are sen­si­tive or deeply per­sonal—the kinds of con­ver­sa­tions you might have with a trusted ad­vi­sor. Many other uses in­volve com­plex soft­ware en­gi­neer­ing tasks, deep work, or think­ing through dif­fi­cult prob­lems. The ap­pear­ance of ads in these con­texts would feel in­con­gru­ous—and, in many cases, in­ap­pro­pri­ate.

We still have much to learn about the im­pact of AI mod­els on the peo­ple who use them. Early re­search sug­gests both ben­e­fits—like peo­ple find­ing sup­port they could­n’t ac­cess else­where—and risks, in­clud­ing the po­ten­tial for mod­els to re­in­force harm­ful be­liefs in vul­ner­a­ble users. Introducing ad­ver­tis­ing in­cen­tives at this stage would add an­other level of com­plex­ity. Our un­der­stand­ing of how mod­els trans­late the goals we set them into spe­cific be­hav­iors is still de­vel­op­ing; an ad-based sys­tem could there­fore have un­pre­dictable re­sults.

Being gen­uinely help­ful is one of the core prin­ci­ples of Claude’s Constitution, the doc­u­ment that de­scribes our vi­sion for Claude’s char­ac­ter and guides how we train the model. An ad­ver­tis­ing-based busi­ness model would in­tro­duce in­cen­tives that could work against this prin­ci­ple.

Consider a con­crete ex­am­ple. A user men­tions they’re hav­ing trou­ble sleep­ing. An as­sis­tant with­out ad­ver­tis­ing in­cen­tives would ex­plore the var­i­ous po­ten­tial causes—stress, en­vi­ron­ment, habits, and so on—based on what might be most in­sight­ful to the user. An ad-sup­ported as­sis­tant has an ad­di­tional con­sid­er­a­tion: whether the con­ver­sa­tion pre­sents an op­por­tu­nity to make a trans­ac­tion. These ob­jec­tives may of­ten align—but not al­ways. And, un­like a list of search re­sults, ads that in­flu­ence a mod­el’s re­sponses may make it dif­fi­cult to tell whether a given rec­om­men­da­tion comes with a com­mer­cial mo­tive or not. Users should­n’t have to sec­ond-guess whether an AI is gen­uinely help­ing them or sub­tly steer­ing the con­ver­sa­tion to­wards some­thing mon­e­ti­z­able.

Even ads that don’t di­rectly in­flu­ence an AI mod­el’s re­sponses and in­stead ap­pear sep­a­rately within the chat win­dow would com­pro­mise what we want Claude to be: a clear space to think and work. Such ads would also in­tro­duce an in­cen­tive to op­ti­mize for en­gage­ment—for the amount of time peo­ple spend us­ing Claude and how of­ten they re­turn. These met­rics aren’t nec­es­sar­ily aligned with be­ing gen­uinely help­ful. The most use­ful AI in­ter­ac­tion might be a short one, or one that re­solves the user’s re­quest with­out prompt­ing fur­ther con­ver­sa­tion.

We rec­og­nize that not all ad­ver­tis­ing im­ple­men­ta­tions are equiv­a­lent. More trans­par­ent or opt-in ap­proaches—where users ex­plic­itly choose to see spon­sored con­tent—might avoid some of the con­cerns out­lined above. But the his­tory of ad-sup­ported prod­ucts sug­gests that ad­ver­tis­ing in­cen­tives, once in­tro­duced, tend to ex­pand over time as they be­come in­te­grated into rev­enue tar­gets and prod­uct de­vel­op­ment, blur­ring bound­aries that were once more clear-cut. We’ve cho­sen not to in­tro­duce these dy­nam­ics into Claude.

Anthropic is fo­cused on busi­nesses, de­vel­op­ers, and help­ing our users flour­ish. Our busi­ness model is straight­for­ward: we gen­er­ate rev­enue through en­ter­prise con­tracts and paid sub­scrip­tions, and we rein­vest that rev­enue into im­prov­ing Claude for our users. This is a choice with trade­offs, and we re­spect that other AI com­pa­nies might rea­son­ably reach dif­fer­ent con­clu­sions.

Expanding ac­cess to Claude is cen­tral to our pub­lic ben­e­fit mis­sion, and we want to do it with­out sell­ing our users’ at­ten­tion or data to ad­ver­tis­ers. To that end, we’ve brought AI tools and train­ing to ed­u­ca­tors in over 60 coun­tries, be­gun na­tional AI ed­u­ca­tion pi­lots with mul­ti­ple gov­ern­ments, and made Claude avail­able to non­prof­its at a sig­nif­i­cant dis­count. We con­tinue to in­vest in our smaller mod­els so that our free of­fer­ing re­mains at the fron­tier of in­tel­li­gence, and we may con­sider lower-cost sub­scrip­tion tiers and re­gional pric­ing where there is clear de­mand for it. Should we need to re­visit this ap­proach, we’ll be trans­par­ent about our rea­sons for do­ing so.

AI will in­creas­ingly in­ter­act with com­merce, and we look for­ward to sup­port­ing this in ways that help our users. We’re par­tic­u­larly in­ter­ested in the po­ten­tial of agen­tic com­merce, where Claude acts on a user’s be­half to han­dle a pur­chase or book­ing end to end. And we’ll con­tinue to build fea­tures that en­able our users to find, com­pare, or buy prod­ucts, con­nect with busi­nesses, and more—when they choose to do so.

We’re also ex­plor­ing more ways to make Claude a fo­cused space to be at your most pro­duc­tive. Users can al­ready con­nect third-party tools they use for work—like Figma, Asana, and Canva—and in­ter­act with them di­rectly within Claude. We ex­pect to in­tro­duce many more use­ful in­te­gra­tions and ex­pand this toolkit over time.

All third-party in­ter­ac­tions will be grounded in the same over­ar­ch­ing de­sign prin­ci­ple: they should be ini­ti­ated by the user (where the AI is work­ing for them) rather than an ad­ver­tiser (where the AI is work­ing, at least in part, for some­one else). Today, whether some­one asks Claude to re­search run­ning shoes, com­pare mort­gage rates, or rec­om­mend a restau­rant for a spe­cial oc­ca­sion, Claude’s only in­cen­tive is to give a help­ful an­swer. We’d like to pre­serve that.

We want our users to trust Claude to help them keep think­ing—about their work, their chal­lenges, and their ideas.

Our ex­pe­ri­ence of us­ing the in­ter­net has made it easy to as­sume that ad­ver­tis­ing on the prod­ucts we use is in­evitable. But open a note­book, pick up a well-crafted tool, or stand in front of a clean chalk­board, and there are no ads in sight.

We think Claude should work the same way.

If you find this use­ful, please ⭐ star the repo — it helps oth­ers dis­cover it!

A pro­duc­tion-ready Model Context Protocol (MCP) server that bridges Ghidra’s pow­er­ful re­verse en­gi­neer­ing ca­pa­bil­i­ties with mod­ern AI tools and au­toma­tion frame­works.

# Windows - run the pro­vided batch script

copy-ghidra-libs.bat “C:\path\to\ghidra_12.0.2_PUBLIC”

# Linux/Mac - copy man­u­ally from your Ghidra in­stal­la­tion

# See Library Dependencies sec­tion be­low for all 14 re­quired JARs

python bridge_m­cp_ghidra.py

python bridge_m­cp_ghidra.py –transport sse –mcp-host 127.0.0.1 –mcp-port 8081

The server runs on http://​127.0.0.1:8080/ by de­fault

# Build the plu­gin (skip in­te­gra­tion tests)

mvn clean pack­age as­sem­bly:sin­gle -DskipTests

# Deploy to Ghidra

.\deploy-to-ghidra.ps1

The lib/ folder must con­tain Ghidra JAR files for com­pi­la­tion. Run the pro­vided script to copy them from your Ghidra in­stal­la­tion:

# Windows

copy-ghidra-libs.bat “C:\path\to\ghidra_12.0.2_PUBLIC”

# Or man­u­ally copy from your Ghidra in­stal­la­tion

Note: Libraries are NOT in­cluded in the repos­i­tory (see .gitignore). You must copy them from your Ghidra in­stal­la­tion be­fore build­ing.

Build and test your changes (mvn clean pack­age as­sem­bly:sin­gle -DskipTests)

This pro­ject is li­censed un­der the Apache License 2.0 - see the LICENSE file for de­tails.

See CHANGELOG.md for ver­sion his­tory and re­lease notes.

* re-uni­verse — Ghidra BSim PostgreSQL plat­form for large-scale bi­nary sim­i­lar­ity analy­sis. Pairs per­fectly with GhidraMCP for AI-driven re­verse en­gi­neer­ing work­flows.

Ready for pro­duc­tion de­ploy­ment with en­ter­prise-grade re­li­a­bil­ity and com­pre­hen­sive bi­nary analy­sis ca­pa­bil­i­ties.

Guinea worm on track to be 2nd erad­i­cated hu­man dis­ease; only 10 cases in 2025

When the erad­i­ca­tion pro­gram be­gan in 1986, there were a 3.5 mil­lion cases.

A pa­tient with a guinea worms emerg­ing, at the Savelugu Case Containment Center. The worm is wrapped around a moist ban­dage, to pre­vent it break­ing and caus­ing in­fec­tion

A pa­tient with a guinea worms emerg­ing, at the Savelugu Case Containment Center. The worm is wrapped around a moist ban­dage, to pre­vent it break­ing and caus­ing in­fec­tion

A de­bil­i­tat­ing in­fec­tion from the par­a­sitic Guinea worm is inch­ing closer to global erad­i­ca­tion, with an all-time low of only 10 hu­man cases re­ported world­wide in 2025, the Carter Center an­nounced.

If health work­ers can fully wipe out the worms, it will be only the sec­ond hu­man dis­ease to be erad­i­cated, af­ter small­pox.

Guinea worm (Dracunculus medi­nen­sis) is a par­a­sitic ne­ma­tode trans­mit­ted in wa­ter. More specif­i­cally, it’s found in wa­ters that con­tain small crus­tacean cope­pods, which har­bor the wor­m’s lar­vae. If a per­son con­sumes wa­ter con­t­a­m­i­nated with Guinea worm, the par­a­sites bur­row through the in­testi­nal tract and mi­grate through the body. About a year later, a spaghetti noo­dle-length worm emerges from a painful blis­ter, usu­ally in the feet or legs. It can take up to eight weeks for the adult worm to fully emerge. To ease the sear­ing pain, in­fected peo­ple may put their blis­tered limbs in wa­ter, al­low­ing the par­a­site to re­lease more lar­vae and con­tinue the cy­cle.

In ad­di­tion to be­ing ex­tremely painful, the dis­ease (dracunculiasis) can lead to com­pli­ca­tions, such as sec­ondary in­fec­tions and sep­sis, which in turn can lead to tem­po­rary or per­ma­nent dis­abil­ity.

When the Guinea worm erad­i­ca­tion pro­gram be­gan in 1986, there were an es­ti­mated 3.5 mil­lion cases across 21 coun­tries in Africa and Asia. To date, only six coun­tries have not been cer­ti­fied by the World Health Organization as Guinea worm-free. In 2024, there were just 15 cases, and, ac­cord­ing to the pro­vi­sional tally for 2025, the num­ber is down to just 10. It’s con­sid­ered pro­vi­sional un­til each coun­try’s dis­ease re­ports are con­firmed, which oc­curs in a pro­gram meet­ing usu­ally held in April.

Getting to zero

The 10 hu­man cases in 2025 were iden­ti­fied in three coun­tries: four in Chad, four in Ethiopia, and two in South Sudan.

To fully erad­i­cate the dis­ease, cases in an­i­mals (infected by the same species of worm) must also be wiped out. In 2025, an­i­mal cases were de­tected in Chad (147 cases), Mali (17), Cameroon (445), Angola (70), Ethiopia (1), and South Sudan (3).

The erad­i­ca­tion pro­gram works by of­fer­ing cash re­wards for re­port­ing cases in ar­eas where the worm is pre­sent. Those re­ports are then in­ves­ti­gated and fol­lowed to pre­vent trans­mis­sion and iden­tify the source. Tools in­clude pub­lic ed­u­ca­tion on wound care and safer drink­ing wa­ter prac­tices, such as boil­ing and fil­tra­tion. Water sources can also be treated with a lar­vi­cide.

Since 1986, the erad­i­ca­tion pro­gram has been es­ti­mated to have pre­vented 100 mil­lion cases.

“Guinea worm causes im­mense suf­fer­ing—not just for the in­di­vid­ual but for their fam­ily and com­mu­nity as well,” Adam Weiss, di­rec­tor of the Carter Center Guinea Worm Eradication Program, said. “Every case is a real per­son we know by name. They are en­dur­ing a dis­ease we know how to pre­vent, and we’ve been given this rare op­por­tu­nity to wipe it out com­pletely. We’re en­er­gized by this year’s progress, but zero is the only ac­cept­able num­ber, and that’s why our com­mit­ment to fin­ish­ing this job is un­wa­ver­ing.”

Beth is Ars Technica’s Senior Health Reporter. Beth has a Ph. D. in mi­cro­bi­ol­ogy from the University of North Carolina at Chapel Hill and at­tended the Science Communication pro­gram at the University of California, Santa Cruz. She spe­cial­izes in cov­er­ing in­fec­tious dis­eases, pub­lic health, and mi­crobes.

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over the past week the dis­course around open­claw (which i’ll re­fer to as clawd­bot) has ab­solutely ex­ploded. it has felt to me like all threads of con­ver­sa­tion have veered to­wards the ex­treme and in­de­fen­si­ble. some are run­ning clawd­bot with un­lim­ited per­mis­sions on their main com­put­ers. oth­ers are run­ning it in the cloud and blow­ing through to­kens like snow. fi­nally, alarm­ingly (and very sen­sa­tion­ally), peo­ple are con­nect­ing their clawd­bots to­gether on a so­cial net­work so they can plot the demise of their hu­mans to­gether.

does any of this make sense? of course not. but i think the vi­ral­ity and silli­ness—lead­ing many to con­clude that sit­ting this one out is the only sane choice—has blinded peo­ple to some­thing real.

i want to quickly write down where i am on my jour­ney and share a bull case from what i think is a rea­soned per­spec­tive. where i started some­where luke­warm, i ended up much closer to the deep end than i ex­pected to be. af­ter winc­ing be­fore press­ing go, i’m now not sure i can go back to a world with­out clawd­bot.

this ar­ti­cle cov­ers what i’ve built, how i think about the risk, and what it’s taught me about this mo­ment in AI. the tar­get au­di­ence is a mod­er­ately+ tech­ni­cal per­son in­ter­ested in or skep­ti­cal of clawd­bot. if you just want the setup de­tails, skip to the end. every­one’s wel­come!

what i’ve been do­ing

i’ll be vul­ner­a­ble here (screenshots or it did­n’t hap­pen) and share ex­actly what i’ve ac­tu­ally set up:

clawd­bot picks up when i make a con­crete promise and date, and adds it to my cal­en­dar­clawd­bot de­tects when i have all the in­gre­di­ents for a cal­en­dar in­vite and then of­fers to make oneev­ery 15 min­utes, clawd­bot looks through new text mes­sages i’ve re­ceived, us­ing a script to iden­tify threads where i’ve sent a mes­sage since it last checked. (it ig­nores threads where i haven’t en­gaged.)if it finds that i’ve made a spe­cific promise about do­ing some­thing to­mor­row (“let me re­view this to­mor­row!“) it will cre­ate a cal­en­dar event for me the next day when i’m free.if spe­cific plans are be­ing made—for ex­am­ple, of­fer­ing a meet­ing slot to some­one—it will au­to­mat­i­cally drop a “hold” onto my cal­en­dar so that i don’t dou­ble book my­self. clawd­bot also checks: is there a time, place, and mu­tual con­fir­ma­tion? if there is, it drafts a cal­en­dar in­vite and asks me if i’d like to cre­ate it.these two au­toma­tions alone have helped me be­come more re­spon­sive and less for­get­ful. more im­por­tantly, they help text mes­sages catch up to email. we’ve long had great tool­ing for email—su­per­hu­man au­to­mat­i­cally re­minds me to fol­low up on emails and brings up my cal­en­dar in a side­bar when i type a date. tex­ting is the wild west and yet i text 100x more than i email.prepar­ing for the next day­clawd­bot looks at days when i am (or could be) down­town to find avail­abil­i­tiesat 8pm every night, clawd­bot goes through my cal­en­dar for the next day and iden­ti­fies meet­ings—cof­fee chats, lunches, phone calls, and more. it sends me a quick sum­mary. as a nat­ural in­tro­vert, it’s help­ful to pre­pare in ad­vance whether a day will be a “big day of meet­ings” or a heads down day. this also en­sures i wake up and get to the of­fice on time.i’m in a few com­mu­ni­ties with what­sapp and sig­nal groups that have high vol­ume (100+ mes­sages a day). i typ­i­cally mute these, but clawd­bot goes through them once a day and sum­ma­rizes in­ter­est­ing top­ics or con­ver­sa­tions for me.clawd­bot helps me check ho­tel prices. af­ter i do it once, i can eas­ily turn it into a cron job­clawd­bot is smart enough to browse through the list­ing to in­ter­pret my re­quire­ments (no pull-out beds)this is what a re­cur­ring up­date looks like.it’s stun­ningly easy to mon­i­tor the price of some­thing now, even if it’s com­pli­cated. whereas be­fore i would go look­ing for a price alert web­site, now i just paste the URL into clawd­bot and tell it to check every few hours if the price has changed.i cur­rently have over 30 price alerts set. these in­clude straight­for­ward alerts on prod­ucts i’m in­ter­ested in buy­ing. but they also in­clude pow­er­ful rea­son­ing guide­lines, like ho­tels and airbnbs in lake tahoe where “a pull­out bed is OK if it’s not in the same room as an­other bed.” clawd­bot ac­tu­ally re­views the pho­tos on the list­ing to en­sure they fit these cri­te­ria!i am cu­ri­ous to try more com­plex cri­te­ria that are cur­rently im­pos­si­ble tra­di­tion­ally (like avoid­ing ho­tel rooms that don’t have a door to the bath­room) or even sub­jec­tive cri­te­ria (vibe of the room is clean and ren­o­vated, not old and dingy).one mes­sage sets up pack­age track­ing. (since clawd­bot knows who it’s for, it will prob­a­bly even of­fer to text my dad for me when it’s de­liv­ered! haha)it turns out that clawd­bot’s web­site + cron func­tion­al­ity is good enough to mon­i­tor ba­si­cally any­thing. while i pay for sev­eral apps like flighty (flight mon­i­tor­ing) and par­cel (package track­ing), i’ve started to grav­i­tate to­wards sim­ply ask­ing clawd­bot to track these things in­stead.for ex­am­ple, with a USPS track­ing num­ber, it can let me know every day what the progress of my pack­age is. when some­thing seems stuck in tran­sit, it flags it. i no longer have to dig through emails or re­mem­ber which car­rier is de­liv­er­ing what. even open­ing the par­cel app to add a track­ing num­ber seems like un­nec­es­sary work now.as some­one who has a chest freezer and a com­pul­sive de­sire to buy too many things at costco, we take every­thing out of the freezer every few months to check what we have. be­fore, this was a rel­a­tively in­volved process: me call­ing things out, my part­ner writ­ing them down.now, i take pic­tures of every­thing in the freezer and send them to clawd­bot, which parses through each pic­ture (asking me if it’s con­fused about any­thing). it makes rea­son­able as­sump­tions on re­main­ing quan­ti­ties and adds the in­ven­tory to a list in no­tion. it also re­moves items from our gro­cery list if we’re al­ready well-stocked.i re­ally en­joy mak­ing blended asks: adding things to my gro­cery list, and check­ing/​resched­ul­ing my cal­en­dar all in the same con­ver­sa­tion­i’m sure this ex­ists in some com­pli­cated form via the NYT cook­ing app, but i now screen­shot recipes and send the in­gre­di­ent list to clawd­bot, which or­ga­nizes them into our gro­cery list in ap­ple re­minders. it’s smart enough to dedupe and com­bine in­gre­di­ents al­ready on the list (as well as ig­nore in­gre­di­ents we al­ready have)—2 car­rots be­comes 3 if the recipe calls for more.clawd­bot can log into resy and opentable as me (it even en­ters the 2FA code it finds in my texts). i haven’t au­to­mated any­thing here, but book­ing a table by talk­ing to clawd­bot is de­light­ful.for my part­ner and me, it looks through our cal­en­dars to find evenings when we’re both free and the restau­rant we want has avail­abil­ity (including click­ing through resy slots page by page—some­thing i used to do my­self). it then sug­gests op­tions back to me to con­firm, fill­ing in all my pref­er­ences.clawd­bot knows when i’m due for a clean­ing and can see my cal­en­dar. when i ask it to book an ap­point­ment, it logs into my den­tist’s por­tal, finds a slot that works (and where i will al­ready be near the den­tist of­fice), and con­firms with me be­fore book­ing. one less thing to for­get about.one thing i’m ex­per­i­ment­ing with, as clawd­bot has more con­text about me, is whether i can trust it to fill out forms on my be­half—for ex­am­ple, to book a ven­dor. clawd­bot takes a first stab at an­swer­ing any ques­tions it knows the an­swer to and then asks me for the rest in a slack mes­sage. we work­shop the an­swers back and forth and then clawd­bot sub­mits the form.it oc­ca­sion­ally gets lost in nested frames (which de­creases my trust in its abil­ity to do this well), but it’s re­mark­ably per­sis­tent at mak­ing it through a lengthy ques­tion­naire, even across mul­ti­ple pages. it also has a lovely in­tu­itive sense for many things—like uncheck­ing mar­ket­ing emails.i was pleas­antly sur­prised early on that clawd­bot picks up im­age at­tach­ments from slack na­tive­ly­clawd­bot is just bet­ter at mak­ing todo items than i am.when i vis­ited REI this week­end to find run­ning shoes for my part­ner, i took a pic­ture of the shoe and sent it to clawd­bot to re­mind my­self to buy them later in a dif­fer­ent color not avail­able in store. the todo item clawd­bot cre­ated was ex­cep­tion­ally de­tailed—pulling out the brand, model, and size—and even adding the prod­uct list­ing URL it found on the REI web­site.through the course of di­al­ing in my clawd­bot, it has cre­ated many tools, skills, work­flows, and pref­er­ences. this is one of the beau­ties of clawd­bot (and LLMs with mem­ory in gen­eral): they get bet­ter as you use them, and they are gen­uinely re­mark­able at learn­ing your pref­er­ences.i some­times nudge this along by ex­plic­itly ask­ing clawd­bot to “make a note” of var­i­ous re­quests—for ex­am­ple, how a cal­en­dar event ti­tle should be for­mat­ted.to get vis­i­bil­ity into how this process is go­ing (mostly out of cu­rios­ity), clawd­bot writes a hu­man-read­able ver­sion of each work­flow and pushes it up to a no­tion data­base. these work­flows can be in­cred­i­bly in­tri­cate and de­tailed as it learns to nav­i­gate dif­fer­ent edge cases.for ex­am­ple, if a resy restau­rant has a reser­va­tion can­cel­la­tion fee, clawd­bot now in­forms me of the fee, asks me to con­firm again if it’s not re­fund­able, and in­cludes the can­cel­la­tion dead­line in the cal­en­dar event it cre­ates.these are lit­tle things that, from my ex­pe­ri­ence work­ing with a hu­man per­sonal as­sis­tant (more on this later), take months or years to dial in. with clawd­bot, this was nearly sin­gle shot.see­ing these work­flows in no­tion (1) awes me with how much i’ve built up in very lit­tle time, with al­most no con­scious “configuration” in the tra­di­tional sense; and (2) with no­tion’s ver­sion con­trol, i get a diff view to see how each work­flow has evolved over time. both are in­cred­i­bly sat­is­fy­ing for the en­gi­neer in me.

on the shape of risk

let me be up­front about how much ac­cess i’ve given clawd­bot: it can read my text mes­sages, in­clud­ing two-fac­tor au­then­ti­ca­tion codes. it can log into my bank. it has my cal­en­dar, my no­tion, my con­tacts. it can browse the web and take ac­tions on my be­half. in the­ory, clawd­bot could drain my bank ac­count. this makes a lot of peo­ple un­com­fort­able (me in­cluded, even now).

some­times i think about my ex­pe­ri­ence with my (human) per­sonal as­sis­tant who helps me with var­i­ous tasks. to do her job, she has my credit card in­for­ma­tion, ac­cess to my cal­en­dar, copies of my flight con­fir­ma­tions, and a doc­u­ment with my fam­i­ly’s pass­port num­bers. she is abroad and i’ve never met her in per­son.

i trust her be­cause i’ve built trust over time but also be­cause i have to. with­out that trust—with­out shar­ing my se­crets—she can­not do her job. the help and the risk are in­sep­a­ra­ble.

all del­e­ga­tion in­volves risk. with a hu­man as­sis­tant, the risks in­clude: in­ten­tional mis­use (she could run off with my credit card), ac­ci­dents (her com­puter could get stolen), or so­cial en­gi­neer­ing (someone could im­per­son­ate me and re­quest in­for­ma­tion from her).

with clawd­bot, i’m trad­ing those risks for a dif­fer­ent set: prompt in­jec­tion at­tacks, model hal­lu­ci­na­tions, se­cu­rity mis­con­fig­u­ra­tions on my end, and the gen­eral un­pre­dictabil­ity of an emerg­ing tech­nol­ogy. i think these risks are com­pletely dif­fer­ent and lead to a dif­fer­ent set of con­sid­er­a­tions (for ex­am­ple, clawd­bot’s de­fault con­fig­u­ra­tion has a ton of per­son­al­ity to be fun and chaotic on pur­pose, which feels un­nec­es­sar­ily risky to me).

the in­crease in risk is largely cor­re­lated to the in­crease in help­ful­ness. the peo­ple most at risk from AI as­sis­tants are the peo­ple get­ting the most value from them. my learn­ing is that the first bits of risk led to a lot more help­ful­ness.

if some­thing is­n’t work­ing or use­ful, i do take the per­mis­sion away. i also take pre­cau­tions—i run clawd­bot on an iso­lated ma­chine and con­strain which sites it vis­its. when i’m un­sure what it’s do­ing, i ask it to take a screen­shot; this has been in­valu­able for catch­ing mis­takes and build­ing trust in new work­flows. but i also have it do things that would make most se­cu­rity pro­fes­sion­als wince, like read­ing my 2FA codes and log­ging into my bank.

what sur­prised me most was how quickly i found my­self want­ing to give it more ac­cess, not less. every new per­mis­sion un­locked some­thing use­ful, and the value ac­cu­mu­lated faster than my cau­tion could keep up. most of the on­line dis­course is about lock­ing it down; my ex­pe­ri­ence has been the op­po­site pull. it comes down to whether the value jus­ti­fies the risk for you.

the dis­course around clawd­bot has been po­lar and, be­cause some peo­ple have been overtly evan­gel­i­cal, many crit­ics feel as­tro­turfed or oth­er­wise sold to.

amongst smart peo­ple i know there’s a sur­pris­ingly high cor­re­la­tion be­tween those who con­tinue to be unim­pressed by AI and those who use a hob­bled ver­sion of it. for some it’s a com­pany-is­sued ver­sion of chat­gpt/​gem­ini with mem­ory dis­abled, and for oth­ers it’s a self-in­flicted de­ci­sion to limit LLM mem­ory, con­text, and tools (usually an­chored around safety and risk).

we’re taught that lim­it­ing scope is good (keeps the AI fo­cused) and safe (keeps bad things from hap­pen­ing). this is true but my ex­pe­ri­ences with clawd­bot com­pletely fried this teach­ing. the sweet sweet elixir of con­text is a real “feel the AGI” mo­ment and it’s hard to go back with­out feel­ing like i would be will­ingly liv­ing my most im­por­tant re­la­tion­ship in am­ne­sia.

this is­n’t a novel in­sight—com­pa­nies know that con­text is the whole game and are work­ing to or­ga­nize their data for AI. but for in­di­vid­u­als, this world has been closed off. your AI in­ter­ac­tions are flat and state­less—data in, re­sponse out, noth­ing build­ing over time. when google an­nounced gem­i­ni’s gmail in­te­gra­tion, peo­ple got ex­cited: fi­nally, an AI that knows me! but when they tried it, it was shal­low and dis­ap­point­ing and could­n’t fig­ure out your spirit an­i­mal from your email style, and they moved on.

if you’re in­ter­ested in cap­tur­ing this value, three things have stood out for me:

i think pro­duc­tiv­ity lift from AI use falls into three phases: gath­er­ing in­for­ma­tion, im­prov­ing it, and ac­tion­ing on it. most us­age to­day fo­cuses on the mid­dle—you gather data your­self, hand it to the AI to im­prove, then ac­tion on it your­self.

for knowl­edge work, this makes sense. there’s a lot to im­prove—sum­ma­riz­ing, trans­lat­ing, cri­tiquing. but per­sonal AI is dif­fer­ent. there’s not much to im­prove; you al­ready know what needs to hap­pen. the lift comes from gath­er­ing and ac­tion­ing.

mak­ing cal­en­dar events is un­in­ter­est­ing. fig­ur­ing out when one needs to hap­pen—by mon­i­tor­ing my texts—and then cre­at­ing it for me? that’s in­ter­est­ing.

one place to start: how can you take data from one place and move it to an­other iso­lated sys­tem? from your text mes­sages to a restau­rant book­ing? from gra­nola meet­ing notes to a fol­low-up email?

if you’re en­gi­neer-brained like me, you grav­i­tate to­wards scripts and play­books—what­ever you can do to con­strain the AI and make its be­hav­ior pre­dictable. this works, and for high-stakes sit­u­a­tions it might be the only way to get com­fort­able.

but the up­side to let­ting go has been 10x, not 10%. i did­n’t see that com­ing. it’s the same thing i’ve heard from peo­ple us­ing claude code—you can’t un­der­stand how much you’re leav­ing on the table un­til you let go. the whole rea­son i’m us­ing an LLM and not a tra­di­tional script is that it can han­dle am­bi­gu­ity, in­ter­pret in­tent, and fig­ure things out on the fly.

early on, i wanted clawd­bot to fetch web pages as text only, be­liev­ing that to be safer (it is). if i’d stuck to that, i would never have dis­cov­ered it could look through airbnb list­ing pho­tos to find a place match­ing my ex­act cri­te­ria (“a pull­out bed is okay if it’s not in the same room as an­other bed”). i did­n’t pro­gram that. i just de­scribed what i wanted and let it fig­ure out how. not spelling out how i wanted clawd­bot to work made it a LOT bet­ter.

a cur­rent AI en­gi­neer­ing adage: treat AI like a ju­nior soft­ware en­gi­neer. guide it through build­ing a plan, watch its first at­tempts care­fully, chal­lenge its rea­son­ing.

this ap­plies to clawd­bot too, but it re­quires pa­tience. it’s easy to give up on a work­flow when you watch it fum­ble (“let me try click­ing this again. did­n’t work. let me try again.“).

re­sist the urge to write clawd­bot off. if you’re wor­ried, ask it what it plans to do be­fore it does it and ask for a screen­shot when you want to ver­ify it’s got the right page open. when an edge case breaks a work­flow, treat it as a teach­ing op­por­tu­nity. once you’ve cor­rected it, it won’t make that mis­take again.

clawd­bot gets mean­ing­fully bet­ter the more you use it, and it gets bet­ter in a fast, or­ganic way that feels less cum­ber­some than writ­ing rules for claude code or yelling at any other LLM. it feels much closer to work­ing with a real ex­ec­u­tive as­sis­tant (in part be­cause the clawd­bot har­ness/​sys­tem prompts are very good), which makes me want to give it more and more re­spon­si­bil­ity.

how’d you set it up?

i run clawd­bot on a mac mini in my home. the mac mini’s pri­mary job is run­ning clawd­bot and it stays on 24/7. why a mac mini?

one of the core use cases is brows­ing web­sites and some­times log­ging into them. to do this con­vinc­ingly (without trig­ger­ing tons of captchas and “is this a new IP?” alerts), clawd­bot needs to be open­ing sites from my home, not the cloud; and it needs to do so in a real google chrome win­dow.

many of the ways clawd­bot ac­cesses data are mac-only. specif­i­cally, clawd­bot can read and send iMes­sages (real blue bub­bles!); man­age my todo and gro­cery lists in ap­ple re­minders; and use my ap­ple con­tacts as a source of truth. ap­ple will only let you do these things with­out get­ting banned on a real bona fide mac.

i com­mu­ni­cate with clawd­bot via a pri­vate slack work­space. many oth­ers have shot them­selves in the foot set­ting it up on what­sapp or telegram (since the bot re­sponds as you to oth­ers). slack is great be­cause:

it’s fa­mil­iar to me—i’ve spent over a decade work­ing in and man­ag­ing slack work­spaces.

i can cre­ate sep­a­rate chan­nels for dif­fer­ent top­ics. #ai-notifs is only for in­bound alerts.

i can have sev­eral work­flows go­ing at once, since each chan­nel’s his­tory is iso­lated. i cre­ated #ai-1, #ai-2, #ai-3, and so on—just for mul­ti­task­ing. (i may ex­plore adding my part­ner at some point, and it’ll be easy since slack is, well, meant for mul­ti­player.)

clawd­bot com­mu­ni­cates with me by send­ing slack no­ti­fi­ca­tions. be­hind the scenes it also makes changes to my cal­en­dar—mov­ing events around, adding “soft hold” events, send­ing in­vites—and man­ages my ap­ple re­minders and no­tion pages. clawd­bot never com­mu­ni­cates with oth­ers on its own.

i give clawd­bot a toolkit of ac­cess. the most use­ful ones have been:

my text mes­sages. i con­duct a lot of work and daily life over imes­sage. frus­trat­ingly, un­like email, tex­ting has very poor tool­ing. where my email app au­to­mat­i­cally pulls up my cal­en­dar when it sees dates/​times, tex­ting me “call to­mor­row 4pm?” does not. when some­one sends me a cal­en­dar in­vite, it’s both in my in­box and on my cal­en­dar; when some­one texts me “yep let’s do it”, nei­ther is true. clawd­bot has given me mas­sive lift here. (yes, this also gives clawd­bot ac­cess to 2FA codes.)

my cal­en­dar. i also have a shared cal­en­dar with my part­ner; clawd­bot sees both.

my no­tion work­space. for me this is a gen­eral catch-all for stor­ing and man­ag­ing in­for­ma­tion; the ap­ple notes app could also work.

web brows­ing. in a way this is the most im­por­tant one—it’s in­fi­nite tools in one. but it’s also where the risk con­cen­trates, so i al­ways give clawd­bot a start­ing URL rather than let­ting it browse freely.

no­tably, i haven’t given clawd­bot ac­cess to my email—my tool­ing there is al­ready good enough that i usu­ally do things my­self. i’ve also found the ways clawd­bot can help here to be cum­ber­some and lim­ited. i may re­visit if i find a killer use case.

i don’t al­low my clawd­bot to ac­cess so­cial net­work­ing web­sites (it does­n’t read x/​twit­ter, for ex­am­ple). this seems high risk and no re­ward.

i don’t give clawd­bot ac­cess to all my lo­gins. (there’s a 1password in­te­gra­tion which is… pretty wild.) when i do, i try to use google chrome’s na­tive pass­word man­ager so that clawd­bot does­n’t need to man­age pass­words in con­text di­rectly. (note that it still has ac­cess to pass­words be­cause it can aut­ofill and then read it off the page, but i’ve at least added more hoops.)

i don’t let clawd­bot send text mes­sages with­out my ex­plicit ap­proval, and i’ve built safe­guards in those skills to en­force this.

i did­n’t add my clawd­bot to molt­book so it can plot against me at my ex­pense. sorry.

i use claude opus 4.5. i haven’t ex­per­i­mented with cheaper mod­els. my view is that any mis­take by the model costs me way more than the pre­mium, so i’d rather stay on the cut­ting edge than try to op­ti­mize for to­kens.

con­text man­age­ment can be an­noy­ing. when clawd­bot is brows­ing sites or do­ing re­search, con­text oc­ca­sion­ally fills up and gets com­pacted (older con­ver­sa­tion his­tory gets deleted to make room). this al­ways seems to hap­pen at the worst time—right when i’m deep into some­thing and have built up mo­men­tum. a frus­trat­ing “ugh, i guess this re­ally is just a word pre­dic­tor” mo­ment. to avoid this i’m con­stantly start­ing new ses­sions, which i wish clawd­bot would do for me.

clawd­bot does­n’t know when to give up. its de­ter­mi­na­tion is usu­ally a strength, but it lacks the hu­man cir­cuit breaker of “am i try­ing too hard here?” and some­times burns through a lot of time/​to­kens on some­thing a hu­man would have aban­doned.

Have you won­dered why the stock mar­ket has been so choppy since October and why crypto and gold keep flash crash­ing? The west­ern me­dia would have you be­lieve this is due to AI bub­ble, war in Greenland, and Trump’s tweets. We have a bet­ter story to tell.

There’s been a fair bit of quiet chaos in fi­nan­cial mar­kets re­cently. Cryptocurrencies have lost 40% of their value. We saw sil­ver drop 40% which has­n’t hap­pened since 1980. Stocks like Microsoft are get­ting picked off one-by-one with 15% drops when pos­i­tive earn­ings re­ports come out. Meanwhile the broader mar­ket chops side­ways, so peo­ple think things are fine. Trump and Europe were on the brink of war for con­trol of a des­o­late arc­tic ter­ri­tory. Truth Social has over­taken FOMC as the most im­por­tant source of fi­nan­cial news. These things may all ap­pear to the un­trained eye as a se­ries of idio­syn­cratic, dis­con­nected shocks. The pre­vail­ing me­dia nar­ra­tive is that the mar­ket is re­act­ing neg­a­tively to AI CapEx spend­ing and a hawk­ish new Fed chair. But our sys­tem­atic analy­sis of cross-as­set flows, de­riv­a­tives po­si­tion­ing, cen­tral bank pol­icy min­utes, and in­sti­tu­tional bal­ance sheets sug­gests a sin­gu­lar, uni­fied causal­ity that binds these dis­parate anom­alies, which is the covert un­wind­ing of the Japanese Yen carry trade.

For nearly thirty years, the Bank of Japan’s (BOJ) Zero Interest Rate Policy (ZIRP) and sub­se­quent Negative Interest Rate Policy (NIRP) ef­fec­tively trans­formed the Yen into the world’s fund­ing cur­rency. We would call it the great­est free money printer ever made. By an­chor­ing bor­row­ing costs at or near zero, the BOJ en­abled Wall Street to bor­row Yen cheaply and in­vest it with lever­age into higher yield­ing in­stru­ments glob­ally, such as U. S. trea­suries, eq­ui­ties, and cryp­tog­ra­phy. For ex­am­ple, you bor­row Yen from Japan at 0% in­ter­est, you ex­change it for USD, and then you buy trea­sury bonds that pay 4%. It’s that sim­ple. This funded gov­ern­ment ben­e­fits and pro­vided con­tin­u­ous re­li­able liq­uid­ity for fi­nan­cial mar­kets that made stocks keep go­ing up while sup­press­ing volatil­ity.

Trillions of dol­lars of free loans from the Bank of Japan were used by a gen­er­a­tion of in­vestors to buy a dou­ble digit per­cent­age of the U. S. econ­omy. Now those loans are be­ing re­called. Wall Street traders who lev­ered up on the free Japanese money now have to sell tril­lions of as­sets and con­vert the pro­ceeds back to Yen in or­der to not be liq­ui­dated. These aren’t happy times for them. They get liq­ui­dated when Japan raises in­ter­est rates; they get liq­ui­dated when the Federal Reserve low­ers in­ter­est rates; they get liq­ui­dated when the Japanese Yen in­creases in value; they get liq­ui­dated when tech stocks aren’t go­ing up enough, and all four of these things have been hap­pen­ing at once.

Wall Street may be greedy, but they’re very in­tel­li­gent too. They made many smart choices about where to put the “free” money. Now let’s say you’re some­one who’s also smart, but was wise enough to not use Sauron’s ring. Chances are you in­vested in the same things as Wall Street. So by now you’ve prob­a­bly seen your whole port­fo­lio move against you; you’re won­der­ing why your hedges don’t work; and you feel like you’re be­ing pun­ished for mak­ing all the right choices. It’s be­cause other smart peo­ple, who got greedy, are be­ing forced to close their po­si­tions, and you’re the whip­ping boy for their avarice.

The Japanese Yen is sort of like GameStop ($GME). It’s the most shorted cur­rency on Earth. When you bor­row yen to buy American as­sets, you’re ef­fec­tively short­ing the yen. Currency can be re­hy­poth­e­cated so that yen-de­nom­i­nated debt ends up ex­ceed­ing the ac­tual yen sup­ply, the same way GME’s short in­ter­est ex­ceeded 100% of its float. When shorts start cov­er­ing it com­pounds tragedy, be­cause they all have to buy yen, which makes its value in­crease, forc­ing more shorts to cover, and Japan is a small is­land.

This December 2025 rate hike to 0.75%, fol­lowed by the ex­plic­itly hawk­ish sig­nalling from Prime Minister Sanae Takaichi’s ad­min­is­tra­tion, has fun­da­men­tally al­tered the risk-re­ward cal­cu­lus of these lever­aged po­si­tions. The mar­ket dis­rup­tions ob­served in January 2026 bear the dis­tinct math­e­mat­i­cal sig­na­ture of a forced liq­ui­da­tion event rather than a fun­da­men­tal repric­ing of growth prospects. When cor­re­la­tions be­tween his­tor­i­cally un­cor­re­lated as­sets (e.g. Gold, Bitcoin, Microsoft, and Silver) ap­proach 1.0 dur­ing a sell-off, it serves as a dis­tinct in­di­ca­tor that traders are not sell­ing what they want to sell, but rather what they must sell in or­der to meet mar­gin calls in a fund­ing cur­rency that is rapidly ap­pre­ci­at­ing against their li­a­bil­i­ties.

We shall in­ves­ti­gate the me­chan­ics of this un­wind in ex­haus­tive de­tail. We an­a­lyze the “Greenland Distraction” not as a root cause but as a volatil­ity trig­ger that shat­tered the com­pla­cent calm of the “Davos Consensus.” We ex­am­ine the anom­alous liq­ui­da­tion in pre­cious met­als fol­low­ing the nom­i­na­tion of Kevin Warsh to the Federal Reserve Chairmanship, and we dis­sect the flow of funds from ma­jor Japanese in­sti­tu­tional whales like Norinchukin Bank, whose re­treat from for­eign bond mar­kets has left a liq­uid­ity vac­uum in the U. S. Treasury com­plex. The ev­i­dence points to a sys­temic repric­ing of the global cost of cap­i­tal, orig­i­nat­ing in Tokyo and trans­mit­ting vi­o­lently through the plumb­ing of Wall Street, leav­ing no as­set class un­touched.

To fully com­pre­hend the mar­ket chaos of January 2026, one must look be­yond the im­me­di­ate head­lines of the new year and scru­ti­nize the sub­tle yet seis­mic shifts that oc­curred in Tokyo dur­ing the clos­ing months of 2025. The con­ven­tional mar­ket nar­ra­tive has long re­garded the Bank of Japan as a pas­sive, al­most par­a­lyzed ac­tor, per­pet­u­ally trapped in a de­fla­tion­ary mire and un­able to nor­mal­ize pol­icy. This view has al­ways been demon­strat­ably false. The truth is that Wall Street lead­ers have been plan­ning for the next quar­ter, while the Japanese have been prepar­ing for the next cen­tury. The data con­firms a de­lib­er­ate, ag­gres­sive shift to­ward nor­mal­iza­tion that caught global carry traders of­f­guard.

In a move that many Western an­a­lysts crit­i­cally un­der­es­ti­mated, the Policy Board of the Bank of Japan voted unan­i­mously to raise the un­col­lat­er­al­ized overnight call rate to 0.75% dur­ing its pol­icy ses­sion on December 18-19, 2025. While a 25 ba­sis point hike might ap­pear neg­li­gi­ble in the con­text of Federal Reserve or ECB tight­en­ing cy­cles, in the con­text of the Japanese fi­nan­cial sys­tem, which has op­er­ated near the zero-bound for decades, it rep­re­sents a mas­sive tight­en­ing of fi­nan­cial con­di­tions.

This move was not merely a tech­ni­cal ad­just­ment; it was a fun­da­men­tal regime change. Coming from a base­line of -0.1% in early 2024 and 0.50% in late 2025, the move to 0.75% sig­naled that the era of “free money” had de­fin­i­tively ended. The ra­tio­nale pro­vided by the BOJ was grounded in shift­ing in­fla­tion­ary dy­nam­ics. Core CPI (excluding fresh food), the cen­tral bank’s pre­ferred met­ric, was track­ing near 3% in late 2025, per­sis­tently ex­ceed­ing the 2% price sta­bil­ity tar­get. Although in­fla­tion eased slightly to 2.4% in December, the BOJ min­utes re­veal a board con­vinced that “wage gains may be durable,” thus jus­ti­fy­ing higher rates to pre­vent a wage-price spi­ral.

Crucially, the min­utes from the December meet­ing, which were re­leased in late January 2026, con­tain ex­plicit lan­guage sug­gest­ing that the tight­en­ing cy­cle is far from com­plete. The board noted that “real in­ter­est rates are ex­pected to re­main neg­a­tive,” im­ply­ing that a pol­icy rate of 0.75% is still con­sid­ered ac­com­moda­tive rel­a­tive to in­fla­tion. To a bond trader, this is hawk­ish code. It sug­gests that the “neutral rate” is sig­nif­i­cantly higher, po­ten­tially be­tween 1.5% and 2.0%. If the mar­ket prices in a ter­mi­nal rate of 2.0%, the cost of fund­ing for carry trades ef­fec­tively triples from pre­vi­ous lev­els, turn­ing prof­itable ar­bi­trage po­si­tions into deep losses.

The po­lit­i­cal di­men­sion in Japan has ex­ac­er­bated the mon­e­tary tight­ness, cre­at­ing a “double tight­en­ing” ef­fect that al­go­rithms have strug­gled to price. Prime Minister Sanae Takaichi, prepar­ing for a snap elec­tion on February 8, 2026, has adopted a com­plex eco­nomic stance that blends fis­cal ex­pan­sion with mon­e­tary dis­ci­pline, a volatile mix for cur­rency mar­kets.

Takaichi ad­vo­cates for “strategic fis­cal spend­ing” and tax cuts to stim­u­late the do­mes­tic econ­omy. In stan­dard macro­eco­nomic the­ory, an ex­pan­sion­ary fis­cal pol­icy (increased gov­ern­ment spend­ing) com­bined with a tight­en­ing mon­e­tary pol­icy (higher rates to com­bat the re­sult­ing in­fla­tion) is the per­fect recipe for cur­rency ap­pre­ci­a­tion. While Takaichi has pub­licly soft­ened her rhetoric to avoid ac­cu­sa­tions of cur­rency ma­nip­u­la­tion, stat­ing she “did not have a pref­er­ence for the yen’s di­rec­tion”, her poli­cies speak louder than her sound­bites.

The mar­ket fears that Takaichi’s pro­posed fis­cal largesse will force the BOJ to hike rates faster than cur­rently pro­jected to coun­ter­act the in­fla­tion­ary ef­fects of gov­ern­ment spend­ing. This cre­ates a two-front war on the Yen carry trade:

Exchange Rate Risk: If the Yen ap­pre­ci­ates due to the fis­cal-mon­e­tary pol­icy mix, the prin­ci­pal value of the USD-denominated as­sets held by Japanese in­vestors falls in Yen terms, trig­ger­ing mar­gin calls.

The ten­sion be­tween the Prime Minister’s of­fice and the Ministry of Finance (MOF) adds an­other layer of un­cer­tainty. Finance Minister Satsuki Katayama has been far less tol­er­ant of cur­rency volatil­ity, re­peat­edly in­ter­ven­ing or threat­en­ing in­ter­ven­tion when USD/JPY ap­proaches the 155-160 dan­ger zone. This po­lit­i­cal fric­tion cre­ates a “floor” for the Yen, mak­ing short­ing the cur­rency a per­ilous en­deavor for global macro funds.

Perhaps the most crit­i­cal, yet un­der­re­ported, de­vel­op­ment is the be­hav­ior of Japan’s gar­gan­tuan in­sti­tu­tional in­vestors, specif­i­cally Norinchukin Bank (often re­ferred to as the “CLO Whale”) and Nippon Life Insurance. These en­ti­ties have his­tor­i­cally been the largest buy­ers of U. S. debt, re­cy­cling Japan’s trade sur­plus into U.S. Treasuries and cor­po­rate bonds.

The data in­di­cates a mas­sive re­ver­sal in these flows. Following sig­nif­i­cant losses in 2024 and 2025 due to un­hedged ex­po­sure to U. S. and European sov­er­eign bonds, Norinchukin has been ac­tively liq­ui­dat­ing for­eign as­sets. By the end of December 2025, the bank had un­loaded nearly ¥12.8 tril­lion (approximately $88 bil­lion) in for­eign gov­ern­ment bonds.The bank’s CEO, Taro Kitabayashi, con­firmed the com­ple­tion of this sell-off, stat­ing the bank would “take its time” be­fore com­mit­ting cap­i­tal to fresh in­vest­ments.

The sig­nif­i­cance of this can­not be over­stated. A ma­jor, price-in­sen­si­tive buyer of U. S. debt has left the build­ing. When the U.S. Treasury is­sues debt to fund its deficit, Norinchukin is no longer the guar­an­teed bid. This re­moval of liq­uid­ity sup­port weak­ens the floor for U.S. Treasuries, con­tribut­ing to the yield spikes seen in January. Similarly, Nippon Life has sig­naled a ro­ta­tion back into do­mes­tic Japanese Government Bonds (JGBs), ac­knowl­edg­ing that “unrealized losses” on for­eign bonds had swelled to ¥4.7 tril­lion.The logic is sim­ple: why take cur­rency risk for a 4.5% U.S. yield when do­mes­tic JGB yields are ris­ing and of­fer a risk-free re­turn in your home cur­rency?

By December 31, 2025, the stage was set. The “free money” era was over. The largest hold­ers of cap­i­tal in Tokyo were repa­tri­at­ing funds or mov­ing into cash. Global mar­kets, how­ever, were still po­si­tioned for “business as usual”, long Nvidia, long Bitcoin, short Yen. The dis­so­nance be­tween Japanese re­al­ity and Western po­si­tion­ing cre­ated the per­fect con­di­tions for a crash.

To val­i­date the the­sis that the Yen un­wind is the pri­mary dri­ver of volatil­ity, we must ex­am­ine the se­quence of events. The crash did not hap­pen in a vac­uum; it fol­lowed a pre­cise time­line where geopo­lit­i­cal shocks acted as trig­gers for a struc­tural fragility that had been build­ing since the BOJ’s December pivot.

The pres­sure be­gan to build in Q4 2025. As the BOJ sig­naled its in­ten­tion to hike rates, Japanese traders, of­ten the “canary in the coal mine” for global liq­uid­ity, be­gan to re­duce risk. This cy­cle started with Bitcoin. Bitcoin is a pure liq­uid­ity as­set; it has no yield and is of­ten funded via mar­gin. As the cost of Yen mar­gin rose, Japanese sell­ing pres­sure on Bitcoin in­ten­si­fied from October through December. This was the first tremor.

Was the “Greenland War” the­ater? While the mil­i­tary di­men­sions may have been per­for­ma­tive, the eco­nomic con­se­quences were tan­gi­ble and acted as the cat­a­lyst that ex­posed the fragility of the Yen carry trade.

On January 17, 2026, President Trump es­ca­lated his de­mand to pur­chase Greenland by threat­en­ing a 10% tar­iff on eight European na­tions (including the UK, Germany, and France) and es­ca­lat­ing to 25% by June if the ter­ri­tory was not ceded. This in­tro­duced a “tail risk” that mar­kets had not priced: the frac­ture of the Atlantic eco­nomic al­liance.

Following the Martin Luther King Jr. hol­i­day, U. S. mar­kets opened on January 20 to a blood­bath. The S&P 500 fell 2.1%, the Nasdaq com­pos­ite dropped 2.4%, and yields on U.S. Treasuries spiked.The nar­ra­tive was “Greenland,” but the mar­ket me­chan­ics told a dif­fer­ent story. The threat of tar­iffs on close al­lies dis­rupts the “Atlantic Trade” nar­ra­tive. For Japanese in­vestors hold­ing U.S. as­sets, this in­tro­duced a new risk pre­mium. It was­n’t just about rates any­more; it was about the sta­bil­ity of the U.S.-led global or­der. This geopo­lit­i­cal volatil­ity forced risk par­ity funds and al­go­rith­mic traders to re­duce gross ex­po­sure. When a global port­fo­lio delever­ages, it buys back its fund­ing cur­rency. In this case, it bought Yen.

While Trump walked back the mil­i­tary threat on January 21 at Davos, the eco­nomic threat of tar­iffs re­mained a live wire. The volatil­ity per­sisted, sug­gest­ing that the “Greenland” nar­ra­tive was merely the match that lit the fuse of a much larger pow­der keg.

The fi­nal and most vi­o­lent phase of the crash oc­curred at the end of the month, trig­gered by the nom­i­na­tion of Kevin Warsh as Federal Reserve Chair. Warsh is widely per­ceived as a hawk, fa­vor­ing sound money and skep­ti­cism to­ward quan­ti­ta­tive eas­ing. His nom­i­na­tion sig­naled the po­ten­tial end of the “Fed Put”, the as­sump­tion that the cen­tral bank would al­ways in­ter­vene to sup­port as­set prices.

This an­nounce­ment trig­gered a mas­sive repric­ing of the “Debasement Trade.” Assets that thrive on cur­rency de­base­ment, Gold, Silver, and Bitcoin, col­lapsed. Gold fell ~11%, and Silver crashed ~36% in a sin­gle ses­sion. This syn­chro­niza­tion of losses across un­cor­re­lated as­sets (Tech and Gold falling to­gether) is the de­fin­i­tive sig­na­ture of a liq­uid­ity cri­sis dri­ven by mar­gin calls.

The un­wind­ing of a carry trade is not a mono­lithic event; it is a cas­cade that rip­ples out­ward from the most liq­uid and spec­u­la­tive as­sets to the core hold­ings of in­sti­tu­tional port­fo­lios. The se­quence of as­set price col­lapses ob­served from October 2025 to January 2026 fol­lows this clas­sic liq­ui­da­tion hi­er­ar­chy per­fectly.

As noted, the un­wind be­gan in the crypto mar­kets. Japan is home to a mas­sive re­tail crypto trad­ing base, and the Yen is a ma­jor pair for Bitcoin trad­ing. Snippets in­di­cate that Japanese traders be­gan sell­ing off Bitcoin in October 2025.

This tim­ing is cru­cial. It cor­re­lates with the pe­riod when the BOJ be­gan sig­nal­ing the December rate hike. Retail traders, fac­ing higher mort­gage rates and loan costs in Japan, likely liq­ui­dated their most volatile, liq­uid as­set first to raise cash. The sell­ing was ex­ac­er­bated by the loom­ing tax re­form in Japan. While the pro­posal to move to a flat 20% tax rate is bull­ish in the long term, the im­me­di­ate pres­sure of ris­ing fund­ing costs forced traders to sell be­fore the tax cut could be re­al­ized. By January 31, mas­sive out­flows from Bitcoin ETFs ($528 mil­lion) co­in­cided with the broader mar­ket crash, con­firm­ing that crypto was be­ing used as a source of liq­uid­ity to cover losses else­where.

Consider the “painful ~3% dump” in the Nasdaq and Microsoft’s stag­ger­ing 15% drop. On January 29, 2026, Microsoft re­ported earn­ings. Despite beat­ing rev­enue es­ti­mates ($81.27 bil­lion vs. $80.28 bil­lion), the stock plum­meted ~11-15% in­tra­day.

The street blamed con­cerns over “AI CapEx”, the idea that Microsoft was spend­ing bil­lions on data cen­ters with slow re­turn on in­vest­ment. However, a 15% drop in a $3 tril­lion com­pany on a “good” earn­ings beat is rarely fun­da­men­tal; it is me­chan­i­cal. Microsoft is a quin­tes­sen­tial “momentum” stock, heav­ily held by for­eign in­sti­tu­tional in­vestors, in­clud­ing Japanese pen­sion funds. When the Yen strength­ens, the value of these USD-denominated as­sets falls in JPY terms.

If a Japanese in­surer holds Microsoft un­hedged, a falling USD/JPY ex­change rate hurts their bal­ance sheet. If they hold it hedged

(rolling short USD po­si­tions), the ris­ing U. S. rates (driven by the Warsh nom­i­na­tion) make the hedge pro­hib­i­tively ex­pen­sive. The January 29 drop was likely ex­ac­er­bated by a “stop-loss” cas­cade from Tokyo desks. As the price broke key tech­ni­cal lev­els, al­go­rithms pro­grammed to pro­tect Yen-denominated re­turns in­dis­crim­i­nately sold the most liq­uid blocks. Microsoft, be­ing one of the most liq­uid stocks in the world, be­came the ATM for the rest of the port­fo­lio.

The most com­pelling ev­i­dence of a forced liq­ui­da­tion event is the be­hav­ior of Gold and Silver on January 31, 2026. Gold fell ~11-12% and Silver crashed ~31-36% in a sin­gle ses­sion. Historically, Gold acts as a safe haven dur­ing eq­uity mar­ket tur­moil. If the Nasdaq is crash­ing due to “Greenland” fears, Gold should rally. Instead, it crashed.

This anom­aly can be ex­plained by two fac­tors:

The Warsh Effect: As dis­cussed, Warsh’s nom­i­na­tion strength­ened the USD and un­der­mined the the­sis for hold­ing anti-fiat as­sets.

Margin Call Dynamics: Snippets re­veal that CME Group and the Shanghai Gold Exchange raised mar­gin re­quire­ments on gold and sil­ver fu­tures days be­fore the crash. When Japanese traders faced losses on their Microsoft longs and their Yen shorts, they needed cash im­me­di­ately. They could­n’t sell illiq­uid bonds quickly enough, so they sold their “winners.” Gold had ral­lied to ~$5,400/oz prior to the crash. Traders liq­ui­dated their prof­itable Gold po­si­tions to pay for the mar­gin calls on their los­ing Tech and Yen po­si­tions.

Cross-Asset Correlations (Week Ending Jan 31, 2026)

Figure 2: Cross-asset cor­re­la­tions, Jan 15–Jan 31,

2026. Note the spike in cor­re­la­tion be­tween Gold, Bitcoin, and

Nasdaq 100 on Jan 31, in­di­cat­ing a sys­temic “sell-everything” mar­gin

call.

Data sources:

Alex Lexington,

Finance Magnates,

Morningstar,

Investing.com,

Seeking Alpha

This cor­re­la­tion break­down is vi­su­al­ized in Figure 2, where the cor­re­la­tion be­tween Gold and the Nasdaq 100 spikes to nearly 1.0 dur­ing the crash week, a sta­tis­ti­cal anom­aly that only oc­curs dur­ing se­vere liq­uid­ity events.

The “Yen Whale” hy­poth­e­sis is strongly sup­ported by the data on fu­tures vol­umes and repo mar­ket stress. The “central mys­tery” is not just in the price ac­tion, but in the un­seen flows of the de­riv­a­tives mar­ket.

About a week ago, some whale kicked off an as­tro­nom­i­cally large mar­ket or­der for a /6J long when it hit re­cent lows. /6J (CME Yen Futures) hit a low of ~0.00647 (approximately 154.50 USD/JPY) in late January. This level has his­tor­i­cally been a “line in the sand” for the Japanese Ministry of Finance (MOF).

Figure 4: The whale event that kicked off

the Japanese Yen un­wind. Note the mas­sive spike as /6J hit re­cent

lows, ral­ly­ing in­vestors world­wide to go long on yen

fu­tures.

CME re­ported record vol­umes in FX and Interest Rate prod­ucts for January 2026. The ag­gres­sive buy­ing off the lows sug­gests a mas­sive repa­tri­a­tion flow. Who is the Whale? Two the­o­ries emerge:

The MOF Thesis: The Ministry of Finance has a his­tory of stealth in­ter­ven­tion. Buying /6J (Long Yen) is func­tion­ally equiv­a­lent to sell­ing USD re­serves. Buying fu­tures al­lows them to sup­port the cur­rency with­out im­me­di­ately de­plet­ing cash re­serves, squeez­ing spec­u­la­tors who are short.

The Carry Unwind: A mas­sive hedge fund or bank (like Norinchukin) re­al­iz­ing that the “game is up” and clos­ing out short-Yen po­si­tions. The size of the or­der sug­gests an en­tity that needed to move bil­lions, not mil­lions.

The sub­se­quent price ac­tion, a sharp rally fol­lowed by “hammering back down”, rep­re­sents the bat­tle­ground. U. S. macro funds are still try­ing to short the Yen (betting on U.S. eco­nomic ex­cep­tion­al­ism and Warsh’s poli­cies), while Japanese do­mes­tic ac­counts are buy­ing it. The volatil­ity is the re­sult of these tec­tonic plates grind­ing against each other.

The plumb­ing of the U. S. fi­nan­cial sys­tem showed signs of stress that co­in­cided with the Japanese re­treat. The Overnight Reverse Repo fa­cil­ity (ON RRP) saw a year-end spike to $106 bil­lion but has since drained.

Japanese banks are typ­i­cally huge par­tic­i­pants in the U. S. repo mar­ket to fund their dol­lar as­sets. As Norinchukin and oth­ers re­treat (repatriating funds to Japan), liq­uid­ity in the U.S. repo mar­ket be­comes thin­ner. The “air pocket” in Microsoft and Gold prices was likely ex­ac­er­bated by a lack of mar­ket maker depth in the repo-funded de­riv­a­tives mar­ket. When mar­ket mak­ers can­not ac­cess cheap repo fund­ing, they widen spreads and re­duce liq­uid­ity pro­vi­sion, lead­ing to “gaps” in price ac­tion dur­ing sell-offs.

There have been sig­nif­i­cant moves in other cur­rency fu­tures as well: /6A in­creased 87 ba­sis points, /6L rose 19 ba­sis points, and /6S rose 18 ba­sis points.

/6A (Australian Dollar): The 87 ba­sis point rise in the Aussie Dollar is no­table. AUD is of­ten a proxy for Chinese growth and global risk sen­ti­ment. A rise here, amidst a tech crash, sug­gests a ro­ta­tion out of U. S. as­sets and into com­modi­ties or Asia-Pacific cur­ren­cies, fur­ther sup­port­ing the “Sell America” the­sis trig­gered by the Greenland tar­iff threats.

/6L (Brazilian Real) and /6S (Swiss Franc): The rise in the Swiss Franc (a clas­sic safe haven) aligns with the risk-off sen­ti­ment. The move in the Brazilian Real sug­gests that emerg­ing mar­kets are also see­ing volatile flows as the dol­lar sta­bi­lizes.

Why was the VIX at 16 de­spite the chaos? The VIX mea­sures im­plied volatil­ity of S&P 500 op­tions. Its rel­a­tively low level (16) com­pared to the vi­o­lence in in­di­vid­ual names (MSFT -15%, Gold -11%) in­di­cates that the crash is a de-lever­ag­ing event, not a panic event.

In a panic, in­vestors buy Puts on the in­dex to pro­tect them­selves, spik­ing the VIX. In a de-lever­ag­ing event, in­vestors sim­ply sell the un­der­ly­ing as­sets (stocks, gold, crypto) to raise cash. They are not hedg­ing; they are ex­it­ing. This ex­plains why the VIX re­mained sub­dued while prices col­lapsed, the sell­ing was or­derly, al­go­rith­mic, and re­lent­less, rather than emo­tional and pan­icked.

Skepticism about the “Greenland War” is well-founded. While the diplo­matic row was real, its util­ity as a fi­nan­cial

nar­ra­tive was far greater than its geopo­lit­i­cal re­al­ity.

President Trump’s threat of mil­i­tary force was re­tracted on January 21 at Davos. This “de-escalation” should the­o­ret­i­cally have calmed mar­kets. Instead, the volatil­ity wors­ened into month-end. This con­firms that the real prob­lem was­n’t Greenland; it was the re-pric­ing of the Yen.

The fi­nan­cial me­dia loves a sim­ple cause-and-ef­fect nar­ra­tive. “Stocks down be­cause of War” is easy to di­gest. “Stocks down be­cause the cross-cur­rency ba­sis swap spread widened due to BOJ min­utes” is not. The “Greenland” nar­ra­tive pro­vided the per­fect cover for so­phis­ti­cated ac­tors to liq­ui­date po­si­tions in Gold and Tech un­der the guise of “war jit­ters.” This al­lowed them to exit with­out spark­ing a broader panic about liq­uid­ity in the bank­ing sys­tem. The fo­cus on the Arctic masked the struc­tural rot in the lever­age com­plex.

The ev­i­dence sug­gests a covert, struc­tural un­wind­ing of the Yen carry trade is the pri­mary dri­ver of the January 2026 mar­ket chaos.

The in­ter­con­nect­ed­ness of these events is un­de­ni­able. The BOJ’s rate hike in December 2025 and the sub­se­quent hawk­ish sig­nal­ing from the Takaichi ad­min­is­tra­tion fun­da­men­tally al­tered the cost of cap­i­tal for the world’s largest carry trade. The “Greenland Crisis” acted as the ini­tial volatil­ity trig­ger, forc­ing a re­duc­tion in gross ex­po­sure. The nom­i­na­tion of Kevin Warsh acted as the fi­nal cat­a­lyst, shat­ter­ing the “Debasement Trade” and forc­ing a liq­ui­da­tion of pre­cious met­als and crypto to cover mar­gin calls on Yen-funded po­si­tions.

Here are some key take­aways:

The “Free Money” Era is Over: BOJ poli­cies have fun­da­men­tally al­tered the global cost of cap­i­tal. The flow of liq­uid­ity from Tokyo to New York has re­versed.

Geopolitics as Catalyst: “Greenland” may have been the spark, but the Yen lever­age was the pow­der keg. The tar­iff threats dis­rupted the “Atlantic Trade” nar­ra­tive, forc­ing a repa­tri­a­tion of cap­i­tal.

Liquidity Event: The syn­chro­nized crash of Gold, Crypto, and Tech con­firms a sys­temic de-lever­ag­ing. The “Whale” or­ders in Yen fu­tures and the break­down of cor­re­la­tions are the smok­ing guns of a mar­gin-dri­ven event.

With the Japanese elec­tion on February 8 and U. S. tar­iffs loom­ing, the “hammering” of the Yen is likely tem­po­rary. The struc­tural trend is now to­ward repa­tri­a­tion. This im­plies lower U.S. as­set prices,

higher U.S. yields, and a stronger Yen over the medium term. The “mystery” of the low VIX is ex­plained by the me­chan­i­cal na­ture of the un­wind, a con­trolled de­mo­li­tion of lever­age rather than a chaotic panic.

This won’t just be the big one. This could be the last one. If you’ve been prepar­ing your whole life, know­ing that some­thing’s com­ing, then this could be the thing you’ve been prepar­ing for. One fi­nal op­por­tu­nity to get the guys who did this.

Longing the Yen is com­monly re­ferred to as “The Widowmaker Trade” on Wall Street, be­cause you have tril­lions of dol­lars of mo­nop­oly money work­ing against you. The carry traders have com­pro­mised every level of our gov­ern­ment. Their great­est vul­ner­a­bil­ity is the Yen ris­ing in value. They will do any­thing to de­fend their po­si­tions, even if that means bring­ing America’s econ­omy down with them. Since re­cent events have made it ob­vi­ous they’re go­ing to lose, we might as well fight them. Most of us prob­a­bly won’t make it out of this fight. But if we at least try, then there’s a chance we might pros­per when it’s over.

The IV on OTM CME

/6J fu­tures calls is 11% which is as­ton­ish­ingly low. The same is true for calls on the

FXY

ETF. Call op­tions have de­fined risk. The more Yen we con­trol, the more its value goes up, and the more crooks on Wall Street get liq­ui­dated. The worst that can hap­pen is you lose your mo­nop­oly money, but that’s been hap­pen­ing any­way. Since carry traders own 10% of all U. S. trea­suries, when they get liq­ui­dated they’ll have to sell a lot of trea­sury bonds, which means that

CME

/UB fu­tures and the TLT

ETF will fall.

This blog is brought to you by var­i­ous rad­i­cals, mal­con­tents, and peo­ple who think the sys­tem is rigged. We’re not af­fil­i­ated with any or­ga­ni­za­tion. Nothing here con­sti­tutes fi­nan­cial ad­vice. Occupy Wall Street is not your fi­nan­cial ad­vi­sor or your lawyer. We’re re­tail in­vestors like you. Do your own re­search. Past per­for­mance does not guar­an­tee fu­ture re­sults. We are the 99 per­cent. The only so­lu­tion is world rev­o­lu­tion. Wall Street’s time has fi­nally come.

SaaS is the most prof­itable busi­ness model on Earth. It’s easy to un­der­stand why: build once, sell the same thing again ad in­fini­tum, and don’t suf­fer any mar­ginal costs on more sales.

I have been writ­ing soft­ware for more than half my life. In the last year it­self, I’ve talked to hun­dreds of founders and op­er­a­tors in SF, from pre­seed to Series E com­pa­nies.

AI is bring­ing an ex­is­ten­tial threat to a lot of B2B SaaS ex­ec­u­tives: How to keep ask­ing cus­tomers for re­newal, when every cus­tomer feels they can get some­thing bet­ter built with vibe-coded AI prod­ucts?

And the mar­ket is pric­ing it in. Morgan Stanley’s SaaS bas­ket has lagged the Nasdaq by 40 points since December. HubSpot and Klaviyo are down ~30%. Analysts are writ­ing notes ti­tled “No Reasons to Own” soft­ware stocks.

The new prob­lem for B2B SaaS is that with AI, cus­tomers can get some­thing work­ing with vibe cod­ing. There are tens of vibe cod­ing “internal tool” ser­vices that promise to con­nect to every in­te­gra­tion in the world to pump out CRUD and work­flow apps.

Whatever they build sim­ply works. It takes some wran­gling to get there (one Series C VP listed eleven dif­fer­ent vibe cod­ing tools they’ve tried and the pros and cons be­tween each on a phone call once), but pro­duc­tiv­ity gains are im­me­di­ate.

And vibe cod­ing is fun. You feel like a mad wiz­ard us­ing the right in­can­ta­tion to get this mag­i­cal new sil­i­con in­tel­li­gence to do ex­actly what you want.

What they don’t know, though, is that a poorly ar­chi­tected sys­tem will fail, even­tu­ally. As every se­nior pro­gram­mer (eventually) un­der­stands, our job is com­plex be­cause we have to un­der­stand the re­la­tion­ships in the real world, the processes in­volved, and the work­flows needed, and rep­re­sent­ing it in a ro­bust way to cre­ate a sta­ble sys­tem. AI can’t do that.

Non-programmers don’t know any of this nu­ance. One Series E CEO told me that they’re re-eval­u­at­ing the quar­terly re­newal of their en­gi­neer­ing pro­duc­tiv­ity soft­ware be­cause they along with an en­gi­neer reim­ple­mented some­thing us­ing Github and Notion APIs. They were pay­ing $30,000 to a pop­u­lar tool and they were not go­ing to re­new any­more.

If cus­tomers feel like they aren’t be­ing served ex­actly like they want to, they are more likely to churn. The rea­son be­hind all this is that cus­tomers are de­mand­ing more from their B2B ven­dors, be­cause they know what’s pos­si­ble.

Previously, you would change your com­pany to fit what your ERP and pay them hun­dreds of thou­sands of dol­lars. Now, every­one can see that agen­tic cod­ing makes an un­prece­dented level of flex­i­bil­ity pos­si­ble. And cus­tomers are de­mand­ing that flex­i­bil­ity, and if they don’t get it, they’ll leave.

This week it­self I was on a phone call with a Series B AE talk­ing about how they’re po­ten­tially los­ing an $X00,000 ac­count just be­cause the cus­tomer can’t use a spe­cific fail­ure re­port­ing work­flow in the SaaS. They’re now work­ing with me to build what the cus­tomer needs and re­tain them.

If the en­tire com­pa­ny’s work­flows op­er­ates on your plat­form, i.e. you’re a line-of-busi­ness SaaS, you are in­te­grated into their ex­ist­ing team al­ready. They know your UI and rely on you on the day to day.

For ex­am­ple, to cre­ate a data vi­su­al­iza­tion I won’t seek any SaaS. I’ll just code one my­self us­ing many of the pop­u­lar vibe cod­ing tools (my team ac­tu­ally did that and it’s vastly more flex­i­ble than what we’d get off-the-shelf).

Being a “System of Record” means you’re em­bed­ded so deeply that there’s no choice but to win. My pre­dic­tion is that we’ll see more SaaS com­pa­nies go from the ap­pli­ca­tion layer to of­fer­ing their ro­bust SoR as their pri­mary sell­ing point.

This is where vibe-coded apps silently fail — and where es­tab­lished SaaS plat­forms earn their keep.

When a non-tech­ni­cal team vibe-codes an in­ter­nal tool, they’re not think­ing about en­vi­ron­ment keys, XSS vul­ner­a­bil­i­ties or API keys hard­coded in client-side JavaScript. They’re not im­ple­ment­ing rate lim­it­ing, au­dit logs, or proper ses­sion man­age­ment. They’re def­i­nitely not think­ing about SOC 2 com­pli­ance, GDPR data res­i­dency re­quire­ments, or HIPAA au­dit trails.

I’ve seen it first­hand: a fi­nance team built a “quick” ex­pense ap­proval tool that stored un­en­crypted re­ports in a pub­lic S3 bucket. A sales ops team cre­ated a com­mis­sion cal­cu­la­tor that any­one with the URL could ac­cess — no auth re­quired. These aren’t edge cases. They’re the norm when soft­ware is built with­out se­cu­rity as a foun­da­tional con­cern.

Enterprise SaaS plat­forms have spent years (and mil­lions) solv­ing these prob­lems: role-based ac­cess con­trol, en­cryp­tion at rest and in tran­sit, pen­e­tra­tion test­ing, com­pli­ance cer­ti­fi­ca­tions, in­ci­dent re­sponse pro­ce­dures. Your cus­tomers may not con­sciously value this — un­til some­thing breaks.

The chal­lenge is that se­cu­rity is in­vis­i­ble when it works. You need to com­mu­ni­cate this value proac­tively: re­mind cus­tomers that the “simple” tool they could vibe-code them­selves would re­quire them to also han­dle auth, per­mis­sions, back­ups, up­time, and com­pli­ance.

The times of ask­ing cus­tomers to change how they work are gone. Now, SaaS ven­dors that dif­fer­en­ti­ate by be­ing ul­tra cus­tomiz­able win the hearts of cus­tomers.

How? It’s the most pow­er­ful se­cret to in­crease us­age. We’ve all heard the clas­sic SaaS prob­lem where the soft­ware is sold at the be­gin­ning of the year, but no one ac­tu­ally ends up us­ing it be­cause of how in­flex­i­ble it is and the amount of train­ing needed.

And if a SaaS is un­der­uti­lized, it gets no­ticed. And that leads to churn.

This is the case with one of my cus­tomers, they have a com­plex SaaS for main­te­nance op­er­a­tions. But turns out, this was not be­ing used at the tech­ni­cian level be­cause they found the UI too com­plex.

How I’m solv­ing this is es­sen­tially a white­la­belled vibe-cod­ing plat­form with in-built dis­tri­b­u­tion and se­cure de­ploy­ments. When they heard of my so­lu­tion they were im­me­di­ately on­board. Their cus­tomer suc­cess teams quickly coded a very spe­cific mo­bile we­bapp for the tech­ni­cians to use and de­ployed it in a few days.

Now, the IC tech­ni­cian is ex­posed to just those parts of the SaaS that they care about i.e. cre­at­ing main­te­nance work or­ders. The ex­ec­u­tives get what they want too, vibe cod­ing cus­tom re­ports ex­actly the way they want vs go­ing through com­pli­cated BI con­fig. They are able to build ex­actly what they want and feel like dig­i­tal gods while do­ing it.

Usage for that ac­count was un­der 35%, and is now over 70%. They are now work­ing closely with me to vibe code new “micro-apps” that work ac­cord­ing to all of their cus­tomer work­flows. And the best part? This is all on top of their ex­ist­ing SaaS which works as a sys­tem of record and han­dles se­cu­rity, au­then­ti­ca­tion, and sup­ports lock-in by be­ing a data and a UI moat.

This is ex­actly what I’m build­ing: a way for SaaS com­pa­nies to let their end-users vibe code on top of their plat­form (More on that be­low). My cus­tomers tell me it’s the best thing they’ve done for re­ten­tion, en­gage­ment, and ex­pan­sion in 2026 — be­cause when your users are build­ing on your plat­form, they’re not eval­u­at­ing your com­peti­tors.

Here’s what I’ve re­al­ized af­ter hun­dreds of con­ver­sa­tions with founders and op­er­a­tors: AI is­n’t killing B2B SaaS. It’s killing B2B SaaS that re­fuses to evolve.

The SaaS model was built on a sim­ple premise: we build it once, you pay for­ever. That worked when build­ing soft­ware was hard. But now your cus­tomers have tasted what’s pos­si­ble. They’ve seen their fi­nance team whip up a cus­tom dash­board in an af­ter­noon. They’ve watched a non-tech­ni­cal PM build an in­ter­nal tool that ac­tu­ally fits their work­flow.

You can’t un­see that. You can’t go back to pay­ing $X0,000/year for soft­ware that al­most does what you need.

The sur­vivors won’t be the SaaS com­pa­nies with the best fea­tures. They’ll be the ones who be­come plat­forms — who let cus­tomers build on top of them in­stead of in­stead of them. When I showed a well-known VC what I was build­ing to help SaaS com­pa­nies do ex­actly this, he said: “This is the fu­ture of mar­ket­places and soft­ware com­pa­nies.”

Maybe. Or maybe this is just an­other cy­cle and tra­di­tional SaaS will adapt like it al­ways has. But I know this: the com­pa­nies I’m talk­ing to aren’t wait­ing around to find out. They’re al­ready re­build­ing their re­la­tion­ship with cus­tomers from “use our prod­uct” to “build on our plat­form.”

The ques­tion is­n’t whether AI will eat your SaaS.

It’s whether you’ll be the one hold­ing the fork.

I’m solv­ing ex­actly this prob­lem with a white­la­belled AI plat­form for B2B SaaS com­pa­nies, so your users can vibe code cus­tomized work­flows on top of their ex­ist­ing sys­tem of record.

My cus­tomers tell me this is the best way to sup­port re­ten­tion, en­gage­ment, and ex­pan­sion in 2026. If this sounds in­ter­est­ing to you or some­one you know, I can reach out with a cus­tom demo or you can learn more about Giga Catalyst.

Skip to main con­tentHow Jeff Bezos Brought Down the Washington PostThe Amazon founder bought the pa­per to save it. Instead, with a mass lay­off, he’s forced it into se­vere de­cline. On September 4, 2013, the Amazon founder Jeff Bezos held his first meet­ing with the staff of the Washington Post, the news­pa­per he had agreed to pur­chase a month ear­lier from the Graham fam­ily, for two hun­dred and fifty mil­lion dol­lars. It had been a long and un­set­tling stretch for the pa­per’s staff. We—I was a deputy ed­i­tor of the ed­i­to­r­ial page at the time—had suf­fered through years of re­trench­ment. We trusted that Don Graham would place us in ca­pa­ble hands, but we did not know this new owner, and he did not know or love our busi­ness in the way that the Graham fam­ily had. Bezos’s words at that meet­ing, about “a new golden era for the Washington Post,” were re­as­sur­ing. Bob Woodward asked why he had pur­chased the pa­per, and Bezos was clear about the com­mit­ment he was pre­pared to make. “I fi­nally con­cluded that I could pro­vide run­way—fi­nan­cial run­way—be­cause I don’t think you can keep shrink­ing the busi­ness,” he said. “You can be prof­itable and shrink­ing. And that’s a sur­vival strat­egy, but it ul­ti­mately leads to ir­rel­e­vance, at best. And, at worst, it leads to ex­tinc­tion.”To look back on that mo­ment is to won­der: How could it have come to this? The pa­per had some prof­itable years un­der Bezos, sparked by the 2016 elec­tion and the first Trump term. But it be­gan los­ing enor­mous sums: sev­enty-seven mil­lion dol­lars in 2023, an­other hun­dred mil­lion in 2024. The owner who once of­fered run­way was un­will­ing to tol­er­ate losses of that mag­ni­tude. And so, af­ter years of Bezos-fuelled growth, the Post en­dured two pun­ish­ing rounds of vol­un­tary buy­outs, in 2023 and 2025, that re­duced its news­room from more than a thou­sand staffers to un­der eight hun­dred, and cost the Post some of its best writ­ers and ed­i­tors. Then, early Wednesday morn­ing, news­room em­ploy­ees re­ceived an e-mail an­nounc­ing “some sig­nif­i­cant ac­tions.” They were in­structed to stay home and at­tend a “Zoom we­bi­nar at 8:30 a.m.” Everyone knew what was com­ing—mass lay­offs.The scale of the de­mo­li­tion, though, was stag­ger­ing—re­port­edly more than three hun­dred news­room staffers. The an­nounce­ment was left to the ex­ec­u­tive ed­i­tor, Matt Murray, and hu­man-re­la­tions chief Wayne Connell; the news­pa­per’s pub­lisher, Will Lewis, was nowhere to be seen as the grim news was un­veiled. In what Murray termed a “broad strate­gic re­set,” the Post’s sto­ried sports de­part­ment was shut­tered “in its cur­rent form”; sev­eral re­porters will now cover sports as a “cultural and so­ci­etal phe­nom­e­non.” The metro staff, al­ready cut to about forty staffers dur­ing the past five years, has been shrunk to about twelve; the for­eign desks will be re­duced to ap­prox­i­mately twelve lo­ca­tions from more than twenty; Peter Finn, the in­ter­na­tional ed­i­tor, told me that he asked to be laid off. The books sec­tion and the flag­ship pod­cast, “Post Reports,” will end. Shortly af­ter the meet­ing, staffers re­ceived in­di­vid­u­al­ized e-mails let­ting them know whether they would stay or go. Murray said the re­trenched Post would “concentrate on ar­eas that demon­strate au­thor­ity, dis­tinc­tive­ness, and im­pact,” fo­cussing on ar­eas such as pol­i­tics and na­tional se­cu­rity. This strat­egy, a kind of Politico-lite, would be more con­vinc­ing if so many of the most tal­ented play­ers were not al­ready gone.Gra­ham, who has pre­vi­ously been res­olutely silent about changes at the pa­per, posted a mes­sage on Facebook that pulsed with an­guish. “It’s a bad day,” he wrote, adding, “I am sad that so many ex­cel­lent re­porters and ed­i­tors—and old friends—are los­ing their jobs. My first con­cern is for them; I will do any­thing I can to help.” As for him­self, Graham, who once edited the sports sec­tion, said, “I will have to learn a new way to read the pa­per, since I have started with the sports page since the late 1940’s.”What hap­pened to the Bezos of 2013, a self-pro­claimed op­ti­mist who seemed to have ab­sorbed the im­por­tance of the Post in the na­tion’s jour­nal­is­tic ecosys­tem? In 2016, ded­i­cat­ing the pa­per’s new head­quar­ters, he boasted that it had be­come “a lit­tle more swash­buck­ling” and had a “little more swag­ger.” As re­cently as December, 2024, at the New York Times’ DealBook Summit, Bezos ex­pressed his com­mit­ment to nur­tur­ing the pa­per: “The ad­van­tage I bring to the Post is when they need fi­nan­cial re­sources, I’m avail­able. I’m like that. I’m the dot­ing par­ent in that re­gard.” Not long ago, he en­vi­sioned at­tract­ing as many as a hun­dred mil­lion pay­ing sub­scribers to the Post. With these bru­tal cuts, he seems con­tent to let the pa­per limp along, di­min­ished in size and am­bi­tion.“In the be­gin­ning, he was won­der­ful,” Sally Quinn, the vet­eran Post con­trib­u­tor and wife of its leg­endary ex­ec­u­tive ed­i­tor, Ben Bradlee, told me of Bezos. “He was smart and funny and kind and in­ter­ested. He was joy­ful. He was a per­son of in­tegrity and con­science. He re­ally meant it when he said this was a sa­cred trust, to buy the Post. And now I don’t know who this per­son is.”The au­thor David Maraniss was with the Post for forty-eight years. He re­signed as an as­so­ci­ate ed­i­tor in 2024, af­ter Bezos killed the ed­i­to­r­ial page’s planned en­dorse­ment of Kamala Harris. “He bought the Post think­ing that it would give him some grav­i­tas and grace that he could­n’t get just from bil­lions of dol­lars, and then the world changed,” Maraniss said of Bezos. “Now I don’t think he gives us—I don’t think he gives a fly­ing fuck.”I asked Maraniss what cuts of this mag­ni­tude would mean for the in­sti­tu­tion. “I don’t even want to call it the Washington Post,” he said. “I don’t know what it’ll be with­out all of that.”The first sign of im­pend­ing lay­offs came in late January, when the sports staff was in­formed that plans to send writ­ers to Italy to cover the Winter Olympics had been can­celled. (Management later agreed to send a smaller crew.) In the fol­low­ing days, as ru­mors be­gan to spread of se­vere cuts, the pa­per’s re­porters be­gan post­ing mes­sages di­rected at Bezos on X, with the plain­tive hash­tag #SaveThePost. “Our re­porters on the ground drove ex­clu­sive cov­er­age dur­ing piv­otal mo­ments of re­cent his­tory,” the for­eign staff wrote to Bezos. “We have so much left to do.” The lo­cal staff noted that it had al­ready been slashed in half in the past five years. “Watergate,” they wrote, “started as a lo­cal story.”It did not help the staff’s morale that Lewis and his team were hob­nob­bing in Davos, or that Bezos and his wife, Lauren Sánchez, were in Paris for Haute Couture Week. More trou­bling were re­minders that Bezos, who once em­bla­zoned “Democracy Dies in Darkness” on the pa­per’s mast­head, ap­pears to be pur­su­ing a pol­icy of ap­pease­ment to­ward the Trump Administration. During the first Trump term, Bezos stood by the Post even when his stew­ard­ship threat­ened to cost him bil­lions in gov­ern­ment con­tracts. Now Bezos had not said a word about a re­cent F.B.I. raid on the home of the Post fed­eral-gov­ern­ment re­porter Hannah Natanson, in which the agency seized her phones, lap­tops, and other de­vices. As the staff awaited the axe, the President and the First Lady cel­e­brated the pre­mière of “Melania,” a doc­u­men­tary that Amazon had li­censed for forty mil­lion dol­lars and was re­ported to be spend­ing an­other thirty-five mil­lion to pro­mote. The deal was inked af­ter Bezos had din­ner with the Trumps shortly be­fore the Inauguration.Martin Baron, who over­saw cov­er­age at the pa­per that gar­nered eleven Pulitzer Prizes dur­ing his eight years as ex­ec­u­tive ed­i­tor, said in a state­ment, “This ranks among the dark­est days in the his­tory of one of the world’s great­est news or­ga­ni­za­tions. The Washington Post’s am­bi­tions will be sharply di­min­ished, its tal­ented and brave staff will be fur­ther de­pleted, and the pub­lic will be de­nied the ground-level, fact-based re­port­ing in our com­mu­ni­ties and around the world that is needed more than ever.” The news in­dus­try is in “a pe­riod of head-spin­ning change,” Baron told me. But the Post’s prob­lems “were made in­fi­nitely worse by ill-con­ceived de­ci­sions that came from the very top.” He pointed to Bezos’s de­ci­sion to kill the Harris en­dorse­ment—a “gutless or­der” that cost the pa­per more than two hun­dred fifty thou­sand sub­scribers. “Loyal read­ers, livid as they saw owner Jeff Bezos be­tray­ing the val­ues he was sup­posed to up­hold, fled The Post. In truth, they were dri­ven away, by the hun­dreds of thou­sands,” Baron said. “Bezos’s sick­en­ing ef­forts to curry fa­vor with President Trump have left an es­pe­cially ugly stain of their own. This is a case study in near-in­stant, self-in­flicted brand de­struc­tion.”I spent more than forty years at the Post, as a re­porter, an ed­i­tor, an ed­i­to­r­ial writer, and a colum­nist. I re­signed last March, af­ter Bezos an­nounced that the Opinions sec­tion, where I worked, would hence­forth be con­cen­trat­ing on the twin pil­lars of “personal lib­er­ties and free mar­kets.” More alarm­ing, Bezos ad­vised, “Viewpoints op­pos­ing those pil­lars will be left to be pub­lished by oth­ers.” We had been an opin­ion sec­tion re­flect­ing a wide range of views—which Bezos him­self had en­cour­aged. It seemed ob­vi­ous that this change was deeply mis­guided.I had writ­ten a col­umn crit­i­cal of the non-en­dorse­ment de­ci­sion sev­eral months ear­lier. The pa­per pub­lished it with­out any sub­stan­tive changes. But, when I wrote a col­umn dis­agree­ing with the no-dis­sent-al­lowed dic­tum, I was told that Lewis had killed it—it ap­par­ently did­n’t meet the “high bar” for the Post to write about it­self—and de­clined my re­quest to meet. I sub­mit­ted my let­ter of res­ig­na­tion. A new ed­i­to­r­ial-page ed­i­tor went on to shift both un­signed ed­i­to­ri­als and signed opin­ion columns dra­mat­i­cally to the right, to the point that no lib­eral colum­nists re­main. One re­cent ed­i­to­r­ial praised the President’s plan for a new ball­room and ex­cused his unau­tho­rized bull­doz­ing of the East Wing, say­ing that “the blue­prints would have faced death by a thou­sand pa­per­cuts.” Another en­dorsed the move to re­name the Defense Department the Department of War as “a wor­thy blow against gov­ern­ment eu­phemism.” There are some ed­i­to­ri­als crit­i­cal of Trump, but the in­cli­na­tion to fawn­ing praise is un­mis­tak­able. Had I not de­fen­es­trated my­self, I would, no doubt, have been ad­vised to take my buy­out and go.But I am not—at least, I have not been—a Bezos-hater. I am grate­ful for the re­sources, fi­nan­cial and tech­no­log­i­cal, that he de­voted to the pa­per in his early years as owner. The sur­prise of Bezos’s tenure at the Post has been his bad busi­ness de­ci­sions. Fred Ryan, a for­mer chief of staff to Ronald Reagan and found­ing pres­i­dent of Politico, was hired as the pub­lisher and C.E.O. in 2014 and over­saw a pe­riod of spec­tac­u­lar growth. Buoyed by Bezos-funded ex­pan­sion and the pub­lic’s fix­a­tion on the new Trump Administration, the num­ber of dig­i­tal sub­scribers soared from thirty-five thou­sand when he ar­rived to two and a half mil­lion when he left, in the sum­mer of 2023. But Ryan failed to de­velop an ad­e­quate plan for how the news­pa­per would thrive in a post-Trump en­vi­ron­ment. As traf­fic and rev­enue plunged, Ryan found him­self in­creas­ingly at odds with the news­room. He held a year-end town-hall meet­ing in 2022 at which he an­nounced that lay­offs were com­ing, and then, to the con­ster­na­tion of the staff, left with­out tak­ing ques­tions. As Clare Malone re­ported for The New Yorker, Woodward be­seeched Bezos to in­ter­cede. The owner made a rare visit to the pa­per in January, 2023, for meet­ings with key staffers, tak­ing notes on a le­gal pad as they poured out their anx­i­ety.Ryan left that sum­mer, but Lewis, his even­tual re­place­ment, ac­com­plished the feat of mak­ing the news­room nos­tal­gic for Ryan. A decade ear­lier, Lewis, then a se­nior ex­ec­u­tive in Rupert Murdoch’s British-tabloid em­pire, had played a piv­otal role in deal­ing with the fall­out from the phone-hack­ing scan­dal at some of Murdoch’s pa­pers. Lewis had said that he was act­ing to pro­tect “journalistic in­tegrity,” when the Post ques­tioned him about his ac­tions dur­ing that time, but in 2024 ques­tions arose, fu­elled by a civil law­suit brought against the pa­pers, about whether Lewis had sought to con­ceal ev­i­dence, in­clud­ing by car­ry­ing out a plan to delete mil­lions of e-mails. (Lewis has said the al­le­ga­tions against him were “completely un­true.”) At the Post, Lewis clashed with ex­ec­u­tive ed­i­tor Sally Buzbee over cov­er­age of the story, re­port­edly in­sist­ing that it was not news­wor­thy. Shortly af­ter­ward, Lewis an­nounced Buzbee’s de­par­ture, and his plan to re­place her with Robert Winnett, a for­mer col­league of his from London’s Daily Telegraph and Sunday Times. The Post and the Times both re­ported on how Lewis and Winnett had used fraud­u­lently ob­tained ma­te­r­ial as the ba­sis for ar­ti­cles. “His am­bi­tion out­ran his ethics,” one of Lewis’s for­mer re­porters told the Times. Winnett ended up with­draw­ing from the po­si­tion, but the episode poi­soned re­la­tions be­tween Lewis and the news­room.The staff, mean­while, be­came in­creas­ingly con­cerned that Lewis was of­fer­ing cor­po­rate word salad in place of a vi­sion to ad­dress the Post’s de­cline. “Fix it, build it, scale it” was his catch­phrase when he ar­rived, in January, 2024. In June of that year came an amor­phous plan for what Lewis called a “third news­room.” (The sec­ond news­room, we were sur­prised to learn, was the Opinions sec­tion.) First, it was to fo­cus on so­cial me­dia and ser­vice jour­nal­ism. Then it was rechris­tened WP Ventures and, ac­cord­ing to a memo to staff, would “focus en­tirely on build­ing per­son­al­ity-dri­ven con­tent and fran­chises around per­son­al­i­ties.” By February, 2025, the sit­u­a­tion had de­te­ri­o­rated to the point that two for­mer top ed­i­tors, Leonard Downie and Robert Kaiser, wrote to Bezos about Lewis. “Replacing him is a cru­cial first step in sav­ing The Washington Post,” they urged in an e-mail. Bezos never re­sponded.Downie, who served as ex­ec­u­tive ed­i­tor from 1991 to 2008, con­trasted the paths of the Times and the Post. During the past decade, the Times trans­formed it­self into a one-stop-shop­ping en­vi­ron­ment that lured read­ers with games such as Spelling Bee, a cook­ing app, and a shop­ping guide. By the end of 2025, it was re­port­ing close to thir­teen mil­lion dig­i­tal sub­scribers and an op­er­at­ing profit of more than a hun­dred and ninety-two mil­lion dol­lars. The Post does not re­lease in­for­ma­tion about its dig­i­tal sub­scribers, but it was re­ported to have two and a half mil­lion dig­i­tal sub­scribers at the time of the non-en­dorse­ment de­ci­sion, in 2024.“One of the big dif­fer­ences to me was that they hired a pub­lisher”—Ryan—“who did­n’t come up with any ideas,” Downie told me. “And then when he left . . . we knew that Bezos was los­ing money, and we were en­cour­aged by the fact that they were look­ing for some­body who could im­prove the busi­ness side of the pa­per and the cir­cu­la­tion side of the pa­per. And then they chose this guy who we hardly ever heard from, who had a check­ered past in British jour­nal­ism.”Writ­ing last month on a pri­vate Listserv for for­mer Post em­ploy­ees, Paul Farhi, who as the me­dia re­porter for the Post cov­ered Bezos’s ac­qui­si­tion of the pa­per, shared his “utter mys­ti­fi­ca­tion and baf­fle­ment” about Bezos’s tol­er­ance of Lewis. “Even as a hands-off boss,” he won­dered, “could Bezos not see what was ob­vi­ous to even ca­sual ob­servers within a few months of Will’s ar­rival—that Will was ill-suited to the Post, that he had alien­ated the news­room, that he had an eth­i­cally sus­pect past, and—most im­por­tant—that none of his big ideas was work­ing or even be­ing im­ple­mented?” (Farhi, who took a buy­out in 2023, gave me per­mis­sion to quote his mes­sage.)Even be­fore these new cuts, a pa­rade of key staffers had left the Post. A beloved man­ag­ing ed­i­tor, Matea Gold, went to the Times. The na­tional ed­i­tor, Philip Rucker, de­camped to CNN, and the po­lit­i­cal re­porter Josh Dawsey to the Wall Street Journal. The Atlantic hired, among oth­ers, three stars of the pa­per’s White House team: Ashley Parker, Michael Scherer, and Toluse Olorunnipa. These are losses that would take years to re­build—if the Post were in a re­build­ing mode. The Post, Woodward said, “lives and is do­ing an ex­tra­or­di­nary re­port­ing job on the po­lit­i­cal cri­sis that is Donald Trump”—including its scoop on the sec­ond strike to kill sur­vivors of an at­tack on an al­leged Venezuelan drug boat. But the print edi­tion is a shadow of its for­mer self, with metro, style, and sports melded into an ane­mic sec­ond sec­tion; daily print cir­cu­la­tion is now be­low one hun­dred thou­sand. More press­ingly, it’s un­clear whether a news­room so stripped of re­sources can sus­tain the qual­ity of its work.The sports colum­nist Sally Jenkins, who left the Post in August, 2025, as part of the sec­ond wave of buy­outs, has been more sup­port­ive of man­age­ment than many other Post vet­er­ans. So it was strik­ing that, when we spoke re­cently, she was both pas­sion­ate about the work of her news­room col­leagues and un­spar­ing about how the busi­ness side had failed them. “When you whack at these sec­tions, you’re whack­ing at the roots of the tree,” she told me. “We train great jour­nal­ists in every sec­tion of the pa­per, and we train them to cover every sub­ject on the globe. And when you whack whole sec­tions of peo­ple away, you are re­ally, re­ally in dan­ger of killing the whole tree.” When I asked how she felt about the losses, Jenkins said, “My heart is cracked in about five dif­fer­ent pieces.”Jenk­ins, who was in California cov­er­ing Super Bowl week for the Atlantic, has spent a ca­reer study­ing what ac­counts for the dif­fer­ence be­tween win­ning teams and los­ing ones. Bezos, she said, had been gen­er­ous with his money and laud­able for never in­ter­fer­ing in the work of the news­room. But, she added, “making money at jour­nal­ism, you have to break rocks with a shovel. You have to love think­ing about jour­nal­ism to the point that it wakes you up at night with an idea, and then you have to be will­ing to try it. And I don’t see a sense that he loves the busi­ness enough to think about it at night. It’s al­most like he’s treated it like Pets.com—an in­ter­est­ing ex­per­i­ment that he’s will­ing to lose some money on un­til he’s not. But the dif­fer­ence with this busi­ness is it’s not Pets.com. It’s not a busi­ness that just dis­ap­pears into the muck of ven­ture cap­i­tal­ism. It’s a busi­ness that is es­sen­tial to the sur­vival of the Republic, for Christ’s sake. So you don’t fuck around with it like that.”As Post staffers and alumni braced for the cuts, I called Kaiser, the for­mer man­ag­ing ed­i­tor, who spent more than half a cen­tury at the pa­per. “Mr. Bezos’s per­sonal sys­tem has failed him in a way I fear he does­n’t grasp,” Kaiser, now eighty-two, told me. “He has no sense of the dam­age that will be done to his rep­u­ta­tion in his­tory if he be­comes seen as the man who de­stroyed the in­sti­tu­tion that Katharine Graham”—the famed pub­lisher who led the pa­per from the six­ties to the nineties—“and Ben Bradlee built.” Kaiser re­called ar­riv­ing at the pa­per’s London bu­reau in 1964. “If I say, ‘I’m Kaiser from the Washington Post’—what’s that? They never heard of it.” A decade later, he was posted in Moscow, as Woodward and Carl Bernstein were break­ing the Watergate story. “Explaining was not nec­es­sary,” Kaiser said. “The Russians, in fact, had a glo­ri­ously ex­ag­ger­ated im­pres­sion of the Washington Post as the king-maker and the king-de­stroyer.”Be­zos, Kaiser con­tin­ued, “knew what the role was, ac­knowl­edged the role—those words ‘doting par­ent’—and then he walked away from it. What the hell?” The dam­age, he pre­dicted, will re­ver­ber­ate be­yond the im­me­di­ate cuts. “What pur­pose does any hon­or­able, at­trac­tive, com­pe­tent jour­nal­ist have for re­main­ing at the Post? None.”At one point, as we talked about the trans­for­ma­tion of the Post, Kaiser stopped him­self. “I’m go­ing to cry,” he said, and paused. “Oh, God, it’s killing me.”Be­zos may be tir­ing of the Post, but he has not seemed in­clined to sell the pa­per. Nor is it clear that would be a bet­ter, or at this point even fea­si­ble, out­come. Newspapers across the coun­try are be­ing bought up by pri­vate-eq­uity firms that are es­sen­tially sell­ing off the valu­able parts. But there is an­other model for Bezos to con­sider: turn­ing the Post into a non­profit, en­dowed by Bezos but op­er­at­ing in­de­pen­dently of him. For Bezos, this would re­duce the role of the Post as a headache and a threat to other, more fa­vored en­deav­ors, such as his rocket com­pany, Blue Origin. For the Post, as­sum­ing the en­dow­ment is suf­fi­cient, it would pro­vide that con­tin­u­ing run­way.There are mod­els for this ap­proach. In Philadelphia, the late ca­ble-tele­vi­sion ty­coon H. F. “Gerry” Lenfest pur­chased the Inquirer, the Daily News, and Philly.com in 2015, and the fol­low­ing year do­nated the pub­li­ca­tions to a char­i­ta­ble trust. “What would the city be with­out the Inquirer and the Daily News?” asked Lenfest, whose con­tri­bu­tion to the en­deavor has been val­ued at al­most a hun­dred and thirty mil­lion dol­lars. In Utah, the in­vestor Paul Huntsman bought the Salt Lake Tribune from the hedge fund Alden Global Capital in 2016; three years later, he trans­formed it into a non­profit, sup­ported in part by tax-de­ductible con­tri­bu­tions from read­ers.Writ­ing in the Columbia Journalism Review in 2024, Steven Waldman sug­gested that Bezos fol­low a sim­i­lar course. “ ‘Nonprofit’ does not mean ‘losing money,’ ” Waldman wrote. “Nonprofit news or­ga­ni­za­tions can sell ads, of­fer sub­scrip­tions, and take do­na­tions. Done well, it is an es­pe­cially strong busi­ness model, be­cause it pro­vides an ex­tra rev­enue stream (philanthropy) and is deeply em­bed­ded in serv­ing the com­mu­nity.” My quib­ble with Waldman’s pitch is that he asked Bezos to ante up a pal­try hun­dred mil­lion. When Bezos pur­chased the Post, his net worth was about twenty-five bil­lion; it is now an es­ti­mated two hun­dred fifty bil­lion. Why not one per cent of that for the Post, enough to sus­tain the pa­per in­def­i­nitely? A pipe dream, I know, but this arrange­ment would make Bezos the sav­ior of the Post, not the man who presided over its demise.In the 1941 movie “Citizen Kane,” Charles Foster Kane, a news­pa­per pub­lisher who, like Bezos, is one of the rich­est men in the world, is con­fronted by his le­gal guardian, Walter Thatcher, about the folly of fund­ing his pa­per. “Honestly, my boy, don’t you think it’s rather un­wise to con­tinue this phil­an­thropic en­ter­prise, this Inquirer that’s cost­ing you a mil­lion dol­lars a year?” Thatcher de­mands. “You’re right, Mr. Thatcher. I did lose a mil­lion dol­lars last year,” Kane replies. “I ex­pect to lose a mil­lion dol­lars this year. I ex­pect to lose a mil­lion dol­lars next year. You know, Mr. Thatcher, at the rate of a mil­lion dol­lars a year, I’ll have to close this place in sixty years.” Update Kane’s out­lays to as­sume losses of a hun­dred mil­lion an­nu­ally, in per­pe­tu­ity. By that math, Bezos would have more than two mil­len­nia be­fore need­ing to turn out the lights. ♦