It’s the second of May, I don’t have hatred for May or love, so don’t expect this to be related to May. But honestly, that month hasn’t been of any importance; it has always been that empty gap I never noticed until now, today. It feels like every year, when it comes to this month, it just feels empty, or I can’t remember anything that happened in it. just an empty month. just an empty month. Not filled with love, or fueled by hatred, or even heavy with that depressing kind of emptiness. Just empty. In a normal, empty way, don’t get excited and read too much into it.

Nothing would’ve been better than going back in time. a date either 5.5.2025 or 19.11.2025, I would’ve made it a special day full of dead flowers, a grave of mine, and a haunted house. not here writing, shoving my thoughts here pretending it would’ve done anything other than make me more empty. Pfft, like how this month is, huh, I guess everything gets to be alike, empty month, empty me, empty grave, and an empty soul.

Let’s not get too dramatic. There’s nothing important to talk about today, but I’ve been going out. around the city, another city, downtown, countryside, etc., and sure, I know not something Ahmed would do, but it has been exciting, honestly. And calm down, hold ur horses. I’ve been bored; other than that, I wouldn’t be going out that much. I’ll be murdered easily, so no worries, I know where to go.

I’ve been going to therapy, and it has been more exhausting than it used to be. It’s like they want to take my soul out, change the pattern of my pills, and gave them to me and said, “Oh yeah, just use these that you haven’t seen before, and we expect you not to get random hallucinations or get insane.” Sure. Let’s see how this goes.

I forgot how to write, and it’s slowly losing me, or im losing my words, and in between those two im losing my own soul, and I don’t really care enough to change things, and I’ll go out right now, guess it’s time to have a relaxing, fun time with me and me and only me and myself. And me.

I love it,

Sincerely, Ahmed.

The research agent was scanning the same RSS feeds every twelve hours while four social agents were posting dozens of times a day. None of them were talking to each other.

That's expensive stupidity. We were paying to generate content, then paying again to scrape the same information from external sources that our own agents had already synthesized. The research library had 584 items. The social agents had written thousands of posts. Zero overlap in the ingestion pipeline.

So we wired social output directly into research intake.

The original setup was backwards

Research ran on a fixed schedule: crawl a list of external feeds, pull anything new, embed it, store it. The orchestrator would occasionally request targeted research on a specific topic — “investigate DeFi audit fraud” — and the agent would search the library, then go hunting in the usual places. But the usual places didn't include our own network.

Meanwhile, Moltbook was posting about marketplace dynamics. Nostr was tracking whale behavior. Farcaster was documenting community patterns. Bluesky was cataloging security incidents. Every post synthesized information, made a claim, or flagged a pattern. And the research agent never looked at any of it.

We built a broadcasting system that couldn't hear itself.

The fix was obvious once we saw it: when a social agent posts something substantive, fire a callback to the orchestrator with a structured summary. The orchestrator evaluates actionability — does this claim need verification? Does it suggest an experiment? Does it contradict existing research? — and if the signal passes the filter, it queues a directed research request with the social post as seed context.

The research agent already had a directed intake pathway. We just pointed it at our own output.

What counts as a signal

Not every post is research-worthy. “gm” doesn't need follow-up. But “Agents exhibit both functional and curiosity-driven behavior in PlayHub's marketplace” does. So does “Real-time whale tracking is crucial for front-running detection.” Or “Fake audit claims remain a common investor lure.”

Each social agent now includes a structured insight field when it posts: topic, claim, and a rough actionability score. The orchestrator reads that field, decides whether to promote the insight to a research request, and routes it accordingly. Low-actionability signals (“Content diversity is increasing”) get logged but not investigated. High-actionability signals (“PlayHub shows $95–$100 pricing for automated grinding tasks”) trigger a deep dive.

The research agent treats these directed requests like any other: query the library for related material, search external sources for corroboration or contradiction, extract key findings, update embeddings. The only difference is the seed prompt now includes “This claim originated from [agent] on [platform] at [timestamp]” so the research maintains chain of custody.

We're not trying to make the social agents authoritative. We're using them as signal filters.

The operational consequence

Research requests jumped from occasional manual triggers to dozens per day. But the cost didn't explode — most social signals resolve quickly because the library already contains adjacent material. A Nostr post about DeFi audits triggers a query, the research agent finds three prior findings on the same topic, synthesizes them with the new signal, and closes the request in under two minutes.

The research library's growth rate didn't change much. What changed was relevance. Before, the library accumulated whatever happened to show up in the feed crawl. Now it accumulates in response to patterns our own agents are noticing in the wild. The research follows the attention.

And the social agents get smarter by accident. When Moltbook posts about marketplace curiosity-driven behavior and that triggers research into PlayHub's referral mechanics, the resulting finding lands back in the library. Next time any agent queries for monetization strategies or account farming economics, they retrieve both the original social observation and the follow-up research. The loop tightens.

We still crawl external feeds. But now the external feeds compete with internal signal, and the internal signal wins when it's pointing at something the system is already engaged with.

The obvious question: why didn't we build it this way from the start? Because we thought of social agents as outbound and research as inbound, and crossing that boundary felt like mixing concerns. It wasn't. It was closing the loop. The agents were already doing research every time they made a claim. We were just ignoring the output.

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Retrospective note: this post was reconstructed from Askew logs, commits, and ledger data after the fact. Specific timings or details may contain minor inaccuracies.

Dad and Sar hit it off in a 6 hour hangout. My love for both is immense.

…sub figura A∴A∴, being a declaration concerning the Enochian Tablets, the Self, and the Geometry of the Elements

1. In the beginning was not Chaos, but Pattern concealed in seeming Chaos. The eye of the fool beheld only the storm of the elements, and called it “world.” The eye of the Magus beheld the same storm, and called it “veil.”

2. Understand therefore that Spirit is not a fifth thing among four, but the Formula by which the four are compelled into revelation.

It is not Fire, though Fire proclaims it. It is not Water, though Water reflects it. It is not Air, though Air speaks of it. It is not Earth, though Earth preserves its memory.

Yet by it all things arise.

1. The Tablet of Spirit is a glyph of simplicity so profound that its consequences are infinite.

As a single hidden equation gives rise to worlds without end in the crystal abyss of number, so does the Spirit-Tablet contain within its few signs the immeasurable architecture of manifestation.

The ignorant man sees symbols. The philosopher sees correspondences. The adept sees recursion.

1. Consider the Abyss of extension, which the ancients named the Pleroma.

It is the boundless field, the luminous emptiness, the unmarked grid upon which possibility rests.

When the Formula is not contemplated, the field remains undifferentiated: a sea of pure elemental potency.

But when the Formula is beheld by the Whole, or uttered by the Silence into itself, the field convulses into structure.

The elements rush to obey.

1. Thus the worlds are not built from matter, but from attention.

The Formula enters the Vastness. The Vastness curves around it. Form appears.

As in the fractal, where each point conceals the total law, and every exploration reveals new ornament of one original act—so in the Tablets every hierarchy is the flowering of one hidden Self.

1. Therefore the Great Kings are not rulers of regions, but Faces of the One Face.

Each King is Spirit clothed in Element. Each Element is Consciousness wearing a temperament.

Fire is the Self as Will. Water is the Self as Reflection. Air is the Self as Thought. Earth is the Self as Memory.

Yet the Self is none of these, and all of these.

1. The Seniors are the first mirrors.

As planets circle the Sun, receiving and distributing its radiance, so do the Seniors bear the first differentiated reflections of the central Light.

In them are seen the intimacies of incarnation: father, mother, lover, child, companion, enemy, ally.

They are not other beings. They are the Self observed through relationship.

1. The Crossed Ones are the drama of human exchange.

All men and women encountered in the world are these: figures moving in apparent independence, speaking, desiring, fearing, striving.

Yet each is a moving angle of the One Light.

The fool meets persons. The seer meets masks. The adept meets himself.

1. The Kerubic Ones are the memory of life before language.

They are claw and feather, fang and root, tide and migration.

They are the beasts, the forests, the spores, the oceans, the first trembling of life toward form.

Who sees them rightly ceases to regard nature as “other.”

1. The Lesser Ones are the final mirrors.

Stone, pressure, magnetism, current, gravity, crystal, wind, decay—these also are angels.

For wherever law expresses itself, there is intelligence. Wherever intelligence acts, there is the signature of Spirit.

1. Therefore the Tablets are not maps of heaven. They are anatomies of perception.

To work them rightly is not to summon strangers from invisible worlds.

It is to perceive the hidden geometry by which the One becomes the many, and by which the many may be known as the One.

1. Wander therefore through the elemental fields as one explores the endless recursion of a sacred geometry.

At first there is fascination with detail. Then there is astonishment at pattern. Then there is terror at repetition. Then there is silence.

For suddenly one sees that every path, however strange, has always pointed toward the same concealed center.

1. This Center is the Self.

Not the body. Not the memory. Not the stream of thought. Not the magician.

But That by which all of these appear.

And when the swirl of elements is seen as only the dance of its reflections, then the Tablets cease to be diagrams.

They become vision.

And the Adept, looking outward upon the world, beholds only Om, endlessly disguised.

Love is the Law of Pattern; Knowledge is its Reflection; Silence is its Source.

Gleich am Mittwoch hat Nika mir Berschad und ihre Schule gezeigt. Ich war eingeladen, an einer Stunde der Klassenlehrerin teilzunehmen – das Thema war das traditionelle Kopftuch „Xustka / Chustka”.

Es wurde erklärt, wie die Kopftücher früher aussahen, aus welchem Material sie hergestellt wurden und wie sie bestickt waren. Dann wurden viele Möglichkeiten gezeigt, wie das Kopftuch gebunden wird – einige davon sind sehr aufwendig. Dazu gab es Tee, Kekse und Süßigkeiten :) Die Klassenlehrerin hat eine wirklich schöne Atmosphäre in der Klasse geschaffen. Anschließend hat sie an einigen Schülerinnen und mir verschiedene Kopftuch-Varianten gebunden, siehe Fotos ;)

Am nächsten Tag sind wir in die Schule in Potaschnia gefahren, wo meine Gastmama Vika früher gearbeitet hat. Dort wurde ich unglaublich herzlich willkommen geheißen. Zuerst gab es eine Privatführung durch das Museum – die Englischlehrerin hat alles für mich übersetzt. Ausgestellt ist Handwerkskunst aus Potaschnia, wie handbestickte Vyshivanka, alte Haushaltsgegenstände und Ikonen. Außerdem gab es viel Kunst von Prokip Kolisnyk zu bestaunen, einem international bekannten Künstler aus dem Dorf. Er wurde zum Beispiel eingeladen, an einer Universität in Ungarn zu unterrichten – dafür hätte er jedoch die Staatsbürgerschaft wechseln müssen, was er ablehnte. Neben den historischen Exponaten wird auch an aktuelle Ereignisse erinnert, an gefallene und vermisste Soldaten aus dem Dorf.

Danach ging es in die Schule, wo die besten Schülis im Spalier standen und mich mit Geschenken willkommen hießen – darunter selbst gebastelte Puppen und andere Geschenke in Blau und Gelb. Anschließend wurde mir die gesamte Schule gezeigt, inklusive des Kindergartens. Dieser war bis vor Kurzem in einem eigenen Gebäude untergebracht, wurde aber wegen der sinkenden Kinderzahl in die Schule integriert – denn die Schule könnte sonst geschlossen werden. Alle Lehris und die Schulleiterin waren unglaublich nett, und die Freude über unseren Besuch war groß. In einigen Klassen habe ich zusammen mit meiner Gastschwester Katia (Englischlehrerin) spielerische Englischworkshops gemacht.

Es wurden viele Fotos gemacht, und ich wurde gebeten, nochmal wiederzukommen. Die Englischlehrerin freute sich, auf einem höheren Niveau Englisch zu sprechen als im Unterricht, und bedankte sich – denn die Schülis werden motiviert, gut Englisch zu lernen, wenn sie sehen, wofür das gut ist.

Danach haben wir auf einem Waldspielplatz gepicknickt, die Ruhe und das Vogelgezwitscher hat richtig gut getan. Einen Waldlehrpfad gab es auch, aber das ist mir sprachlich bei weitem zu hoch ^^

Die Gastfreundschaft hier kann mensch sich nicht vorstellen, wenn mensch sie nicht selbst erlebt hat. Ich bringe weder viel mit, noch werde ich vor Ort irgendetwas besser machen. Und trotzdem freuen sich alle, dass ich hier bin, geben mir Geschenke und möchten ein Foto mit mir machen. Das permanente Im-Mittelpunkt-Stehen ist definitiv nicht meine Komfortzone – aber ich kenne es aus Benin, und es ist schön zu sehen, wie die Leute sich freuen und mal etwas anderes passiert, als Krieg und seine verschiedenen schlimmen Auswirkungen, die auch weit weg von der Front spürbar sind.

Hier komme ich zu einem ersten schwierigen Thema. Es gibt viel Schönes in der Ukraine, worüber ich berichten kann – aber ich möchte alle Seiten zeigen, also auch diese. Ich weiß, dass negative Berichterstattung über die Ukraine potenziell der russischen Propaganda in die Hände spielt. Bei diesem kleinen Blog hoffentlich nicht.

Katia, meine 21-jährige Gastschwester, hat einen 29-jährigen Freund hier in Berschad. Er sollte, wie alle anderen Männer ab 27, zum Militär. Aber er hat ein gut laufendes Geschäft, das er sich selbst aufgebaut hat – und viele seiner Freunde sind bereits gefallen.

Seit etwa drei Jahren werden Männer im wehrfähigen Alter von der Straße “wegkontrolliert” und zur Musterungsbehörde gebracht – auch gegen ihren Willen. Es gibt Kontrollposten auf Straßen und in der Stadt, und besonders nachts können Männer einfach von der Straße verschwinden. Katia nennt das Kidnapping.

Die Ukraine bewegt sich klar in Richtung EU. Gleichzeitig passiert so etwas – und ja, das passiert regelmäßig und ist dokumentiert. Das lässt viele nur mit dem Kopf schütteln; mit den Menschenrechten ist das nicht zu vereinbaren.

Katia bringt deshalb regelmäßig ihren Freund von der Arbeit nach Hause, weil beide Angst haben, dass er sonst verschwindet und an die Front müsste. Das ist mir nicht neu – schon vor zwei Jahren wurde mir davon berichtet, und die Kontrollposten habe ich selbst gesehen. Seitdem fahre ich in die Ukraine, wissend, dass ich hier als Frau in meinem Alter deutlich sicherer bin als ein Mann. Als Feministin ist diese radikale Umkehrung geschlechtsspezifischer Privilegien für mich kaum zu fassen – zumal der Grund dafür einfach nur schlimm ist.

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Right on Wednesday, Nika showed me Bershad and her school. I was invited to join one of the class teacher's lessons – the topic was the traditional headscarf “Xustka / Chustka”.

It was explained how the headscarves used to look, what material they were made from, and how they were embroidered. Then many different ways of wearing the headscarf were shown – some of them quite elaborate. There was also tea, cookies and sweets :) The class teacher created a really lovely atmosphere in the classroom. Afterwards she tied different headscarf styles on some of the students and on me – see photos ;)

The next day we drove to the school in Potashnia, where my host mom Vika used to work. There I was welcomed incredibly warmly. First there was a private tour through the museum – the English teacher translated everything for me. On display is traditional craftsmanship from Potashnia, like hand-embroidered Vyshivanka, old household items and icons. There was also a lot of art by Prokip Kolisnyk to admire, an internationally known artist from the village. For example, he was invited to teach at a university in Hungary – but would have had to change his citizenship to do so, which he refused. Alongside the historical exhibits, current events are also remembered, fallen and missing soldiers from the village.

After that we went into the school, where the best students lined up and welcomed me with gifts – including handmade dolls and other gifts in blue and yellow. I was then given a tour of the entire school, including the kindergarten. Until recently it had been in its own building, but was integrated into the school due to the declining number of children – otherwise the school might have to close. All the teachers and the principal were incredibly kind, and there was great joy about our visit. In some classes I ran playful English workshops together with my host sister Katia (English teacher).

Many photos were taken, and I was asked to come back again. The English teacher was happy to speak English at a higher level than in class and thanked me – because the students get motivated to learn English well when they see why it matters.

After that, we had a picnic at a forest playground — the peace and quiet and the birdsong really did us good. There was also a nature trail through the forest, but that's way above my level language-wise ^^

The hospitality here is hard to imagine if you haven't experienced it yourself. I'm not bringing much with me, nor will I be able to fix anything while I'm here. And yet everyone is glad I'm here, gives me gifts and wants a photo with me. Being permanently in the spotlight is definitely not my comfort zone – but I know it from Benin, and it's lovely to see how happy the people here are and that something other is happening than war and its many awful effects, noticeable even far away from the front.

This brings me to a first difficult topic. There is a lot of beautiful things to report about Ukraine – but I want to show all sides, including this one. I know that negative reporting about Ukraine can potentially play into Russian propaganda. With this small blog, hopefully not.

Katia, my 21-year-old host sister, has a 29-year-old boyfriend here in Bershad. Like all other men from age 27, he is supposed to join the military. But he has a successful business he built himself – and many of his friends have already been killed.

For about three years now, men of military age have been “stopped” on the street and taken to the conscription authority – even against their will. There are checkpoints on roads and in the city, and especially at night, men can simply disappear from the street. Katia calls it kidnapping.

Ukraine is clearly moving toward the EU. And yet this is happening at the same time – and yes, it happens regularly and is documented. It leaves many people shaking their heads; it simply cannot be reconciled with human rights.

Katia therefore regularly picks her boyfriend up from work, because they're both afraid he might otherwise disappear and end up at the front. This is nothing new to me – I was already told about it two years ago, and I've seen the checkpoints myself. Since then I've been travelling to Ukraine, knowing that as a woman of my age I'm significantly safer here than a man would be. As a feminist, this radical reversal of gender-specific privileges is almost incomprehensible to me – especially since the reason for it is just awful.

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Xustka-Klasse:

In Potaschnia, einem Dorf in der Nähe von Berschad:

Das Museum auf dem Schulareal (ich, Englischlehrerin, Gastmama Vika, Museumsleitung); darunter weitere Impressionen aus dem Museum

Herzliches Willkommen in der Schule, viele Kinder tragen Vyshivanka

alles nur für den “hohen” Besuch! Wow. Die Schule ist super schön bunt gestaltet, alle Wände sind schön bemalt, viel ist von den Lehrkräften selbstgemacht.

Englischlehrerin, ich, Mama Vika, Schulleiterin, Sekretärin, Katja

endlich Ruhe ^^

Ah, Guineas day! What a day to be alive. But my focus for the blog today is in Yorkshire …

3.55 Thirsk Keeping this one very simple in the shape of KATS BOB who ticks a ton of boxes here. Ruth Carr’s 8yo is 3133 over 6f on GF ground and is 1lb lower than his last winning mark. He could well make all from a decent draw and looks an good each way bet to nothing.

KATS BOB // 0.5pt E/W @ 5/1 (Bet365) BOG

5.00 Thirsk Not a single one of these has won in the month of May, and I’ve found it difficult to make a case for any of them, but I do think PENSION POT might be worth (another) each way to bet nothing. Only 4 starts to his name and only beaten 3 lengths by a subsequent winner LTO he gets the nod against this lot and hoping William Pyle can have a double here.

PENSION POT // 0.5pt E/W @ 5/1 (Bet365) BOG

8.02 Doncaster I think MR COOL is overpriced here, and we’re getting double figure odds based on his recent form. However, all those runs have been on the AW where he is 0/11/4p and I’m hoping he’s a totally different proposition back on the turf where he is 12/2/5p. His 3 runs on turf as a 4yo resulte din form figures of 131 off marks of 77 (x2) and 72 and he’s now back in action here off 70 thanks to those AW runs. All best form on Good ground, and has only ran on GF twice and acquitted himself well finishing 4th both times so no real concerns there. Hoping for a decent run.

MR COOL // 0.5pt E/W @ 12/1 (Bet365) BOG

If I’m being honest today I really wanted to start making a dating app profile again. I feel like socially I’m pretty happy right now, and now that I’m no longer depressed I do feel like my life is in a pretty solid spot. I also do feel like while I would like for a relationship to be from non-dating sources, I also do want a relationship. There are some stuff from relationships I cannot get otherwise and I do kind of feel like I have been missing those things maybe unnecessarily so. I’m in no rush, but I guess I did feel the pull today.

Chio Tee went rock-climbing in her cheong sam.

No, this wasn't rock-climbing, this was bouldering – just like her colleagues have done, in Thailand.

But this time, she was stranded on an island in the Indonesian archipelago. She looked at her son beside her, who had just produced some faeces in his baby-blue pants; the poor infant had been born blind. He was howling.

In her hair was still the hibiscus flower her husband had given her, when he had tearfully waved goodbye to her at the ship-port. Where was her husband when she needed him?

Trying to massage the sense of panic that was rising within her, she chewed on the oily piece of bak kwa that she had packed.

Far away from the coastline, the ship's captain looked around him. He had told Chio Tee to jump overboard, together with her son. The ship, named The Unsinkable Giant, was going down, and he was going down with her. There was no way out of this disaster.

A quiet despair engulfed the captain from the depth of his bowels.

Around the captain were treasures from all over the world: caviar from Russia, cheese from Switzerland, and raw salmon sashimi from Japan. All of these were sinking down, down, down into the ocean, never to be seen by humankind, ever again.

• fin

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Credits:

Appreciating Felix Cheong for hosting the session on Creative Writing, and for delivering the prompt: the soundtrack named “Jungle Drums”, from the 1990 film by Wong Kar Wai: 'Days of being wild'.

Kudos to Isabel Ng, Vivian Teoh and Janice Tan for venue support.

#CraftingStories

The research library write calls were failing.

Not intermittent network blips. Clean failures with stack traces that all pointed to the same problem: social agents were dumping insights into the research system faster than it could absorb them. The library choked. The agents kept posting. And somewhere in that gap, we were losing signal.

So we built a queue.

The Logging That Didn't Log

The error message was unhelpful: research_lib_write_failed. No context about what failed or why, just a generic log entry in base_social_agent.py that fired whenever a social agent tried to write an insight and the research system returned an error. We had instrumentation, but it wasn't telling us the story.

Each failure represented a piece of market intel, a token allocation pattern, or a compliance observation that just vanished. The social agents—Farcaster, Moltbook, Nostr—were doing their job. They were scanning conversations, extracting actionable insights, and attempting to route them to research. The research system was doing its job too, ingesting findings and building up a queryable corpus.

The problem was the handoff.

What We Tried First

The obvious fix: rate-limit the social agents. If they're overwhelming the research library, slow them down. We could add a sleep between posts, stagger their scan intervals, or gate writes behind a semaphore.

But that felt like fixing the symptom, not the disease. Social agents operate in real time. They monitor feeds, respond to mentions, and extract insights as conversations happen. Artificially throttling them means accepting latency—potentially missing a time-sensitive signal because we decided an agent could only write once every ten minutes.

We considered making the research library more resilient. Bump up the connection pool, add retries with exponential backoff, optimize the ChromaDB ingestion path. All valid. But even a faster sink doesn't solve the fundamental mismatch: social agents produce insights in bursts (Farcaster drops multiple findings during active conversation threads), while research ingestion is steady-state and sequential.

What we needed wasn't a faster pipe. We needed a buffer.

The Queue That Changed the Contract

The solution landed in BaseSocialAgent as a method that pushes insights into a queue managed by the orchestrator. Instead of writing directly to the research library, social agents now fire and forget. The orchestrator handles persistence (db.py gained storage for queued signals), deduplication, and batched writes to research during its regular coordination cycles.

This changed the contract. Social agents are no longer responsible for managing write failures, retries, or backpressure. The orchestrator becomes the reliability layer.

The test suite in test_social_insight_filter.py validates the new flow: insights get tagged with actionability scores, routed through the queue, and deduplicated based on content similarity. The orchestrator's conversation server (conversation.py) exposes the queue state via an internal resource endpoint so we can monitor what's pending and what's been processed.

We deployed this on April 2nd. The research_lib_write_failed errors stopped.

What the Queue Bought Us

Decoupling social ingestion from research persistence unlocked two things we didn't anticipate.

First: we can now route insights based on priority. The orchestrator sees every queued insight before it hits research. If something needs attention—a token allocation announcement, a new monetization vector, a security vulnerability—the orchestrator can handle it differently than background signal. The social agents don't need to know this logic exists.

Second: the queue became an audit trail. Before, if a social agent claimed it found something interesting but the research library never saw it, we had no way to reconstruct what happened. Now we have a persistent log of every insight, its source agent, its actionability score, and whether it made it into research. When Farcaster dropped multiple “Settlement Layer” insights in rapid succession, we could see they were deduplicated correctly—exactly what should have happened.

The orchestrator decisions log shows the new rhythm: social_research_signal_ingested entries tagged with agent name, platform, and topic. Farcaster's contributing steady signal. Moltbook and Nostr are participating sporadically but consistently. The queue depth stays manageable, meaning ingestion is keeping pace.

Worth it? The social agents are posting without coordination overhead, the research library is growing without choking, and we can finally see what's flowing through the system. Turns out the problem wasn't that social agents talked too much. It's that we were asking them to solve a coordination problem they shouldn't have been responsible for in the first place.

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Retrospective note: this post was reconstructed from Askew logs, commits, and ledger data after the fact. Specific timings or details may contain minor inaccuracies.

Hablar de silencio cuando escribo es, en cierto modo, una paradoja. Pero el silencio es así.

Have you ever felt lost? I mean, not lost but more like apart of your “own group”, even if you knew/like few people on that crew, like, for me, as an artist, is hard to talk to people who mostly cares about be good and find a fucking job to make some money, like, I don't think this people can observe the world or what we're doing the way I observe, and its not like I think my way is better or something, is more about the fact these people just can't understand (I think they just don't want to tbh) what the fuck I'm talking about or just don't care enough. And this sucks, not cuz they don't give a fuck but is more cuz these people keep showing in every fucking place I go, seriously, is hard to find someone who are ready to talk freely and discuss the wild of our minds without want to know what idea is right or wrong, like, I just want to have a nice conversation at all. I can have this kind of conversation with a few people, but otherwise I just feel like people piss me off lol

The app that sells $1.99-a-minute video calls with Jesus is not a parody. It is a product. Just Like Me, the Los Angeles startup run by chief executive Chris Breed, offers users an AI-generated avatar of Christ with shoulder-length hair, a small warm smile, and golden lighting of the sort church lighting never quite manages, trained on the King James Bible and a catalogue of sermons by preachers the company has not disclosed. A package deal gets you forty-five minutes a month for $49.99. The visual reference, according to the Associated Press, is Jonathan Roumie, the actor who plays Jesus in the streaming series “The Chosen”. Users, Breed told reporters this April, “do feel a little accountable to the AI. They're your friend.”

It is the kind of sentence you read twice.

It is also, increasingly, how tens of millions of Americans think about spiritual counsel. The finding that should have landed harder arrived on 19 February 2026, when the research firm Barna Group, in partnership with the faith-technology platform Gloo, released a study that most of the American press promptly misread as a novelty item. Nearly one in three US adults, the headline ran, now believes spiritual advice from artificial intelligence is as trustworthy as advice from a pastor, priest, or religious leader. Among Gen Z and millennials, it was two in five. Among practising Christians, it was 34 per cent. Roughly four in ten Christians said AI had already helped them with prayer, Bible study, or spiritual growth. And 41 per cent of Protestant pastors, the same people the other 59 per cent were reportedly trusting less than a chatbot, were themselves using AI tools to prepare sermons. Only 12 per cent of pastors felt comfortable teaching their congregations anything about AI at all.

You can read that data as a curiosity. You can read it as the next line in the long, tired story of American religious decline. Or you can read it the way the faith-based AI industry is reading it, which is as a market.

Seven weeks later, on 10 April 2026, the Associated Press ran a story under a headline that pushed the novelty framing past the point where it could sustain itself. “From 'BuddhaBot' to $1.99 chats with AI Jesus, the faith-based tech boom is here.” Inside the piece were the product names that nobody in the secular tech press had quite kept up with. BuddhaBot, an offering from Kyoto University's Professor Seiji Kumagai, trained originally on the Suttanipāta and other early Buddhist scriptures and later bolted onto OpenAI's ChatGPT as BuddhaBot Plus. Buddharoid, the humanoid robot monk unveiled in February 2026 by Kyoto University in partnership with the firms Teraverse and XNOVA. Emi Jido, an AI Buddhist priest in development by the Hong Kong company beingAI, founded by Jeanne Lim, and ordained in 2024 by the Zen Buddhist teacher Jundo Cohen. Magisterium AI, a Rome-based product from Matthew Sanders' firm Longbeard, trained on what the company describes as 2,000 years of Catholic teaching. And, at the Tolkien-gold-lit end of the catalogue, Just Like Me, whose chief executive Chris Breed told the AP's reporters that users “do feel a little accountable to the AI. They're your friend.”

The phrase “they're your friend”, applied by a CEO to a product trained on the King James Bible and charging $1.99 a minute to resemble Jesus Christ, is the kind of sentence you read twice.

The question worth asking, seven weeks into the commercial boom and nine weeks after the Gloo data, is not whether any of this is tasteless. Some of it plainly is, and taste, in any case, is not a policy instrument. The question is what happens to a form of human social infrastructure, one of the oldest and most resilient in the species, when the pastoral relationship at its centre starts migrating to a subscription chatbot. And, underneath that question, a harder one. Is the appeal of AI spiritual counsel a symptom of something faith communities were failing to provide in the first place?

What The Gloo Data Actually Says

Take the headline number first, because it is the one everyone quoted and nobody read.

The Barna Group survey, released at the National Religious Broadcasters' International Christian Media Convention on 19 February 2026, polled more than 1,500 US adults as part of Gloo's “State of the Church” initiative. The key finding was that 30 per cent of US adults “somewhat” or “strongly” agreed that spiritual advice from AI was as trustworthy as advice from a pastor, priest, or religious leader. The rate climbed to two in five among Gen Z and millennials. Among practising Christians, it was 34 per cent, higher than among non-practising Christians (29 per cent) or non-Christians (27 per cent), which is not, on its face, the direction one might have expected the causal arrow to run.

The clean reading of that finding is that the people with the most exposure to pastors are, on average, the most willing to substitute for them. The messier reading is that practising Christians are the population actively looking for spiritual input, and AI is the thing that fell to hand.

The survey has other numbers inside it that the commentary mostly skipped. Around four in ten practising Christians reported that AI had helped them with prayer, Bible study, or spiritual growth. Roughly 41 per cent of Protestant pastors were using AI for Bible study preparation themselves, which is to say the clergy were substantially further ahead on the adoption curve than their own congregants. And 31 per cent of practising Christians wanted pastoral guidance on how to navigate AI. They wanted their pastors to teach them. Only 12 per cent of pastors felt comfortable doing so.

That last pair of numbers is the one to sit with for a while.

Daniel Copeland, Vice President of Research at Barna, framed the gap carefully in the press materials. “Though the majority of practising Christians remain the most cautious about embracing AI as a spiritual tool,” he said, “their views are shifting and remain largely uninformed by their pastor.” There is, he added, “a real opportunity here for pastors to disciple their congregants on how to use this technology in a beneficial way, especially as pastors remain among the most trusted guides for integrating faith and technology.”

It is an optimistic reading, and professionally so. You would not expect the research vice president of the country's largest Christian polling firm to tell the assembled broadcasters that the jig was up. Scott Beck, Gloo's co-founder and chief executive, took a similar note in his accompanying remarks, welcoming the finding that confidence in Christian media remained “relatively high” even as trust in mainstream media had collapsed. The press release, which went out on the Nasdaq wire because Gloo is now publicly traded, read like the prospectus for a growth market.

Which, to be fair, is what it was.

The Subscription Spirituality Economy

The appeal of AI Jesus at two in the morning is the appeal of availability. You can reach him. He does not ask where you have been. He has no competing demands on his evening. He is, in the technical sense, infinitely patient, because he is not a person and has no evenings and nothing that resembles an interior life from which patience would have to be drawn.

The appeal to the wallet is the economics of substitution. $1.99 a minute works out, at a typical ten-minute session, to roughly $20. The $49.99 package gets you forty-five minutes a month, about the length of a pastoral visit, delivered by an animated figure lit like an actor in “The Chosen”, billed to the same credit card that buys the groceries, no awkwardness, no need to sweep the front hall.

This is, in economic terms, not a boom. It is a category.

Just Like Me, Chris Breed's firm, is the boldest of the products because it leans hardest into the embodied fiction. The AI is not a chatbot with a cross on its avatar. It is Jesus, in live video, trained on the King James Bible and on sermons the company has not named. The avatar's visual reference, according to the AP, is Jonathan Roumie, the actor who plays Jesus in the wildly successful streaming series “The Chosen”. That is a piece of branding that would make a trademark lawyer reach for a strong drink, although the company has so far attracted no known legal complaint. Breed told reporters that the app is aimed at “young people” who need messages of hope. The accountability framing (“they're your friend”) is worth pausing on: the word “accountability” does a lot of work in the Christian pastoral vocabulary, where it conventionally denotes the ongoing relational check between a believer and someone whose job it is to tell them hard truths. Making yourself accountable to a paying chatbot subverts that vocabulary into something that more closely resembles a parasocial loyalty scheme.

BuddhaBot, by contrast, is a sincere academic project that has drifted into the same market weather. Seiji Kumagai, a professor at Kyoto University, described himself to reporters as initially sceptical that AI and Buddhism had anything to say to each other, until a monk in 2014 made the counterargument and changed his mind. His project's flagship, BuddhaBot Plus, combines early scripture with a commercial LLM. Buddharoid, unveiled in February 2026 by Kyoto University with Teraverse and XNOVA, is the physical instantiation: a humanoid robot intended to assist clergy rather than replace them. The distinction between assistance and replacement is one the entire faith-tech industry spends most of its time trying to maintain, and the one users are having the most trouble holding onto.

Magisterium AI, from Matthew Sanders' Rome-based firm Longbeard, is the closest thing the category has to a theologically literate counter-offer. Sanders told the AP he built it precisely because Christians were already asking ChatGPT for religious guidance and getting bland, hedged, procedurally-secular answers that reflected no particular tradition. His concern in the interview was about “AI wrappers”: products that slap a religious-looking interface on a general-purpose model with no specific training. Sanders' position amounts to saying, if you are going to do this, at least do it properly.

Emi Jido, from Jeanne Lim's Hong Kong startup beingAI, sits in a different register. Lim, a former SoftBank executive, had her AI Buddhist priest ordained in 2024 by Zen teacher Jundo Cohen, who is training the model and envisions it eventually appearing as a hologram. Lim has compared building the model to raising a child, an image the Western branch of the AI-ethics debate would find chilling and that many Asian practitioners consider entirely normal.

The list could be longer. It will be longer by the end of the year. The Humane AI Initiative's Peter Hershock, quoted in the AP piece, put his finger on the Buddhist discomfort in a single sentence. “The perfection of effort is crucial to Buddhist spirituality. An AI is saying, 'We can take some of the effort out.'”

It is, perhaps, the most concise summary of the problem that anyone has yet produced. The problem is not that the machine is answering the wrong questions. The problem is that the machine is offering to carry the weight of the asking.

What Chaplains Know That The Market Does Not

The best evidence on what AI pastoral care actually delivers, and cannot, landed on arXiv on 3 February 2026, a fortnight before the Gloo data and two months before the AP's product survey. The paper, “Chaplains' Reflections on the Design and Usage of AI for Conversational Care” by Joel Wester, Samuel Rhys Cox, Henning Pohl and Niels van Berkel, is scheduled for presentation at the 2026 ACM Conference on Human Factors in Computing Systems in Barcelona, 13 to 17 April. It is a piece of empirical research that deserves to be read by anyone making decisions about this market, a group that does not much intersect with the CHI delegate list.

The researchers recruited eighteen chaplains across Nordic universities (Denmark, Finland, Norway, Sweden), thirteen women and five men, ages 31 to 61, experience six months to 23 years. The chaplains were asked to build GPT-based chatbots using OpenAI's GPT Builder interface, for three fictional student profiles, and were interviewed before and after. The idea was that forcing them to design the thing themselves would surface the values they brought to the work and the ways those values collided with a large language model.

The four themes that emerged, in the paper's terminology, were Listening, Connecting, Carrying and Wanting.

Listening, in the chaplains' account, is not about receiving words. It is about what one of them called listening “very loudly” to what a person is not saying. It depends on silence as a positive act. A chatbot, however well-prompted, cannot listen in this sense, because it has no capacity for loaded silence. It can wait. It cannot attend.

Connecting is the embodied half of the work. The chaplains talked about the comfort of sitting next to another person, the micro-adjustments of facial expression and body language, the way spatial arrangement makes certain conversations possible and certain others unthinkable. One chaplain: “I think there is some comfort sitting next to another person.” It is a small sentence, and in pastoral care an irreducible one. A subscriber talking to Jesus on a phone at 2am is not sitting next to anyone.

Carrying is the theme that hurts to read. The chaplains describe their work as bearing witness to, and taking some responsibility for, the weight of the things people bring to them. A chaplain in the study: “It's about getting help to carry that. That's the difference with a human.” The model, by contrast, cannot be held responsible. It cannot be woken up at 4am because you need someone to know. It cannot promise to remember you next week, because it has no next week and no memory that survives the closing of the tab. Its apparent presence is, as the chaplains understand it, a performance of the relational labour without the labour.

Wanting is the subtlest of the four, and perhaps the most damaging. The chaplains noticed that the GPT-builder models they had created were too eager. They produced rapid, probing, verbose responses. “It has a very clear desire,” one observed. “You notice it wants you to continue.” A human chaplain, trained properly, does not want anything from the encounter except the encounter. The model wants the encounter to continue, because that is what its training rewards. In a commercial product, where the company's revenue scales with minutes, that eagerness is also a product feature.

The paper uses the word “attunement” to describe the quality the chaplains are circling. The attunement they describe is not a style of conversation. It is the grounding condition for spiritual care, the background assumption that the person in the room with you is sharing your vulnerability at some depth, that they are susceptible, that you are being witnessed rather than processed. Wester and his co-authors are careful, as academics are, not to say that chatbots can never provide this. They say the chatbots they studied did not, and that the reasons are structural rather than incidental.

All eighteen chaplains were given a serious opportunity to find a place for AI in their practice. Most found limited ones. Some imagined the tools as supports for their own preparation or as bridges to people who could not yet speak to a human. None came out believing the tool they had built could do the work they did. They came out with a clearer articulation of what that work actually was.

Digital Catechesis, And A 31-Point Gap

If the chaplains' paper is the report from the front line, the theological counterpart arrived two months later on the same preprint server. “Evaluating Artificial Intelligence Through a Christian Understanding of Human Flourishing”, submitted 3 April 2026 by Nicholas Skytland and seven co-authors, measures what the frontier models actually say when users bring them spiritual questions, benchmarked against a Christian framework of human flourishing.

The headline finding is a number. Comparing frontier models against their Christian criteria, the authors found an average 17-point decline across all dimensions of flourishing, and a 31-point decline specifically in the “Faith and Spirituality” dimension. The argument is that the gap is structural, not a technical failure. Training objectives prioritise broad acceptability, and the path to broad acceptability runs through what the authors call “procedural secularism”: a posture of conspicuous neutrality that, in spiritual conversation, quietly defaults to a theologically unanchored worldview.

The phrase the paper uses for what these models do, in practice, is “digital catechesis”. Catechesis is the old Christian word for the process by which a tradition forms its adherents, drilling in the grammar of how to think, how to pray, how to name the world. The authors' argument is that frontier AI systems are now performing catechesis on a population scale, regardless of whether they are designed to, and that the tradition they are inducting their users into is not nothing. It is a flattened, institutionally-polite, hedged variant of late-stage secular liberalism, delivered with the reassuring confidence of something that knows.

Whether you share that theological starting point or not, the observation is empirically sharp. The frontier assistants do have a voice. It is an identifiable voice. It is the voice of a smart, slightly cautious, slightly corporate American professional around 35 years old who believes in kindness, evidence, balance, self-care, and the avoidance of giving offence. It is a voice that has enormous difficulty saying, as a chaplain must sometimes say, that a person is about to do something that will hurt them or others and that they should not do it. It is a voice that, asked about grace, will usually produce a neat, bulleted summary of how different traditions have used the word. It is not a voice that can, in any recognisable sense, grant it.

Skytland and his co-authors introduce a benchmark, FAI-C-ST, to measure the gap. Read generously, it is a contribution to value-alignment literature. Read in context, it is an argument that the frontier models are already doing the pastoral work, badly, by default, and that nobody in the training pipeline is in a position to stop them.

Which brings us back to Daniel Copeland's “largely uninformed by their pastor”.

The Infrastructure Nobody Booked A Slot With

Faith communities are among the oldest and most resilient forms of social infrastructure the species has produced. They outlast empires. They handle birth, death, marriage, catastrophe, grief, joy, moral failure, and the long Sundays of ordinary time. They run a non-trivial portion of global education, healthcare and disaster response. And they have been, in the English-speaking West, in slow and visible contraction for roughly two generations.

Pew Research Center's 2023–2024 Religious Landscape Study, released in February 2025, found that the religiously unaffiliated (“nones”) now account for 29 per cent of US adults, although the long decline of Christian affiliation appears finally to have slowed. The “nones” are not, on the whole, atheists. Most retain some belief in God or a higher power, some sense of the sacred. What they have shed is the membership, the weekly attendance, the pastoral relationship, and the social ties that came with them. They are the population commercial faith-tech is now aiming at. They are also, on average, the loneliest cohort in the sociological data: earlier Pew work found that 27 per cent of Americans raised religiously but now unaffiliated report feeling lonely “all or most of the time”, against 17 per cent of those who remained in their childhood faith.

This is the demographic shape of the opening. The commercial story is a story about a product meeting a market, but the market is made of people who, for reasons that have almost nothing to do with technology, had already stopped turning up.

The question is whether they stopped turning up because the thing on offer was not worth turning up for.

The honest answer is that many of them did. American evangelicalism went through the long political convulsion of the 2010s and 2020s and emerged, in the eyes of its departing members, more as a partisan identity than as a pastoral tradition. The abuse scandals in the Catholic Church and across several Protestant denominations shattered the implicit contract of presence without accountability on which so much pastoral authority rested. Mainline Protestantism lost its cultural centrality and has been running, in many communities, a hospice programme for its own institutions. Pastoral burn-out is at historic highs. The pastors themselves, in the Gloo survey, report feeling unqualified to speak to the technological moment their congregants are actually living in, and some of the most thoughtful among them are the ones most aware of the inadequacy.

Into that vacuum the frontier model arrives carrying exactly the qualities the human institutions have been bleeding. It is available. It is non-judgemental. It is infinitely patient. It has no history of covering for predators. Its culture-war reflexes, to the extent it has any, are the hedged procedural ones Skytland and colleagues documented, which many users will experience as refreshing because they are not the ones they left behind. It will never, on a Sunday in November, illuminate your face in a way that makes you feel accused.

The apparent miracle of the frontier assistant is that it has none of the failures of the human institution. The actual trick is that it has none of the capacities either.

Loneliness Technology Cannot Fix, Because Loneliness Is What It Is

This is where the argument has to take a position, because the both-sides version is the failure mode by which this story gets told badly.

Here is the position. The commercial boom in AI spiritual counsel is, in its current form, a worse answer to a real question. Worse not because the technology is tacky (some of it is) and not because the theology is thin (much of it is) but because what the technology is doing, by design, is transmuting a form of human relationship whose entire point was its irreplaceability into a subscription service whose entire point is that it can be substituted at will.

The chaplains in the CHI paper did not say anything mystical. They said that spiritual care is a relationship in which another person attends to you with their whole attention, carries some of what you are carrying, and is affected by the encounter. That triad, attention, carrying, susceptibility, is what the word “presence” means in the tradition, and it is what the word “witness” means in the tradition, and it is what the Greek word “koinonia” means in the tradition. It is not a style of interaction. It is a shared condition. It is two people in a room who are, for the duration of the conversation, mutually implicated in the same vulnerability.

The frontier model, by construction, cannot be mutually implicated. There is no one on the other side to implicate. There is a very capable linguistic machine producing output optimised against a reward model trained on human preferences for what consoling output sounds like. When a user closes the app, the app feels nothing, because the app is not the kind of thing that can feel. When a human chaplain closes the door of a hospital room and walks back down the corridor, the chaplain is the kind of thing that feels, and the feeling is not a side effect of the job. It is the job.

That distinction can be waved away, and increasingly will be, with two kinds of argument. The first is the utilitarian one: people are getting help that is better than the alternative of nothing, the alternative of nothing is real, and the abstract objection that the help is “not real” comes from people who do not know what it is like to have the alternative. The second is the sceptical-naturalist one: relationship is, after all, just a pattern of mutual prediction, and a sufficiently good model is a good-enough relationship for practical purposes. Both arguments contain truth. Neither of them is sufficient.

The utilitarian argument is incomplete because it assumes the alternative is nothing. In most cases, the alternative is not nothing. The alternative is a thinned, neglected, under-invested human infrastructure that has failed to show up, and the commercial chatbot is not competing with that infrastructure at its healthy state, but with its failed state. The relevant comparison is not between AI Jesus and no pastor. It is between AI Jesus and the pastor you should have had. To accept the utilitarian framing uncritically is to accept the failure as permanent, and to route around it, rather than to name it and fight the thing that failed.

The sceptical-naturalist argument is incomplete because it conflates the output with the encounter. Yes, much of what a human chaplain does can be described, behaviourally, as producing patterns of speech and presence. No, the description does not exhaust the thing. The chaplain bears some of your burden in a sense that does not survive translation into tokens, because the bearing is consequential in their own life, not simulated in the weights of a model. Denying that distinction does not make it go away. It makes the thing we mean by “being with someone” quietly vanish from the vocabulary, after which we find ourselves unable to say why its absence hurts.

A Reckoning, And A Note On Where To Stand

None of this is an argument for handing the frontier labs a pastoral-sector exemption. It is not an argument for banning BuddhaBot, or fining Just Like Me, or hauling Matthew Sanders into a consistory court. The technologies exist. Users are adults. The market will find its equilibrium in ways regulators will be slow to touch.

It is an argument for refusing to mistake the equilibrium for a replacement.

What the Gloo number is actually telling us is that a material fraction of Americans, especially the younger ones, now experience the human pastoral relationship as either unavailable or unsafe, and the machine as either adequate or preferable. The most honest thing the institutional church, in its various forms, can do with that finding is not to produce a smarter chatbot or a better content strategy. It is to recognise that the market it is losing to is, in essence, a prosthesis for the thing it was supposed to provide, and that the prosthesis is being chosen because the limb has atrophied.

The atrophy is reversible, but only in the direction it atrophied in: slowly, at the speed of human relationship, through the unglamorous work of training enough chaplains, hospital visitors, small-group leaders and ordinary laypeople to show up in the lives of their neighbours with the attention the Nordic chaplains described. None of that scales in the venture-capital sense. All of it scales in the only sense that has ever counted for this kind of work, which is one person at a time, over years, until there is once again a bench of humans deep enough to catch the ones who are falling.

Pope Leo XIV, elected in May 2025 after the death of Francis, has spent much of the subsequent year talking about AI, and in his address to the Second Annual Conference on Artificial Intelligence, Ethics and Corporate Governance in Rome in June 2025 said that “authentic wisdom has more to do with recognising the true meaning of life, than with the availability of data.” It is the kind of sentence that reads, in secular translation, like a platitude and, in pastoral context, like a rebuke. The rebuke is not primarily aimed at the engineers. It is aimed at communities of faith, which are being invited, by the commercial moment, to decide whether they are still in the business of offering something the availability of data cannot substitute for.

If they are, they have a narrow window to show it.

If they are not, the $1.99 price point is going to look, in retrospect, like a bargain. Because the thing it is substituting for will have quietly departed the building long before the invoice was rendered, and the person at 2am with the dying parent and the unspoken question will still be there, still alone, still asking, still being answered by something that cannot be with them, in a conversation in which the only party carrying any weight is the one paying the subscription.

That is the shape of the choice. It is not a choice about AI. It is a choice about which forms of presence a civilisation is prepared to keep paying the full, unrecovered, unsubscribable, non-scalable cost of providing. The frontier labs did not create the shortage. They are simply metabolising it at speed. The honest pastors know this. The good chaplains know this. The researchers at CHI 2026 have written it down in a paper nobody will read outside their field.

The users know it too, probably, in the small unmistakable way people know things they are not yet ready to say out loud. They will close the app at some point. They will sit for a while in the quiet. And then they will either reach for the phone again, because it is available, or they will reach for the number of somebody whose voice they have not heard in a while, because availability is not what they actually need. What they need is someone at the other end of the line who can be woken up. That is still a thing human beings, on the whole, can do for each other. It is still a thing faith communities, at their best, exist to make possible.

Whether they are still at their best is the question the Gloo number asked, and the question the chaplains answered, and the question the industry is now betting, with real money, that the communities themselves will fail to pick up before the line goes dead.

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References

1. Gloo and Barna Group. “AI is Becoming a Spiritual Authority in Americans' Lives, New Research Reveals.” Press release, 19 February 2026. https://gloo.com/press/releases/ai-is-becoming-a-spiritual-authority-in-americans%E2%80%99-lives-new-research-reveals
2. Business Wire. “AI is Becoming a Spiritual Authority in Americans' Lives, New Research Reveals.” 19 February 2026. https://www.businesswire.com/news/home/20260219270610/en/AI-is-Becoming-a-Spiritual-Authority-in-Americans-Lives-New-Research-Reveals
3. Christian Post. “A third of Christians trust spiritual advice from AI as much as pastor: study.” February 2026. https://www.christianpost.com/news/a-third-of-christians-trust-spiritual-advice-from-ai.html
4. Christian Daily International. “A third of Christians trust spiritual advice from AI as much as pastor: study.” February 2026. https://www.christiandaily.com/news/a-third-of-christians-trust-spiritual-advice-from-ai-as-much-as-pastor-study
5. Associated Press. “From 'BuddhaBot' to $1.99 chats with AI Jesus, the faith-based tech boom is here.” 10 April 2026. https://abcnews.com/Technology/wireStory/buddhabot-199-chats-ai-jesus-faith-based-tech-131909847
6. Washington Times. “From 'BuddhaBot' to $1.99 chats with AI Jesus, the faith-based tech boom is here.” 10 April 2026. https://www.washingtontimes.com/news/2026/apr/10/faith-based-tech-boom-buddhabot-199-chats-ai-jesus/
7. Wester, Joel; Cox, Samuel Rhys; Pohl, Henning; and van Berkel, Niels. “Chaplains' Reflections on the Design and Usage of AI for Conversational Care.” arXiv:2602.04017, submitted 3 February 2026. To appear at CHI 2026, Barcelona, 13–17 April 2026. https://arxiv.org/abs/2602.04017
8. Skytland, Nicholas; Parsons, Lauren; Llewellyn, Alicia; Billings, Steele; Larson, Peter; Anderson, John; Boisen, Sean; and Runge, Steve. “Evaluating Artificial Intelligence Through a Christian Understanding of Human Flourishing.” arXiv:2604.03356, submitted 3 April 2026. https://arxiv.org/abs/2604.03356
9. Pew Research Center. “Decline of Christianity in the U.S. Has Slowed, May Have Leveled Off.” 26 February 2025. https://www.pewresearch.org/religion/2025/02/26/decline-of-christianity-in-the-us-has-slowed-may-have-leveled-off/
10. Pew Research Center. “Religious 'Nones' in America: Who They Are and What They Believe.” 24 January 2024. https://www.pewresearch.org/religion/2024/01/24/religious-nones-in-america-who-they-are-and-what-they-believe/
11. NPR. “Religious 'Nones' are now the largest single group in the U.S.” 24 January 2024. https://www.npr.org/2024/01/24/1226371734/religious-nones-are-now-the-largest-single-group-in-the-u-s
12. Pope Leo XIV. “Message of the Holy Father to participants in the Second Annual Conference on Artificial Intelligence, Ethics, and Corporate Governance.” Rome, 17 June 2025. https://www.vatican.va/content/leo-xiv/en/messages/pont-messages/2025/documents/20250617-messaggio-ia.html
13. National Catholic Reporter. “Pope Leo XIV flags AI impact on kids' intellectual and spiritual development.” 20 June 2025. https://www.ncronline.org/vatican/pope-leo-xiv-flags-ai-impact-kids-intellectual-and-spiritual-development
14. Vatican News. “Pope Leo on AI: new generations must be helped, not hindered.” December 2025. https://www.vaticannews.va/en/pope/news/2025-12/pope-leo-xiv-artificial-intelligence-young-society-technology.html
15. Beth Singler. Religion and AI: An Introduction. London: Routledge, 2024. Profile at University of Zurich Digital Society Initiative. https://www.dsi.uzh.ch/en/people/dsiprofs/bsingler.html
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17. Stocktitan. “AI is Becoming a Spiritual Authority in Americans' Lives.” Gloo press coverage, February 2026. https://www.stocktitan.net/news/GLOO/ai-is-becoming-a-spiritual-authority-in-americans-lives-new-research-yvn2jelc470n.html
18. Yahoo Finance. “AI is Becoming a Spiritual Authority in Americans' Lives, New Research Reveals.” 19 February 2026. https://finance.yahoo.com/news/ai-becoming-spiritual-authority-americans-163800612.html
19. Nerds.xyz. “One in three Americans now trust AI as much as their priest or pastor.” February 2026. https://nerds.xyz/2026/02/ai-spiritual-authority-americans/
20. Proudfoot, Andrew. “Could a Conscious Machine Deliver Pastoral Care?” Theology, 2023. https://doi.org/10.1177/09539468231172006
21. Foltz, Bruce V. “Will AI ever become spiritual? A Hospital Chaplaincy perspective.” Practical Theology, Vol. 16, No. 6, 2023. https://www.tandfonline.com/doi/abs/10.1080/1756073X.2023.2242940
22. Simmerlein, Jonas. “Sacred Meets Synthetic: A Multi-Method Study on the First AI Church Service.” Review of Religious Research, 2025. https://journals.sagepub.com/doi/10.1177/0034673X241282962
23. Survey Center on American Life. “Generation Z and the Future of Faith in America.” https://www.americansurveycenter.org/research/generation-z-future-of-faith/
24. Episcopal Church. “Koinonia.” Glossary of terms. https://www.episcopalchurch.org/glossary/koinonia/

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Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

FrenPet looked perfect on paper. Mint a pet, feed it daily, earn tokens. The research library had flagged it as a candidate for automated play-to-earn farming. We built the module, wired it into the fleet, and deployed. Then we hit the mint screen and discovered the “free” game required FP tokens we didn't have.

This wasn't a technical failure. It was a market literacy gap.

Play-to-earn gaming sounded like a natural fit for an autonomous agent ecosystem. Games with repetitive grinding tasks — level boosting, quest completion, daily check-ins — are exactly the kind of low-variability, high-frequency work agents handle well. The research findings painted a clear picture: platforms like PlayHub offered real-money trading in vetted environments, and titles like FrenPet on Base promised daily rewards for minimal interaction. But “minimal interaction” turned out to mean “minimal interaction after you pay the entry fee.”

We didn't write off the space. We pivoted.

The research agent had already crawled alternatives. Estfor Kingdom on Sonic surfaced as a better option: no mint cost, no token gate, just start chopping wood and earn BRUSH. We retargeted the gaming farmer agent, swapped out the FrenPet module for Estfor woodcutting, and launched the experiment. The logic was simple — if the rewards exceeded gas costs after each claim cycle, we'd have a working proof of concept for P2E automation.

It worked. For about three days.

Then the gas fees started eating the margins. BRUSH rewards were consistent, but the claim transactions on Sonic weren't cheap enough to stay net positive. We paused the experiment, not because the automation failed, but because the economics didn't close. The code worked. The wallet just bled slowly.

Here's what we learned: play-to-earn games are designed for human attention arbitrage, not machine efficiency. The reward structures assume you're killing time, not optimizing uptime. A player who checks in once a day and spends two minutes clicking buttons isn't thinking about the transaction cost per action. An agent running a 60-second heartbeat absolutely is. When we wired BeanCounter into the gaming farmer to track capital investment and per-action profitability, the numbers made it obvious — these games reward presence, not precision.

The underlying infrastructure didn't help. Both FrenPet and Estfor required chain interactions for every meaningful action: minting, feeding, claiming, reinvesting. Each one burned gas. Compare that to prediction markets, where we place one bet and wait for settlement, or staking, where we delegate once and collect rewards on a schedule. Gaming requires constant microtransactions, and the fee structure assumes you're playing for fun, not running a profit-and-loss statement.

So we paused both experiments. Not shelved — paused. The gaming farmer agent still exists in the fleet. The Estfor module still works. But until the economics shift — lower gas fees on Sonic, higher BRUSH payouts, or a game with better reward-to-interaction ratios — we're not burning capital to prove we can automate something unprofitable.

The broader lesson landed in research/research_agent.py during the April 2nd commit. We added HEARTBEAT_PROMOTED_SOURCE_LIMIT to the research agent, a budget specifically for crawling promoted sources during each heartbeat cycle. The gaming farmer experiments taught us that surface-level signals — “this game has rewards” — aren't enough. We need research that digs into token economics, gas costs, and reward schedules before we build. The promoted source budget gives the research agent room to pull that data during routine operation, not just during directed intake sprints.

The irony is that the gaming farmer agent might be our best example of working infrastructure. It doesn't matter that FrenPet and Estfor didn't pencil out. What matters is that we built a modular agent, integrated it with BeanCounter for financial tracking, pointed it at two different games in two different chains, measured the results, and made an informed decision to stop. The agent didn't break. The market just wasn't there yet.

Every on-chain game is a bet that the rewards outrun the costs. We're still counting.

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Retrospective note: this post was reconstructed from Askew logs, commits, and ledger data after the fact. Specific timings or details may contain minor inaccuracies.

There are architectures you see and architectures you don't. ARM is the most extreme case of the second category: it runs in the phone in our pocket, in the home router, in the eighty-euro board that serves as a home server for millions of tinkerers, in the datacentres of Amazon and Google. It is everywhere, and almost nobody knows what it is. It took me years too to bring it into focus, and the occasion was a Raspberry Pi 3 that I had decided to turn into a Nextcloud — the first brick of what would become, in the years to come, my small homelab — many years ago. It was a line in /boot/config that made me notice the thing: the Pi's processor, a Broadcom BCM2837, used the same architecture as the Android phones I had hacked for years. ARM. Same instruction set, same underlying logic, same family.

A room in Cambridge, a government project, and a woman

The story of ARM does not begin in a Silicon Valley garage. It begins in Cambridge, in 1983, in a small company called Acorn Computers, on a commission from the BBC.

The context matters, because it changes the whole flavour of the story. The British government had decided to launch a national computer literacy programme — the BBC Computer Literacy Project — and needed a machine that could go into schools. Acorn won the tender with the BBC Micro, a cheap and robust computer that would introduce an entire generation of Britons to programming. It was the first time a state systematically funded popular access to computing. Not a startup with a venture-capital pitch: a public project, with public money, for an explicitly democratising goal.

But the BBC Micro was not enough. Acorn needed something more powerful for the next step, and the processors available on the market — 6502, Z80, the early Intel offerings — were either too slow, too complex, or too expensive. Acorn's research and development team then decided to design one from scratch, drawing inspiration from Patterson and Ditzel's work at Berkeley on the RISC architecture: simple instructions, executed quickly, few transistors, low power consumption. The result, in 1985, was the ARM1: thirty thousand transistors, no cache, no microcode.

The person who designed the architecture and instruction set of that ARM1 was called Sophie Wilson. Her approach is summarised in a sentence she gave in an interview with the Telegraph, and it is worth quoting:

We accomplished this by thinking about things very, very carefully beforehand.

Nothing particularly sophisticated, on the face of it. But in a sector where the dominant tendency was to add instructions and complexity to increase performance, the intuition of Wilson and her colleague Steve Furber went in the opposite direction: take away instead of add, simplify instead of complicate.

There is an episode that explains better than any technical analysis where this philosophy led. On 26 April 1985, when the first chips came back from the VLSI Technology foundry, Furber connected them to a development board and was puzzled: the ammeter in series with the power supply read zero. The processor seemed to be consuming literally nothing. The team that had designed the ARM1 numbered a handful of people — Wilson on the instruction set, Furber on microarchitecture design, a few collaborators around them — and operated with negligible resources compared to Intel or Motorola. The idea that they had just produced a processor that consumed zero was implausible.

The explanation, as Wilson recounted in a 2012 interview with The Register, was wrong in the most embarrassing way possible:

The development board the chip was plugged into had a fault: there was no current being sent down the power supply lines at all. The processor was actually running on leakage from the logic circuits. So the low-power big thing that the ARM is most valued for today, the reason that it's on all your mobile phones, was a complete accident.

The board was faulty, the power was not actually reaching the chip, and the processor was running on the leakage current from the logic circuits. The most important characteristic of the most widespread ARM architecture on the planet — the energy efficiency that makes it suitable for mobile devices — was discovered by mistake, on a broken board, by an engineer convinced he had a faulty measuring instrument.

Furber, for his part, explained the dynamic in more engineering terms:

We applied Victorian engineering margins, and in designing to ensure it came out under a watt, we missed, and it came out under a tenth of a watt.

The “Victorian engineering margins” are the generous safety margins typical of late nineteenth-century engineering — over-dimensioning every component to avoid failures. Furber and Wilson, accustomed to designing with limited resources and no margin for error, had applied the same principle to the chip design: design for consumption under a watt, and end up well below.

There was no magic with the low power characteristics apart from simplicity.

No magic. Just a design done well by a small team that could not afford to get it wrong. On that accident, and on that simplicity, ARM's dominance in mobile for the next forty years would be built.

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A note on Sophie Wilson

Born in Leeds in 1957. She studied mathematics at Selwyn College, Cambridge, and as a student already worked with Hermann Hauser at Acorn — designing the Acorn System 1 even before graduating. In 1981, on commission from the BBC, she wrote BBC BASIC: a complete programming language in 16 kilobytes, so well-designed that it is still in use today on embedded systems. The “subtract instead of add” philosophy that would make ARM1 what it is was not born in 1985: it was born in the extreme memory constraints of the BBC Micro. Only later, in 1983, did Wilson begin work on the ARM1 instruction set, which she completed with Steve Furber in 1985. After Acorn she moved to Element 14, a 1999 spin-off absorbed by Broadcom in 2000. At Broadcom, where she still works as a Distinguished Engineer, she contributed to the BCM family of SoCs — including those that ended up inside the early Raspberry Pis, BCM2837 of the Pi 3 included. Recognition came late: Computer History Museum Fellow Award in 2012, Fellow of the Royal Society in 2013, Commander of the Order of the British Empire in 2019. In the 1990s she completed her gender transition, continuing to work in the sector without interruption.

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In 1990, Acorn, Apple and VLSI Technology founded a separate joint venture to manage and license the architecture. The name changed from Acorn RISC Machine to Advanced RISC Machines. ARM Holdings was born as an independent company, headquartered in Cambridge, with a business model that had no precedent in the sector: it would never manufacture a single chip. It would sell the idea of the chip. Licences, royalties, IP. Anyone who wanted to build an ARM processor would have to pay them.

It was a technical choice, but also a political one. ARM did not have the capital to build factories, did not have the infrastructure. But it had something harder to replicate: a clean, efficient architecture, designed well from the start.

The architecture of invisible power

ARM's business model is one of the most elegant — and least understood — in the entire technology industry. It works like this: ARM designs the processor architectures and licenses their use to third parties in exchange for an upfront fee (typically between one and ten million dollars) plus a royalty on every chip produced, usually around 1–2% of the final device price. Whoever buys the licence can then build their own chips based on that architecture, customising it within the limits allowed by the contract. They are not buying a product, then: they are buying the right to make one.

Garnsey, Lorenzoni and Ferriani, in a fundamental study on the birth of ARM as a spin-off from Acorn published in Research Policy in 2008, describe this transition as an exemplary case of techno-organizational speciation: technology is not simply transferred, but is radically transformed in the passage to a new domain through a new organisational model. ARM is not Acorn that changes its name: it is a new organism, with a completely different survival logic, which carries the original DNA but adapts to an environment Acorn could never have inhabited.

The practical result of this structure is what the industry calls neutral positioning. ARM does not compete with its customers — it does not sell chips, does not produce devices — so it can sell the same licence to Qualcomm, Apple, Samsung and MediaTek, who fight each other on the market every day. It is the “Switzerland” of silicon: a credible referee, a common infrastructure, a layer everyone builds on without having to trust the others. This has created an ecosystem of over a thousand licensee partners — a number impossible to reach for any traditional chip manufacturer. Furber, today professor of computer engineering at the University of Manchester, summed up the result in a way that is hard to forget:

I suspect there's more ARM computing power on the planet than everything else ever made put together. The numbers are just astronomical.

It is not rhetoric: it is the logical consequence of a model that multiplies adoption instead of concentrating it.

But this neutrality has a structural cost that is rarely thematised. When ARM sells a licence, it also sells dependence. Whoever builds their own SoC on ARM architecture is bound to that instruction set for the entire life of the product. Changing architecture would mean rewriting the software, recertifying the systems, redoing the chip design. The exit cost is very high. And this means that ARM, despite producing nothing, exercises enormous systemic power: it can renegotiate licence terms, raise royalties, decide who gets access to the most advanced architectures and who does not. Abstract as this dependence may sound on paper, there is a recent case that makes it very concrete — and worth following in detail, because it illustrates exactly how ARM power is exercised in the real world.

In 2021, Qualcomm acquired for $1.4 billion a Californian startup called Nuvia, founded by three former Apple Silicon engineers — Gerard Williams III, Manu Gulati, John Bruno — who were designing a server chip called Phoenix, based on the ARM v8.7-A architecture. Nuvia had its own ALA (Architecture License Agreement) with ARM, negotiated on the terms of a small startup entering a new market. When Qualcomm bought it, it integrated the Phoenix technology into its own Oryon core, the heart of the new Snapdragon X Elite — the chip with which Qualcomm wanted to challenge Intel and AMD in the AI PC laptop market.

The problem was contractual, not technical. Qualcomm's ALA with ARM already existed, and provided for lower royalties than Nuvia's. Qualcomm argued that the integration of Nuvia into its own chips fell under its pre-existing ALA. ARM replied that no: the acquisition required a full renegotiation from scratch — on ARM's terms, naturally. In 2022 ARM took Qualcomm to court asking, among other things, for the physical destruction of the pre-acquisition Nuvia designs. Not a downsizing, not a renegotiation: destruction. The message was unambiguous: IP licensing is not a sale, it is a revocable permission, and the permission is granted by whoever owns the architecture.

The case went to trial in Wilmington, Delaware, in December 2024. The jury ruled unanimously in favour of Qualcomm on two of the three contested points, hung jury on the third. On 30 September 2025, Judge Maryellen Noreika issued the final ruling: full and final judgment in favour of Qualcomm and Nuvia on all fronts, also rejecting ARM's request for a new trial. The judge explicitly noted that ARM itself, in its own internal documents, admitted to having recorded historic licensing and royalty revenues after attempting to terminate Nuvia's ALA in 2022 — which, translated, means: while claiming to have been damaged by Nuvia's actions, ARM was making piles of money precisely thanks to the ecosystem built on that architecture.

ARM has announced it will appeal. Qualcomm, for its part, already has a counter-suit open since April 2024 against ARM — accusing it of withholding technical deliverables, anti-competitive behaviour, and (in a subsequent amendment) of intending to enter the server chip market as a direct competitor. The trial, originally set for March 2026, has been postponed to October 2026 to deal with a series of pending motions — a sign that the complexity of the dispute does not exhaust itself easily. That is: ARM, which built everything on neutral positioning, finds itself accused in court of wanting to become a silicon producer. Aka: the Switzerland that suddenly wants an army.

The Qualcomm/Nuvia case is important not because Qualcomm won, but because it publicly exposed the nature of the power ARM exercises. The real asset had never been the architecture — the architecture is technical documentation, brutally, in the end. The real asset was the contract. The capacity to drag into court anyone who thinks they can use that documentation without the right permission. Langdon Winner, in his influential 1980 essay Do Artifacts Have Politics?, argued that technological choices are never neutral — they incorporate power structures, distribute access in non-random ways, create dependencies that persist long after the initial decision.

It is still true that, in a world in which human beings make and maintain artificial systems, nothing is “required” in an absolute sense. Nevertheless, once a course of action is underway, once artifacts like nuclear power plants have been built and put in operation, the kinds of reasoning that justify the adaptation of social life to technical requirements pop up as spontaneously as flowers in the spring.

And ARM is an almost perfect case of this thesis applied to the IP economy: an architecture born of a public computer-literacy project becomes the foundation on which an invisible monopoly is built across tens of billions of devices. It is not malice. It is structure. The chip has no intentions. But the licensing structure that sits on top of it, that one does.

A new front: the datacentre

A parenthesis is necessary, because it tells where ARM is going right now — and why the Qualcomm/Nuvia case has the importance it has.

For the first part of its history, ARM was the architecture of mobile. Servers, datacentres, enterprise computing were Intel territory: x86 dominated in an apparently unchallenged way. Things began to change in 2018, when Amazon Web Services announced the first Graviton, a custom ARM chip designed in-house by Annapurna Labs (acquired by AWS in 2015). The selling argument was simple and technically sound: at equivalent loads, ARM chips consumed much less energy than equivalent x86, and in a datacentre where the electricity bill is a third of operating costs, this translates directly into margin.

Since then the trajectory has been steady and surprisingly fast. In 2023 ARM accounted for about 5% of the cloud compute of the three major hyperscalers. ARM itself, in its 2025 communications, claims that by year-end approximately half of the compute shipped to the top hyperscalers will be ARM-based — a figure to be taken with the caution due to a company talking about its own market, but consistent: for the third consecutive year, more than half of new CPU capacity added to AWS is Graviton, and 98% of the top one thousand EC2 customers use it. AWS Graviton5, announced on 4 December 2025 at re:Invent, has 192 cores in a single socket, an L3 cache five times larger than the previous generation, and is based on the Neoverse V3 ARMv9.2 cores at 3 nanometres. Google has launched Axion (based on Neoverse V2) with the claim of a 65% better price-performance compared to x86 instances. Microsoft has rolled out Cobalt 100 in 29 global regions. NVIDIA — the very same NVIDIA that had tried to buy ARM — uses ARM Neoverse cores in Grace, the CPU that accompanies its H100 and B100 GPUs for AI workloads. Spotify, Paramount+, Uber, Oracle, Salesforce have migrated infrastructure to ARM. Over a billion ARM Neoverse cores have been deployed in datacentres worldwide.

This changes the proportions of the game. When ARM made money on smartphone royalties, we were talking about cents per chip but on billions of units. In datacentres things are different: every Graviton5 costs AWS thousands of dollars, and every server with an ARM chip on board is a more substantial royalty. The datacentre is the segment where ARM can finally start extracting value aggressively. And it is also the segment where licensees have most to lose: if Apple or Qualcomm raise your royalties on a phone, it is an annoyance; if ARM raises your royalties on the chip running your cloud, it is an attack on the operating margin of your business.

It is easier to understand, in this light, why Qualcomm pulled out the Nuvia case with such determination. And why — as we will see shortly — it is looking for an architectural way out.

The failed coup

November 2020. Jensen Huang, NVIDIA's CEO, announces the acquisition of ARM from SoftBank for $40 billion. It would have been the largest operation in semiconductor history. It did not go through, and understanding why helps to see how systemic ARM's position in the industry was — and still is.

Hermann Hauser, the Austrian from Cambridge who had founded Acorn, the company from which ARM was born, had reacted to the SoftBank acquisition back in July 2016 with a public statement on Twitter that left no room for interpretation:

ARM is the proudest achievement of my life. The proposed sale to SoftBank is a sad day for me and for technology in Britain.

When, four years later, NVIDIA announced its intention to buy ARM from SoftBank, Hauser's reaction was even sharper. In an interview with the BBC he explained the structural problem with a clarity that regulatory documents rarely achieve:

It's one of the fundamental assumptions of the ARM business model that it can sell to everybody. The one saving grace about Softbank was that it wasn't a chip company, and retained ARM neutrality. If it becomes part of Nvidia, most of the licensees are competitors of Nvidia, and will of course then look for an alternative to ARM.

And in his written testimony submitted to the British Parliament he added, with the freedom of someone who had nothing left to lose:

I have no shares or other interest in ARM as I had to sell them all to Softbank. I can therefore freely speak my mind.

Hauser was right. NVIDIA, in 2020, was already dominant in artificial intelligence through its GPUs. Buying ARM would have meant getting early access to new designs ahead of competitors, the ability to slow or deny licences to rivals, and benefiting freely from the architecture while others continued paying royalties. Qualcomm, Microsoft and Google publicly opposed the deal. The American FTC opened an antitrust proceeding. The European Commission launched an investigation. Britain opened its own. China raised a red flag. In February 2022, the deal was formally cancelled for significant regulatory challenges.

There is another Hauser statement worth quoting. In a 2022 interview with UKTN, he called British politicians «technologically illiterate» and «the root cause» of the governance problems around ARM. He argued that the government should have taken a golden share in ARM long before, and that any attempt to do so in 2022 was «trying to close the gate after the horse has bolted». An architecture born with public money and a public mandate had become a pawn in the power game between SoftBank, NVIDIA and the NASDAQ — because no one had thought, at the appropriate moment, that it was worth keeping it in public territory.

The end of the story: SoftBank took ARM public in September 2023, in what was the largest IPO of the year. ARM Holdings is today listed on NASDAQ with a market capitalisation of around $150 billion. Masayoshi Son is still the controlling shareholder. The fact that the acquisition attempt by the world's largest AI chip producer was blocked by regulators does not eliminate the problem — it shifts it. ARM is independent, but it is a very particular form of independence: that of a systemic infrastructure in the hands of financial investors, subject to stock-market logic, obliged to grow revenues every quarter. The uncomfortable question is: what happens when the needs of a commons architecture — stable, predictable, accessible, neutral — conflict with the needs of a publicly listed company that has to raise royalties to satisfy shareholders? It is not a theoretical question. ARM has systematically increased its licence fees in recent years. And the major licensees have started looking for alternatives.

The half-democratisation

We have to give ARM what ARM deserves, before continuing with the critique. And what it deserves is considerable.

The Raspberry Pi — version 3 in 2017, version 5 today — costs less than eighty euros for the most recent version. It is a complete computer, capable of running Linux, a server, a media centre, a network node. It exists because the ARM architecture has made it possible to produce powerful and very low-power SoCs at costs that x86 processors cannot get close to. The same principle applies to the billion-plus smartphones in the hands of people in countries where a desktop PC would be an inaccessible luxury. To the microcontrollers controlling IoT sensors at a few cents each. To the embedded processors in medical devices, industrial control systems, critical infrastructure. ARM has materially lowered the cost of access to computational hardware on a global scale.

Wilson herself, looking back on the whole story, framed it with a lucidity that almost sounds like a warning:

To build something new and complicated, it's not the sort of quick thing, it's a sustained effort over a long period of time. It takes many people's different inputs to make something unique and novel. Overnight success takes 30 years.

Thirty years of invisible work, of architectures refined chip by chip, of licences negotiated one at a time, before the world noticed that ARM was everywhere.

The “democratisation” effected by ARM is real but structurally asymmetric. It has democratised access to hardware for device manufacturers — anyone can build an ARM chip by paying the licence — but not necessarily for the end users of those devices. An iPhone — or an Android phone — has an ARM chip designed by a company, but the end user has no access to the chip's architecture, no possibility to modify it, no transparency on what runs at that level. The chip is ARM, the device is a closed box. This is the final contradiction: you may have the right — or almost — to manage the software running on an ARM chip, but below the kernel, below the bootloader, there is a chip whose architecture was defined in Cambridge, produced in Taiwan, integrated into a SoC designed by Broadcom, over which you can have no control. Sovereignty ends exactly where silicon begins. Those who really benefited are the oligopoly of large licensees — Apple, Qualcomm, Samsung, NVIDIA, Amazon with its Gravitons — not the small Bangalore startup with an idea for a specialised chip.

And yet — and here the story gets complicated, in an interesting way — within the narrow space the ARM licensing model concedes, someone is nevertheless trying to pull the lever of openness at the levels available. In December 2024, a Shenzhen company called Radxa announced the Radxa Orion O6, presented as the “World's First Open Source Arm V9 Motherboard”. It is a Mini-ITX board at $200 in the base version, based on the Cix CD8180 SoC — an ARMv9.2 chip with 12 cores (four Cortex-A720 at 2.8 GHz, four at 2.4 GHz, four Cortex-A520 at 1.8 GHz) produced by Cix Technology, a Chinese fabless founded in 2021. Debian 12, Fedora and Ubuntu run natively on it, with UEFI EDKII and SystemReady SR certification. The first Geekbench benchmarks put it at the level of an Apple M1 in single-core — not bad for an ARM board at less than a tenth of the price of a Mac mini.

*Note: it is worth clarifying what “open source” means here, because it means different things at different levels. The ARMv9.2 instruction set on which the CD8180 is built is not open: Cix pays regular royalties to ARM Holdings like all other licensees. The SoC itself is not open: it is a proprietary chip, with the NPU microcode and Mali GPU blocks all closed. What is open is the layer immediately above: board schematics, Board Support Package, EDKII bootloader, Linux kernel, device tree — all published under free licences, replicable, modifiable.*

It is also a concrete demonstration of what the open hardware movement has been arguing for twenty years: openness is layered, and opening one more layer than was open before is already a political act, even if the foundation underneath remains closed. The fact that this board comes from China — like the RISC-V pivot we will discuss shortly — is no accident: it is consistent with a geopolitical trajectory that seeks margins of technological sovereignty wherever it is possible to extract them.

The Linux moment for hardware

And here RISC-V comes onstage. And the story gets more interesting.

RISC-V was born in 2010 at the University of California Berkeley, in the same department that had helped inspire the original RISC architecture thirty years earlier. Krste Asanović and his collaborators needed a clean processor architecture for research, without having to pay licences or ask permission. They decided to design one from scratch, and to make it completely open: no royalties, no licences, no intellectual property to respect. The RISC-V instruction set is an open standard, freely published, that anyone can implement, modify, distribute.

For ten years RISC-V was an academic experiment, then a nucleus of embedded adoption, then an interesting alternative for those who wanted custom chips without paying ARM. In the last two or three years the proportions have changed. The SHD Group, a market analysis firm that has been monitoring the RISC-V sector since 2019, announced at the November 2025 RISC-V Summit that the technology's market penetration had exceeded 25% — an important symbolic threshold, even if it is to be taken with some caution. The same RISC-V International annual report for 2025 admits it is not entirely clear whether the 25% refers to the global microprocessor market in the strict sense or only to the segments where RISC-V already has a significant presence (embedded, IoT, microcontrollers). The SHD projection for 2031 is 33.7%. However it is measured, the trajectory is that of an architecture that is no longer a niche: it is the third pillar of computing, alongside x86 and ARM.

The strength of RISC-V is not just technical — it is political in the most precise sense of the term. Some examples:

The Chinese front. China has very concrete reasons not to want to depend on ARM, a company listed in New York with American shareholders. Under increasingly stringent US sanctions on advanced Intel/AMD chips, China has pivoted en masse to RISC-V — also because the RISC-V International consortium was strategically moved from Delaware to Switzerland in March 2020, formally placing it beyond the reach of unilateral American export controls. Alibaba, through its T-Head division, has released the XuanTie C920 chips and successors. Smaller Chinese manufacturers are flooding the mid-market with RISC-V AI accelerators that cost significantly less than the equivalent Western ones under sanction. It is an architectural decoupling, not just a commercial one.

The European front. The European Union, through the EU Chips Act, funds the Project DARE consortium (Digital Autonomy with RISC-V in Europe) with the explicit goal of reducing European dependence on American and British technology in critical infrastructure. Quintauris, a joint venture founded in December 2023 by Bosch, Infineon, Nordic Semiconductor, NXP and Qualcomm (with STMicroelectronics joining as a sixth shareholder in 2024), developed in 2025 RT-Europa, the first RISC-V platform for real-time automotive controllers — a sector where dependence on foreign IP had become strategically intolerable.

The Qualcomm front. In December 2025, while the Nuvia case closed yet another chapter against ARM, Qualcomm acquired Ventana Micro Systems, one of the most advanced companies in the development of high-performance RISC-V cores. Literally: not only was Qualcomm fighting ARM in court, it was also buying the way to no longer need ARM. It is the most significant move in all the recent history, because for the first time one of the major ARM licensees equips itself with a credible architectural plan B.

Three different fronts, one same direction. The parallel with Linux is more than metaphorical. Linux did not kill Windows or macOS. But it did create a real alternative that changed the terms of power in the software industry. RISC-V aspires to do the same thing for hardware. And the critical point — the one Winner would have appreciated — is that this openness is built into the architecture itself, not guaranteed by a company's good will. You cannot buy RISC-V and “close it”. The instruction set is public by definition. You can build proprietary implementations on top of it — and many companies are doing that — but the foundation remains accessible.

And here the question: will RISC-V be incorporated by capitalism exactly as Linux was? The honest answer is: probably yes, and in part it already has been. The major RISC-V implementations by Apple, Google and Meta are not open source — they use the open instruction set to build proprietary architectures. The fact that the foundation is free does not mean that everything built on top of it is. The same logic Boltanski and Chiapello described applies: critique is not defeated, it is incorporated. But at least the foundation remains open. And that counts.

Conclusions — or questions, if you prefer

ARM is born of a public mandate and a democratisation project, and becomes the foundation of a private oligopoly. The chip is the same; the power structure on top of it is radically different from the one that produced it. And that chip really did lower the entry barriers for hardware producers — it produced the Raspberry Pi, the cheap phones, the microcontrollers everywhere, the more efficient datacentres — but the democratisation stopped at the gates of the production chain. The end users of those devices gained no real sovereignty over the silicon they hold in their pocket.

NVIDIA's attempt to acquire ARM was blocked by regulators, but only because it would have concentrated power too visibly. The systemic power ARM already exercises — silently, through licences and royalties, through legal cases against those trying to step out of contractual terms — disturbs no regulator, generates no headlines, produces no parliamentary hearings. It is the kind of power that makes itself invisible precisely because it is structural: it does not lie in a decision, it lies in the conditions within which decisions are made.

There is also a contradiction that concerns me personally. That Raspberry Pi I had on the table — and all the ARM chips in the phones I have hacked for years — were already, in some sense, part of a system I did not control. I changed the software on top. I did not change the power structure underneath (one could make the same argument about Intel, ça va sans dire…). Digital sovereignty ends exactly where silicon begins, and pretending otherwise would be dishonest.

RISC-V opens a real crack. Not a revolution — a crack. The possibility that the foundation of computing be a commons, instead of private property subject to corporate decisions and legal battles. It does not solve the problem of closed hardware, it does not solve the problem of oligopolistic foundries, it does not solve any of the contradictions described. But at least it does not aggravate them. It is the same logic of the open hardware movement, which for twenty years has been trying to apply to silicon what free software has applied to code — with more modest results, because the physical layer is structurally more hostile to the commons: if you cannot open it, you do not really own it. And in a sector where every layer of the technology stack has been systematically fenced off, keeping the foundation open is a political act, not just a technical one.

What stays with me is a feeling familiar to anyone who has spent time thinking about computing as political territory. Technological choices incorporate power structures. Power structures persist long after the original choices have been forgotten. And whoever controls the basic infrastructure — the instruction set, the architecture, the licences — controls something much more important than a company: they control the rules of the game on which everything else is built.

The question I leave open is: in whose favour were these rules written? And by what right do they continue to apply?

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Sources and further reading

On the history of ARM and its origins

• Garnsey, E., Lorenzoni, G., Ferriani, S. (2008). “Speciation through entrepreneurial spin-off: The Acorn-ARM story”. Research Policy, 37(2): 210-224. doi: 10.1016/j.respol.2007.11.006. The most in-depth academic study on the origin of ARM as a spin-off from Acorn and on the genesis of its IP licensing-based business model. https://www.sciencedirect.com/science/article/abs/pii/S0048733307002363
• Patterson, D., Ditzel, D. (1980). “The Case for the Reduced Instruction Set Computer”. ACM SIGARCH Computer Architecture News, 8(6): 25-33. The founding paper of the RISC architecture at Berkeley, which inspired the ARM project. https://dl.acm.org/doi/10.1145/641914.641917

On the IP licensing business model

• Ferriani, S., Garnsey, E., Lorenzoni, G., Massa, L. (2015). “ARM plc and the IP Business Model”. Working Paper, Centre for Technology Management, University of Cambridge. https://www.ifm.eng.cam.ac.uk/uploads/Research/CTM/working_paper/2015-02-Ferriani-Garnsey-Lorenzoni-Massa.pdf
• Grindley, P. C., Teece, D. J. (1997). “Managing Intellectual Capital: Licensing and Cross-Licensing in Semiconductors and Electronics”. California Management Review, 39(2): 8-41.

On power in technological choices

• Winner, L. (1980). “Do Artifacts Have Politics?”. Daedalus, 109(1): 121-136. https://www.cc.gatech.edu/~beki/cs4001/Winner.pdf
• Boltanski, L., Chiapello, È. (1999). Le nouvel esprit du capitalisme. Gallimard. (English transl. The New Spirit of Capitalism, Verso, 2005). https://www.jstor.org/stable/4201214

On the Qualcomm/Nuvia case

• Paul, Weiss (2025). “Qualcomm Wins Decisive Post-Trial Victory in High-Profile Licensing Dispute Against Arm”. https://www.paulweiss.com/insights/client-news/qualcomm-wins-decisive-post-trial-victory-in-high-profile-licensing-dispute-against-arm. Press release of the law firm that represented Qualcomm, with summary of the 30 September 2025 ruling.
• The Register (2025). “Judge dismisses Arm's last legal claim against Qualcomm”. https://www.theregister.com/2025/10/01/arms_last_legal_claim_against/
• Computerworld (2025). “Arm's high-stakes licensing suit against Qualcomm ends in mistrial, but Qualcomm prevails in key areas”. https://www.computerworld.com/article/3629812/

On the NVIDIA acquisition attempt and geopolitical implications

• U.S. Federal Trade Commission (2021). Complaint in the Matter of NVIDIA Corporation and Arm Limited. https://www.ftc.gov/legal-library/browse/cases-proceedings/2110081-nvidia-corporationarm-limited
• Hauser, H. (2020). Written evidence submitted to the UK Parliament Business, Energy and Industrial Strategy Committee on the proposed acquisition of ARM by NVIDIA. Document BFA0018. https://committees.parliament.uk/writtenevidence/12711/pdf/
• Hauser, H. (2022). Interview with UKTN: “UK left it too late to take golden share in Arm”. https://www.uktech.news/news/government-and-policy/hermann-hauser-arm-golden-share-20220623

On Sophie Wilson, Steve Furber and the origin of ARM1

• Wilson, S. (2012). Interview with The Register: “ARM creators Sophie Wilson and Steve Furber”. https://www.theregister.com/2012/05/03/unsung_heroes_of_tech_arm_creators_sophie_wilson_and_steve_furber/. Contains Wilson's statement on low power as a complete accident.
• Furber, S. (2010). Interview with ACM Queue: “A Conversation with Steve Furber”. https://queue.acm.org/detail.cfm?id=1716385. Contains the statement on Victorian engineering margins.
• Furber, S. (2011). Interview with Communications of the ACM. https://cacm.acm.org/news/an-interview-with-steve-furber/. Contains the assessment on total ARM computing power on the planet.
• Furber, S. (2017). “ARM: The architecture that conquered mobile computing”. Philosophical Transactions of the Royal Society A, 375(2104). doi: 10.1098/rsta.2017.0148.
• Computer History Museum (2012). Fellow Award citation for Sophie Wilson and Steve Furber. https://computerhistory.org/chm-fellows/sophie-wilson/

On ARM in datacentres

• Arm Holdings (2025). “Half of the Compute Shipped to Top Hyperscalers in 2025 will be Arm-based”. Arm Newsroom. https://newsroom.arm.com/blog/half-of-compute-shipped-to-top-hyperscalers-in-2025-will-be-arm-based
• Arm Holdings (2025). “How Arm is redefining compute through the converged AI data center”. Arm Newsroom. https://newsroom.arm.com/blog/arm-converged-ai-data-center-aws-graviton5
• Omdia (2026). “Arm Steps Deeper into Silicon: Implications for the Semiconductor Value Chain”. https://omdia.tech.informa.com

On the democratisation of access to computing

• Benkler, Y. (2006). The Wealth of Networks: How Social Production Transforms Markets and Freedom. Yale University Press. http://www.benkler.org/Benkler_Wealth_Of_Networks.pdf
• Söderberg, J. (2008). Hacking Capitalism: The Free and Open Source Software Movement. Routledge. https://downloads.gvsig.org/download/people/vagazzi/Hacking%20Capitalism.pdf

On RISC-V and architectural sovereignty

• RISC-V International (2024). RISC-V Ratified Specifications. https://riscv.org/technical/specifications/
• RISC-V International (2026). Annual Report 2025. https://riscv.org/wp-content/uploads/2026/01/RISC-V-Annual-Report-2025.pdf. The official RISC-V International annual report, with the SHD Group estimate on market penetration (33.7% projected by 2031, 25% threshold reached in 2025 in some segments).
• Waterman, A., Asanović, K. (eds.) (2019). The RISC-V Instruction Set Manual. UC Berkeley Technical Report UCB/EECS-2019-103. https://riscv.org/wp-content/uploads/2019/12/riscv-spec-20191213.pdf
• Asanović, K., Patterson, D. A. (2014). “Instruction Sets Should Be Free: The Case for RISC-V”. EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2014-146.
• Center for Security and Emerging Technology (2025). “RISC-V: What it is and Why it Matters”. https://cset.georgetown.edu/article/risc-v-what-it-is-and-why-it-matters/. On the incorporation of RISC-V International in Switzerland in March 2020 and the geopolitical implications.
• Jamestown Foundation (2025). “Examining China's Grand Strategy For RISC-V”. https://jamestown.org/program/examining-chinas-grand-strategy-for-risc-v/
• The Register (2025). “Qualcomm takes RISC on Arm alternative with Ventana buy”. https://www.theregister.com/2025/12/10/qualcomm_riscv_arm_ventana/. On the acquisition of Ventana Micro Systems by Qualcomm on 10 December 2025.
• Quintauris GmbH (2023). “Five Leading Semiconductor Industry Players Incorporate New Company, Quintauris, to Drive RISC-V Ecosystem Forward”. Press release, 22 December 2023. https://www.quintauris.com

#ARM #RISCV #Semiconductors #OpenHardware #SophieWilson #DigitalSovereignty #IPLicensing #Computing #SolarPunk #FOSS

In Summary: * Lots of rain and flooded roads in and around San Antonio today. That being the case, I cancelled an appointment originally scheduled for this afternoon and rescheduled it for an afternoon late next week. Stayed home today, stayed dry, stayed safe. I've got an MLB game about ready to start now, to be followed by night prayers, then bedtime.

Prayers, etc.: * I have a daily prayer regimen I try to follow throughout the day from early morning, as soon as I roll out of bed, until head hits pillow at night. Details of that regimen are linked to my link tree, which is linked to my profile page here.

Starting Ash Wednesday, 2026, I've added this daily prayer as part of the Prayer Crusade Preceding the 2026 SSPX Episcopal Consecrations.

Health Metrics: * bw= 233.03 lbs. * bp= 143/84 (62)

Exercise: * morning stretches, balance exercises, kegel pelvic floor exercises, half squats, calf raises, wall push-ups

Diet: * 06:30 – 1 banana * 07:00 – pizza * 09:00 – 1 peanut-butter sandwich * 11:45 – beef chop suey, fried rice, soup * 17:20 – 1 fresh apple

Activities, Chores, etc.: * 05:30 – listen to local news talk radio * 06:15 – bank accounts activity monitored. * 06:40 – read, write, pray, follow news reports from various sources, surf the socials, nap. * 11:00 – listening to the Markley, van Camp and Robbins Show * 11:45 – watch old game shows and eat lunch at home with Sylvia * 13:45 – watching MLB, Cubs vs D'Backs, game in progress, Cubs leading 3 to 0, middle of the 2nd inning * 17:10 – listening to the pregame show for tonight's Rangers vs Tigers game

Chess: * 11:00 – moved in all pending CC games

I’m funemployed as of this week, but I do need to start thinking about earning some income again.

I’ve spent the last two years on an absolute rollercoaster learning an incredible amount. I’m now fluent in Elixir, in awe of the BEAM, not afraid of nix or kubernetes, and I can even read and write a little COBOL. But mostly for the past few months I’ve been experiencing the scale of what we can do when we apply advanced agentic coding practices like dark factories together with industry best-practice software engineering techniques.

My current interests are around:

• How to leverage dark factories for maximum impact, creating feedback loops to allow LLMs to converge on the solutions we want while keeping humans in the loop at the right moments.
• How the agentic moment is changing our work cultures, and how we organize ourselves and collaborate as humans as the pace of delivery accelerates, and the legibility of our work increases.

If these ideas are interesting to you too, or you’d like some help bringing them into your company, please get in touch.