JOURNAL 8 décembre 2025 Être ou ne pas être un garçon

Les choses s'éclairent maintenant nettement. Pendant 6 ans Je me suis efforcée de ressembler à ce que Je croyais que mon frère attendait de moi, et chaque progrès me renforçait dans le sentiment d'exister. Je rêvais de devenir un garçon. Un garçon ne pleure pas. Oubli des larmes, plus aucune plainte. Je ne sentais plus la douleur, les courbatures, les coups reçus parfois très durs. C’est dur le boken. Je mes suis musclée, je suis devenue hardie, décidée, bagarreuse. J’ai appris à manier la naginata, trop grande trop lourde pour moi. J'ai appris les positions les meilleures, les gestes les plus adéquats pour limiter les efforts. J'y suis arrivée. Mon caractère actuel est né dans ces années : ne jamais renoncer, ne jamais reculer, toujours faire face, trouver la faille qui permet de passer. Vers 10 ans j'étais devenue capable de tenir tête à un adulte avec n'importe quelle arme, même un simple tanto. MON FRÈRE ÉTAIT FIER DE MOI. Il m’exhibait comme preuve de son talent d'instructeur. J'étais heureuse à ma façon, comme un petit coq de combat, pas loin de me prendre pour de bon pour un garçon. J'existais pour de bon. À l'école j’avais plein de copines. J'étais épanouie et meneuse. Rien ne m'arrêtait. J'avais de très bonnes notes.

Mais jamais jamais mon père n'a donné le moindre signe d'intérêt

Puis j'ai été confiée à mon oncle pédophile, et ça a commencé à dérailler. L'intérêt que lui et sa femme me portaient était certes la preuve de mon existence, mais mon esprit était troublé, j'existais comme une fille. J'appliquais à ce nouveau mode ce que javais acquis : pas de plainte, pas de protestation. Je me conformais à ce qu'on attendait de moi mais dans un trouble qui allait grandissant. Le viol filmé a été un choc terrible. J'ai fait une sévère dépression. J’en suis sortie au bout d'un an et là j'ai éclaté : toute ces pressions, tous ces efforts pour ça ? La digue s’est rompue. Je me suis révoltée avec toute la puissance de mes seize ans, 10 ans de silence. 10 ans d'efforts énormes pour forger une image de conformité, pour être exactement le personnage désiré. Scandale public. Internement au hokkaidô dans cette secte, ce que j'ai déjà assez raconté.

Ce soir Je me sens libre et éclairée. En face de moi au kotatsu mon amour me sourit, ses yeux bleus plongent dans les miens et y lisent la paix qui m'habite enfin. Jeudi j'irai à l'hôpital. Je dirai à mes médecins merci vous m'avez aidée au moment où j'avais besoin d’un coup de pouce extérieur pour me lancer sur la piste, et voilà j'ai trouvé la porte de sortie. Je ne reviendrai pas. Merci encore infiniment (profonds saluts). Au revoir.

#NSFW

This post is NSFW 19+ Adult content. Viewer discretion is advised.

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In Connection With This Post: The Vagina as the Second Face .01 https://write.as/hustin/the-vagina-as-the-second-face-01

In the AV·BJ scene, for adult performers who reveal their vaginas, the vagina emerges as a self-possessed subject rather than an object. They render their vaginas as publicly legible as their faces. Within this world, the vagina appears as routinely as a face—it is the performer herself enacting a public claim to vaginal subjectivity.

It is an unconscious modality of corporeal resistance, liberating what was once concealed by social regulation and capitalist repression. In practice, vulva close-ups in AV·BJ function equivalently to facial close-ups: they transmit emotion. The vagina becomes a bearer of essence, presence, selfhood, subjectivity, authenticity, identity and bodily dignity—a site where her other face, her SECOND FACE, is inscribed.

From the perspective of film/video studies, the vagina frequently orchestrates the movement and narrative architecture of the frame. In adult BJ broadcasting and first-person POV AV, the camera follows the will of the vagina’s owner rather than directorial instruction. Metaphorically, a vaginal close-up becomes a mode of self-inscribed cinema authored by the performer herself. The vagina is not merely a filmed object but the protagonist of the scene—the element that leads and organizes the narrative. What governs the video is not an external cameraman but the vagina itself as the decisive—the anatomical axis—key frame. It operates as a commanding, narrative-driving agent within the media environment.

In front of the camera, the vagina is no longer an object; it is the most unmediated speaking subject and the center of the gaze that objectifies the viewer. When the camera zooms in on the vagina, the gaze originates from the vagina itself, and the viewer becomes the one who receives that gaze. Viewers respond to this gaze by masturbating, posting praise in the comments, and sending monetary support. The bidirectional economy formed between the pussy and its many spectators offers ordinary women an immediate, transparent, and appealing reward system for pussy performance. The convergence of modern technologies—close-up capability, narrative framing, and economic interactivity—transforms the vagina into a subject. This marks a radical inversion of the gaze economy and a reallocation of sexual agency.

In Connection With This Post:

#AdultBJ #PornAesthetics #VaginalArt #VulvaPerformance #VaginalTheory #SexualExpression

Porque intentamos ser profundos o superficiales cuando la examinamos, no vemos la vida con claridad.

A coal touched his lips, and a warning touched the world.

ISAIAH — VISION AT THE TEMPLE

NARRATOR

In the year that King Uzziah died, I saw Jehovah sitting on a lofty and elevated throne, and the skirts of his robe filled the temple.
Seraphs were standing above him; each had six wings. Each covered his face with two and covered his feet with two, and each of them would fly about with two.

SERAPHIM — CALLING TO ONE ANOTHER

“Holy, holy, holy is Jehovah of armies.
The whole earth is filled with his glory.”

NARRATOR

And the pivots of the thresholds quivered at the sound of the shouting,
and the house was filled with smoke.
Then I said:

ISAIAH

“Woe to me!
I am as good as dead,
For I am a man of unclean lips,
And I live among a people of unclean lips;
For my eyes have seen the King, Jehovah of armies himself!”

NARRATOR

At that, one of the seraphs flew to me, and in his hand was a glowing coal that he had taken with tongs from the altar.
He touched my mouth and said:

SERAPH

“Look! This has touched your lips.
Your guilt is removed,
And your sin is atoned for.”

NARRATOR

Then I heard the voice of Jehovah saying:

JEHOVAH

“Whom shall I send, and who will go for us?”

ISAIAH

“Here I am! Send me!”

JEHOVAH

“Go, and say to this people:
‘You will hear again and again,
But you will not understand;
You will see again and again,
But you will not get any knowledge.’

Make the heart of this people unreceptive,
Make their ears unresponsive,
And paste their eyes together,
So that they may not see with their eyes
And hear with their ears,
So that their heart may not understand
And they may not turn back and be healed.”

ISAIAH

“How long, O Jehovah?”

JEHOVAH

“Until the cities crash in ruins without an inhabitant
And the houses are without people
And the land is ruined and desolate;
Until Jehovah removes men far away
And the deserted condition of the land becomes very extensive.

But there will still be a tenth in it,
And it will again be burned,
Like a big tree and like an oak,
Which after they are cut down leave a stump;
A holy seed will be its stump.”

---

ISAIAH — THE SIGN TO AHAZ

NARRATOR

Now in the days of Ahaz son of Jotham son of Uzziah, the king of Judah, King Rezin of Syria and Pekah son of Remaliah, the king of Israel, came up to wage war against Jerusalem, but he could not capture it.
A report was made to the house of David:

MESSENGER

“Syria has joined forces with Ephraim.”

NARRATOR

And the heart of Ahaz and the heart of his people began to tremble, like the trees of the forest shaking in the wind.
Jehovah then said to Isaiah:

JEHOVAH

“Go out, please, to meet Ahaz, you and your son Shear-jashub, at the end of the conduit of the upper pool by the highway of the laundryman’s field.

You must say to him:
‘Take care to stay calm.
Do not be afraid, and do not lose heart because of these two stumps of smoldering logs, because of the hot anger of Rezin and Syria and the son of Remaliah.

For Syria with Ephraim and the son of Remaliah have plotted harm against you, saying:
‘Let us go up against Judah and tear it apart and conquer it for ourselves, and let us appoint the son of Tabeel as its king.’”

JEHOVAH — CONTINUING

“This is what the Sovereign Lord Jehovah says:
It will not succeed,
Nor will it take place.

For the head of Syria is Damascus,
And the head of Damascus is Rezin.

Within just 65 years
Ephraim will be completely shattered and cease to be a people.

The head of Ephraim is Samaria,
And the head of Samaria is the son of Remaliah.

Unless you have firm faith,
You will not be firmly established.”

NARRATOR

Jehovah continued speaking to Ahaz:

JEHOVAH

“Ask for a sign from Jehovah your God;
it may be as deep as the Grave or as high as the sky.”

AHAZ

“I will not ask, nor will I put Jehovah to the test.”

ISAIAH

“Listen, please, O house of David.
Is it not enough that you try the patience of men?
Must you also try the patience of God?

Therefore, Jehovah himself will give you a sign:
Look! The young woman will become pregnant and will give birth to a son,
and she will name him Immanuel.

He will eat butter and honey by the time that he knows how to reject the bad and choose the good.

For before the boy knows how to reject the bad and choose the good, the land of the two kings whom you dread will be completely abandoned.

Jehovah will bring against you and against your people and against the house of your father a time such as has not come since the day Ephraim broke away from Judah, for He will bring the king of Assyria.”

NARRATOR

In that day Jehovah will whistle for the flies from the distant streams of the Nile of Egypt and for the bees in the land of Assyria,
and they will all come and settle down on the steep valleys, on the rocky clefts, on all the thornbushes, and on all the watering places.

In that day by means of a hired razor from the region of the River,
by means of the king of Assyria,
Jehovah will shave the head and the hair of the legs,
and it will sweep away the beard as well.

In that day a man will keep alive a young cow of the herd and two sheep.
And because of the abundance of milk, he will eat butter,
for everyone remaining in the land will eat butter and honey.

In that day wherever there used to be a thousand vines worth a thousand pieces of silver,
there will be only thornbushes and weeds.

Men will go there with bow and arrow, because all the land will become thornbushes and weeds.

And all the mountains that used to be cleared with a hoe,
you will not go near for fear of thornbushes and weeds;
they will become a grazing place for bulls
and a trampling ground of sheep.

---

ISAIAH 8 — THE CHILD AS A SIGN

JEHOVAH TO ISAIAH

“Take a large tablet and write on it with an ordinary stylus,
‘Maher-shalal-hash-baz.’

And let me have it confirmed in writing
by faithful witnesses, Uriah the priest and Zechariah the son of Jeberechiah.”

NARRATOR

Then I had relations with the prophetess, and she became pregnant
and in time gave birth to a son.

Jehovah then said to me:

JEHOVAH

“Name him Maher-shalal-hash-baz,
for before the boy knows how to call out, ‘My father!’ and ‘My mother!’
the resources of Damascus and the spoil of Samaria will be carried away before the king of Assyria.”

NARRATOR

Jehovah spoke to me again:

JEHOVAH

“Because this people has rejected the gently flowing waters of the Shiloah
and they rejoice over Rezin and the son of Remaliah,

Therefore look! Jehovah will bring against them
the mighty and vast waters of the River,
the king of Assyria and all his glory.

He will come up over all his streambeds
and overflow all his banks,
and sweep through Judah.

He will flood and pass through, reaching to the neck;
his outspread wings will fill the breadth of your land,
O Immanuel!”

NARRATOR — PROPHETIC CALL TO NATIONS

Cause harm, you peoples, but you will be shattered to pieces.
Listen, all you from distant parts of the earth!

Prepare for battle, but you will be shattered to pieces.
Prepare for battle, but you will be shattered to pieces.

Devise a plan, but it will be thwarted.
Say what you like, but it will not succeed,
For God is with us.

JEHOVAH — WARNING TO ISAIAH

With his strong hand on me, this is what Jehovah said to warn me away from following the course of this people:

“You should not call a conspiracy what this people calls a conspiracy.
Do not fear what they fear;
Do not tremble at it.

Jehovah of armies — he is the One you should regard as holy.
He is the One you should fear,
And he is the One who should cause you to tremble.”

NARRATOR

He will become as a sanctuary,
but as a stone to strike against
and as a rock to stumble over
to both houses of Israel,
as a trap and a snare
to the inhabitants of Jerusalem.

Many of them will stumble and fall and be broken;
they will be ensnared and caught.

“Wrap up the written confirmation;
seal up the law among my disciples!

I will keep in expectation of Jehovah,
who is hiding his face from the house of Jacob,
and I will hope in him.

Look! I and the children whom Jehovah has given me
are as signs and as miracles in Israel
from Jehovah of armies, who resides on Mount Zion.”

NARRATOR — AGAINST FALSE GUIDANCE

And if they say to you:
“Inquire of the spirit mediums or of the fortune-tellers who chirp and mutter,”
is it not of their God that a people should inquire?

Should they inquire of the dead in behalf of the living?

Instead, they should inquire of the law
and of the written confirmation.

When they do not speak according to this word,
they have no light.

And each one will pass through the land afflicted and hungry;
and because he is hungry and indignant,
he will curse his king and his God as he looks upward.

Then he will look to the earth
and see only distress and darkness,
obscurity and hard times,
gloom and no brightness.

---

#bible #isaiah #reading

Last night I was so exhausted I gave up on journaling or gratitude. It’s going to hurt with E gone for so long. I try not to think about it but I’m afraid.

And we should ignore the alarm bells.

These companies want us to anthropomorphize their software, so let's indulge in that fantasy. What type of person ends up like this? By tracing LLM companies, with all their opportunities and outcomes, over a person's life path, it paints a pretty tropey picture.

I came up with this analogy while trying to unpack what’s going on here to my wife. It started to feel less like market analysis and more like gossiping about “that” person from high school. We all have “that” person in our lives. LLMs are like “them”, but supercharged.

They’re like that wealthy kid who used their influence to bypass every normal social control and bully their way into situations where they were not welcome or qualified to be, and all while being able to wave away any accountability.

School Life

Starting right at the beginning, one of the first impacts of LLMs was how they were a corrupting influence in schools, serving as a bad universal-calculator and slot-machine that allowed students to fake assignments with ease.

This quickly spiraled into a culture of apathy for large segments of the student population. The result? Widespread and effortless short-cutting of learning outcomes has killed any faith many students and educators had in the current system. And the messaging by LLM boosters did not help.

Kids are not blind to the realities of the working world and they do not have a lot to look forward to. Why bother learning when the machine already “knows” every answer.

LLMs also went up to higher education and almost destroyed the institutions altogether. And not just for students, but for educators and administrators as well.

A foundation of higher learning is academic honesty through the avoidance of plagiarism and use of proper citation. !Tenets! that LLM companies were allowed to freely flaunt, and the loss of that institutional trust has cascaded through society. Generated assignments, briefs and answers. Generated lesson plans. Generated assessments. Generated applications and automated reviews thereof. Textbooks. Studies. Quotes.

The point of a university degree is now being questioned, given how unstable the landscape is. It doesn’t exactly help when you have so many people who still need to pay off their tuition fees but are actively looking for a job.

Because of LLM-fueled layoffs.

I can't imagine starting college in the middle of Lockdown and watching the future you were promised just evaporate away as you get closer to graduation.

The cherry on top of the crap cake that is AI Education is that it hasn't been proven to create better learning comprehension in students yet. It hasn’t been in use or studied long enough to prove any outcomes.

Anyone who truly understands education will tell you that delivering answers is a secondary outcome.

The value of education stems from the process of creating the answers. For instance, finding your voice in writing essays, correcting weaknesses through assessments, discovering fields of interest through safe engagement environments. It is all about creating those neural frameworks to work through math, science, geography and every other discipline; then interweaving those processes in individualistic ways to form unique but still factual ideas. But the most important part is collaborating with people in building the social skills and structures needed to achieve a collective good. Knowing how and when to push your points, compromise and concede for the greater good.

I'm not going to pretend that global education frameworks don't fall short by becoming increasingly outcomes and metrics based. Some first-world nations are decades behind on tech adoption and are not equipping students for the realities of modern life. But I don't think LLMs are any better.

Because the technology is so new in schools and industry, there is no structure or method to its implementation. Hell, most people don't even know what it’s for. I've writing a bloody novel about this and can’t really tell you what it’s for.

It's too early to determine the long- term outcomes of using this tech has on students and their performance. However, in this same short time there have been ample indications that it is detrimental to people’s abilities to meet current standards.

It's plain to see how inaccurate these tools have been and how caustic they are to cognitive ability and critical thinking skills, especially in children.

Working World

In spite of the dumpster fire they have made of education, LLMs have started to infiltrate the working world.

All of a sudden, AI was dumped front and center of every workflow. Software that was not intentionally selected by the user, that cannot be turned off or configured, that sends unknown amounts of data to unknown processes over the internet. Software that generates erroneous data that could easily disrupt business processes.

Is there a name for software like that? Or is it essentially just a virus?

Regardless, everyone was given a set of free incompetent interns. This massive technological development was swiftly met with... confusion? Resignation? Apathy?

I don't think anyone knows how to feel about it, because the interns are technically “free”.

But they aren’t particularly good at anything. They don’t even learn and improve as advertised. They just need to be babysat constantly.

The biggest impact is informal applications such as a web search replacement and a compiler and summarizer of emails.

There are people who have found a place for language models in a workflow as a sounding board or brainstorming tool. Fair enough, but I don't think many people can argue that they are mission critical, and I'm curious about how much people are willing to spend on that.

I wouldn't be surprised if the bulk of LLM usage was in HR and the bullshit hiring merry-go-rounds. LLM job boards and recruiters, LLM-written cover letters and resumes, LLMs doing all the screening of those applicants, LLM interviews and assessments, LLM rejection letters. The lynchpin of a valueless, circular business process. (I love how this industry rhymes with itself.)

And what about Vibe Code

Vibe Coding. Vibe Coding. Vibe. Code. The AI industry’s lone use case shining like a beacon in the maelstrom. What would I be allowed to say about Vibe Code as a washed-out, failed developer who hasn't touched production code in a decade...?

That is its own uninformed industry issue.

But I can confidently say that I might have been too hard on Agile being the worst thing to happen to computers.

Back to work

When LLMs climbed the ladder and made it for corporate consideration, they were fast-tracked right up to the top and... let’s just say that the 95% failure study is fairly well circulated at this point.

And I’m talking about the actual study detailing that companies need to identify specific goals and outcomes that demand use of this specific technology, while also having a clear plan on how to achieve it and hold the vendors accountable to their promises and commitments.

Not the many “interpretations” that insist that the solution is more AI spend, training and adoption to overcome the problems caused by poor AI spending, training and adoption.

Organizations that successfully cross the GenAI Divide approach AI procurement differently, acting more like BPO clients than SaaS customers. They demand deep customization, drive adoption from the frontlines, and hold vendors accountable to business metrics. The most successful buyers understand that crossing the divide requires partnership, not just purchase.

The sense I’m getting is that corporate AI initiatives are just gambling – as if AI is piloting the last helicopter out of the tech boom, and there are only a few seats left to become the next Facebook or Google.

There's a sense of urgency to put all your money on a one-trick pony. Just like how a “growth-minded” CEO will start with an inflated salary and stock options and a bonus structure and a golden parachute before the business even makes its first profit because it's not like corporates have anything else to spend that money on.

Would you trust people like this?

We all know people like this.

Someone who looks the part and we are assured can do the job by people paid to say so.

People who are given every opportunity and incentive to succeed simply because they had every opportunity and incentive to succeed. The type of person that can confidently absorb all praise and reward from success while effortlessly passing along the cost and consequence of failure. After all, they could pay to be where they are.

Money talks. It speaks volumes. Loud enough to create its own narrative and drown out critics.

But money doesn't actually do anything. It's just a fancy battery. A storage of potential energy.

AI very often just wastes that potential and then demands more.

There's nothing wrong with messing up, even at seemingly monumental scales. That’s why we have checks, structures and standards. Barriers that keep customers and companies safe by filtering the potential for mistakes. Barriers that you overcome with results. Success, even in spite of potential limitations.

But why, for LLMs, do we constantly ignore and even reward failure? Virtue by scope of potential, even in spite of repeat failures.

Every opportunity and easy win just gone up in smoke. Ignore the lawsuits. The artistic endeavors booed by audiences. The high-profile blunders. The rollbacks and broken rules. Just slide it all under the rug and let it fail upwards until the creators are eating dinner with the president and “sponsoring” his inauguration and ballroom for no particular reason.

The best part is that LLMs are not just the embodiment of incompetence. This is Incompetence as a Service. An enforced service, to be more precise.

They didn't mess up just one school or company. No no. They are in a position to screw with all of them. When I said above that they were forced everywhere, it was not just software. Fridges and toasters. Toys and light-switches. This list grows by the day.

If the apocalypse happens because of “AI”, it will most likely be because of a mistake, not malice. Maybe Microsoft pushes an LLM-written patch that screws up a math library. Or the LLM summary of a critical email misunderstands basic facts.

Microsoft is part way to developing an “Agentic Operating System” based on LLMs that feels as if it was programmed by LLM. People are starting to notice and their patience is wearing thin. The head of Windows knows this.

The team (and I) take in a ton of feedback. We balance what we see in our product feedback systems with what we hear directly. They don’t always match, but both are important. I've read through the comments and see focus on things like reliability, performance, ease of use and more. But I want to spend a moment just on the point you are making, and I’ll boil it down, we care deeply about developers. We know we have work to do on the experience, both on the everyday usability, from inconsistent dialogs to power user experiences. When we meet as a team, we discuss these paint points and others in detail, because we want developers to choose Windows. We know words aren’t enough, it’s on us to continue improving and shipping. Would love to connect with you about what the team is doing to address these areas if you are open to it.

It sounds like cutesy corporate talk to do better, but it's not some theoretical PR exercise. We're at the point where users can't trust an operating system, developers can't trust their platform, and power users do not know how to service the product.

That's how you kill a company. But what makes this situation far worse is that we have a running theme of concentrated influence., because that suicidal company has a finger in almost everything and can take it all down with them. The worst part is that it seems like every person, organization, and government is powerless to prevent this insanity from causing more harm.

“You can't stifle innovation.”

“We're acting in shareholder interests.”

“We need to stop other people from making the bad AI.”

“If we stop spending money, then there's no economy because everything is scary right now without any real growth markets; but we need to show profit and growth otherwise capitalism will get angry and will smite us with a plague of bears.”

“I'm going to tell Donald Trump and he'll add you to the naughty list and tariff you if you don't play nice with his special friends.”

So whats the point?

Everyone I've run this project past asks the same things.

Why are you creating this? Who is it for? Do we even need this? Do you have a plan for what this looks like? Why should anyone care, as it's not as if you've got a profile or public reputation for success? Shouldn't you be fixing the prices on the online store? Do you hate the economy?

And they’re all perfectly fair and valid. I've put you through five thousand words and that's a lot of reading in a doom scroll world.

Or, perhaps you're just skimming to the end looking for a tl,dr, in which case. TLDR: Hi. You just missed some long overdue but measured cathartic decompression. We're going to be adults now.

I'll answer the above with a question that burns in my soul: Why the fuck do we not ask the AI companies these questions too? At worst, I'm just wasting some of your time and you could simply stop whenever you want and be just fine. Hell, I'm the only one out of pocket here.

Sorry, still had some left in the tank.

I wanted to create something by exploiting a gap in the market and offering real value – only to then realize that there is no value to be found.

As for the question of who we're writing for, this project is for the growing number of people who know something is wrong but can't articulate what or why. This part probably deserves its own rant and it feels very justified to do so right now. I'm writing this revision after NVIDA’s very weird earnings report where the good(?) numbers did not stem the dip they have been seeing through November.

My guess is that it may have something to do with “Who is OpenAI’s auditor?” trending on the day and I also saw “Cisco 01” in the linkmap. Why are we being visited by The Ghost of Bubbles Past?

There's also the question of why a company would have so much riding on quarterly reports. It can't be healthy or responsible to require positive outlooks every reporting period.

Regardless, the doubt is now outweighing the hype, but people lack the understanding and language to describe what is going on. I said that modern education has not equipped students for the modern technology landscape. This industry preys on the victims of this failure, and it’s just so hard to communicate a precise perspective about this because emotion, deep technical knowledge, personal principals and history make a very unappealing cocktail. It's why I’ve moved some of the denser stuff to their own sections.

But at the same time, it appears that companies are all in on AI initiatives. The job cut numbers are no secret. The scope is likely in line with most other technology revolutions like automation, globalization, digitization and the subsequent global networking of those tools. But unlike other revolutions that have rolled out over years of incremental experimentation, discovery, development and competition; AI is an out-the-box leap.

We are starting with the conclusion that there WILL BE efficiency gains. There WILL BE infinite scale. There WILL BE a net good for humanity. We’re working from a speculative outcome. Making a gamble.

I'm personally doing this because I enjoy doing business. I started looking into this new industry because, like a lot of people, I wanted to get in on the ground floor. People skipped out on the internet and mobile and social media and every big thing because it seemed to have been the smart choice. Now it feels as if we can't afford to be smart and might as well put all our eggs in this blender.

I will be the first to admit that I do not understand every single factor of this technology. I do not know the right way to do this. There's a lot going on, and this little rant was simply a way of saying that people are not crazy for seeing so many problems that have been snowballing for years. All I could do was learn and I was lucky to have just enough background knowledge and experience to no be completely lost.

Other people can’t say or do the same.

And the foundational knowledge is not even scratching the surface of what is happening.

I didn't even mention the military technology, the psychosis issue, the data centers and the questionable procurement of datasets, or how the tech even works.

Did we ever define AI? Or just the Intelligence part?

We should really start there.

We were super stoked at After Happy Hour when we finally started being able to pay our contributors. It wasn't much at first—just a $10 token payment per contributor, which for us felt just on the good side of not insulting but still seemed manageable if we didn't bring in much revenue that reading period. What we found, though, was that once we started paying contributors our revenue went up, too. More people were willing to pay for expedited submissions, or throw us a few bucks as a tip jar submission, and we also started selling more print issues. All together, that meant we were able to increase our pay rates within just a couple years to where they are now. 

Currently, After Happy Hour pays contributors $2.50 per issue page, with a minimum of $15 and a maximum of $50 per work. Functionally, this means we end up paying $15 per poem or work of art, with prose writers getting $15-$50 depending on the length of their work. That puts us into semi-pro territory for art and poetry, and we perch on the border between token and semi-pro payment for fiction and creative nonfiction depending on the length of the work. 

For context of what I mean by these terms, I'm basing them off of Duotrope's classification system, which essentially reflects the industry standard. They break markets into 4 pay categories:

• Non-paying – No monetary compensation for contributors
• Token payment – Pays less than .01/word for fiction or creative nonfiction, less than $5 per poem,  or less than $10 per work of art
• Semi-pro Payment – Pays .01-.05/word for fiction or creative nonfiction, $5-$49 per poem, or $10-$49 per work of art
• Professional payment – Pays over .05/word for fiction or creative nonfiction, $50 or more per poem, or $50 or more per work of art

I was curious, both as an editor and a submitter, about where After Happy Hour falls in the broader literary landscape in terms of our payment structure. So I decided to scrounge up some data and crunch some numbers to get a sense for what pay rates are across the literary journal world. And since I figured I'm not the only person who might find this info helpful, I put that data into some pie charts and decided to make a post about it. 

All the data used in this post came from Duotrope. I used the Advanced Search for Publishers feature with contests excluded and temporarily closed markets included, so while it's not a fully comprehensive picture of the short fiction and poetry publishing landscape, it covers the majority of markets that are out there.

I should also note that when it gives an acceptance ratio, that's based on the user-reported stats on Duotrope. That means it's not necessarily completely accurate to what would show up on the editors' back-end for those markets since not every submission gets reported on Duotrope. That said, typically the real acceptance percentage will be lower than what gets reported on market databases, so something that's in the “under 10% acceptance percentage” category on Duotrope is most likely still in that subset of markets IRL.

On to the data!

Pay rates for short fiction publishers

Duotrope categorizes short fiction publishers according to the length of what they publish, which means that flash fiction (up to 1,000) is a separate category than short fiction (1,000-7,500). I started off by looking at each of these categories for both print and electronic formats to get a broad overview:

This confirmed a suspicion I had: you're slightly more likely to get paid by a print publication than an online one when it comes to short fiction. It was also a bit surprising to me, though, that the percentage of markets offering professional publication are about the same for flash as for longer short stories. I would have thought more markets would end up in semi-pro or pro territory for flash work, just since they're shorter. Instead, it seems to be the opposite. I imagine this is because more of the non-paying markets have a lower word count cut-off and that balances out the markets that pay a flat honorarium regardless of work, which would be the situation where a market would end up potentially paying pro rates for flash but semi-pro or even token for a longer piece (e.g. a $50 per story policy, which would be considered “pro” for a story up to 1,000 words, semi-pro for a 1,001-5,000 word story, and “token” for one that's 5,001+).

I had another suspicion based on my experience as a submitter: that the percentage of paying markets for genre fiction is higher than for literary or general publications. Here's what the data showed when I restricted the search to just fantasy or sci-fi:

I would say these numbers partially confirmed my suspicions, though there were also some surprises. The biggest for me was the disparity between pay rates for sci-fi and fantasy—I had thought those would be nearly identical, but it seems as if there are more non-paying publishers in fantasy than there are in sci-fi. Thinking through why this might be, I suspect it's because fantasy is a broader genre and there are simply more markets that publish it compared to the slightly more limited category of sci-fi.

In either case, though, across both short stories and flash, the odds of being paid are higher in the genres than across all markets in general. Considering those sci-fi and fantasy publishers were also included in that overall stat, by extension we can infer that the percentage that pay for straight literary work are lower than what's presented here as the overall figures (since the genre-only publishers are giving the stats a wee boost). 

The big picture takeaway here: you're the most likely to at least be paid something in a print sci-fi magazine, while fantasy has a broader spread, with slightly more non-paying markets as well as the highest percentage of markets paying pro rates across both print and electronic formats. 

I also thought it would be interesting to break things down by acceptance percentage. Again, I had a suspicion going into this, which was that the markets with the lowest acceptance ratios would also be most likely to pay. So I started with Duotrope’s list of the 100 Most Approachable Fiction Markets (the ones with the highest acceptance percentages):

Then I shifted over to the markets whose reported acceptance percentage is 10% or lower, which is the rough cutoff point in my mind for what you might consider a “mid-list” publication:

Then I took that down to 5% or lower, which is where I mentally put my cutoff for “upper-tier” publications:

Then I took it down one more step, to a 1% acceptance ratio, which is generally my cutoff for an “elite” journal:

And finally I looked at the journals that appear on Duotrope's 100 Most Challenging Fiction Markets:

…I will say I was surprised by how similar the distribution was across the 10%, 5%, and 1% acceptance markets. I sort of assumed that the percentage that pay would gradually go up as the percentage of submissions accepted decreases. From the 100 Most Challenging breakdown, it’s clear that the majority of markets at the very top do pay (and typically quite well), but it seems that shift happens at a lower acceptance percentage threshold than 1%.

Something else I was curious about was whether you’re more likely to get paid from submitting to journals that have a submission fee. And, oddly enough, it actually seems like it’s the opposite:

…which I feel like is representative of a deeper ill among certain types of literary publishers, and a topic that could warrant its own future blog post. Especially considering that over half of all journals with a 1% or lower acceptance percentage that require payment to submit don’t pay their writers. Considering the sheer number of submissions they must receive to have an acceptance percentage that low, it really makes you wonder exactly where all of that money is going if not back to the authors.

Pay rates for poetry publishers

I took the same approach to start with journals that publish poetry as with the fiction markets, breaking it down by electronic versus print publications:

…this seemed to confirm a suspicion I had coming into my research: a smaller percentage of poetry markets pay compared to fiction markets. Checking out the numbers for Duotrope’s 100 Most Approachable Markets seemed to double down on this:

…but then I switched over to the markets with a 10% or lower acceptance rate, and the ratios started to look more familiar:

When you get up to the very top, then the balance shifts and poetry markets are again markedly less likely to pay contributors than fiction ones:

…but when you’re looking at the mid-range markets, all the way up through the lower end of “top tier” territory, the difference in pay rates between poetry and fiction publishers is minor. The biggest difference seems to be that there are fewer in the “token” pay range, which makes sense. For poetry, that’s something that pays but less than $5 per poem, which honestly gets down into the level where it’s almost not even worth it to send the payment for a single poem, depending on how you do it.

The other main difference I saw with the poetry markets was with how submission fees impacted the percentages:

The difference is more pronounced when you take a broader view across mid-range and top-tier markets, which makes sense to an extent. A lot of those 1% or less acceptance journals have such a reputation that a lot of people will pay to submit to them for the prestige of potentially getting published there, even if they don’t pay (not that I think that’s fair, but I can see the thought process of submitters). But at least the majority of poetry publishers that charge submission fees send at least some of that money back to writers, which is heartening.

So what’s it all mean?

I think there are heartening and disheartening takeaways from this data. On the positive side, there are definitely plenty of markets out there that are compensating writers well for the words they write, and not all of them are white whales (although the whales are, on the whole, the most likely to pay professional rates). 

The most disturbing insight, to me, is the fact that charging submission fees without paying writers has become such a widespread practice. I suppose I had naively assumed it was something reserved to a few university affiliated literary journals, but these numbers suggest that's not the case. As the editor of a literary journal, I completely get that publications need to do something to keep the lights on, but if it's writers financing said lights it only seems fair to me that they stand to see some kind of benefit from that if their work is published. 

I would be curious to dig deeper into some of these stats, and see how pay ranges break down based on factors like whether the journal is university affiliated or what year it was founded. But this at least gives a big-picture overview of how lit mags are paying writers, and hopefully it's interesting and/or useful for other folks out there. 

See similar posts:

#Submissions #ShortStory #Poetry #PublishingAdvice

In Summary: * On the upside, was able to spend an hour and a half doing yard work this afternoon, mowing and collecting leaves off the front yard. Totally wore me out, but at least the front yard looks better now.

On the downside, our washing machine broke. It won't drain or spin, it's locked up. Luckily I spoke to stepson in the Philippines who repairs such things. He explained to me what was wrong and how to fix it. It involves pulling the darned thing away from the wall and removing the back panel to start, and he explained what to look for and what to do next, etc. Dang, wish he was here instead of over there on the other side of the flippin' planet!

Prayers, etc.: * My daily prayers

Health Metrics: * bw= 218.48 lbs. * bp= 123/77 (71)

Exercise: * kegel pelvic floor exercise, half squats, calf raises, wall push-ups

Diet: * 08:00 – 1 peanut butter sandwich * 08:45 – 1 fresh orange * 11:00 – baked fish and vegetables * 14:50 – baked chicken, mashed potatoes, baked beans

Activities, Chores, etc.: * 07:55 – bank accounts activity monitored * 08:00 – read, pray, follow news reports from various sources, surf the socials * 13:00 to 14:30 – mow and collect front yard leaves * 14:50 – watch old game shows and eat lunch at home with Sylvia * 16:00 – read, pray, follow news reports from various sources, surf the socials * 19:45 – listening to relaxing music and quietly reading until bedtime

Chess: * 12:20 – moved in all pending CC games

The artificial intelligence industry stands at a crossroads. On one side, proprietary giants like OpenAI, Google, and Anthropic guard their model weights and training methodologies with the fervour of medieval warlords protecting castle secrets. On the other, a sprawling, chaotic, surprisingly powerful open-source movement is mounting an insurgency that threatens to democratise the most transformative technology since the internet itself.

The question isn't merely academic. It's existential for the future of AI: Can community-driven open-source infrastructure genuinely rival the proprietary stacks that currently dominate production-grade artificial intelligence? And perhaps more importantly, what governance structures and business models will ensure these open alternatives remain sustainable, safe, and equitably accessible to everyone, not just Silicon Valley elites?

The answer, as it turns out, is both more complex and more hopeful than you might expect.

Open Source Closes the Gap

For years, the conventional wisdom held that open-source AI would perpetually trail behind closed alternatives. Proprietary models like GPT-4 and Claude dominated benchmarks, whilst open alternatives struggled to keep pace. That narrative has fundamentally shifted.

Meta's release of LLaMA models has catalysed a transformation in the open-source AI landscape. The numbers tell a compelling story: Meta's LLaMA family has achieved more than 1.2 billion downloads as of late 2024, with models being downloaded an average of one million times per day since the first release in February 2023. The open-source community has published over 85,000 LLaMA derivatives on Hugging Face alone, an increase of more than five times since the start of 2024.

The performance gap has narrowed dramatically. Code LLaMA with additional fine-tuning managed to beat GPT-4 in the HumanEval programming benchmark. LLaMA 2-70B and GPT-4 achieved near human-level performance of 84 per cent accuracy on fact-checking tasks. When comparing LLaMA 3.3 70B with GPT-4o, the open-source model remains highly competitive, especially when considering factors like cost, customisation, and deployment flexibility.

Mistral AI, a French startup that raised $645 million at a $6.2 billion valuation in June 2024, has demonstrated that open-source models can compete at the highest levels. Their Mixtral 8x7B model outperforms the 70 billion-parameter LLaMA 2 on most benchmarks with six times faster inference, and also outpaces OpenAI's GPT-3.5 on most metrics. Distributed under the Apache 2.0 licence, it can be used commercially for free.

The ecosystem has matured rapidly. Production-grade open-source frameworks now span every layer of the AI stack. LangChain supports both synchronous and asynchronous workflows suitable for production pipelines. SuperAGI is designed as a production-ready framework with extensibility at its core, featuring a graphical interface combined with support for multiple tools, memory systems, and APIs that enable developers to prototype and scale agents with ease.

Managed platforms are emerging to bridge the gap between open-source potential and enterprise readiness. Cake, which raised $10 million in seed funding from Google's Gradient Ventures in December 2024, integrates the various layers that constitute the AI stack into a more digestible, production-ready format suitable for business. The Finnish company Aiven offers managed open-source data infrastructure, making it easier to deploy production-grade AI systems.

When Free Isn't Actually Free

Here's where the open-source narrative gets complicated. Whilst LLaMA models are free to download, the infrastructure required to run them at production scale is anything but.

The economics are sobering. Training, fine-tuning, and running inference at scale consume expensive GPU resources that can often easily exceed any licensing fees incurred for proprietary technology. Infrastructure costs masquerade as simple compute and storage line items until you're hit with unexpected scaling requirements, with proof-of-concept setups often falling apart when handling real traffic patterns.

Developers can run inference on LLaMA 3.1 at roughly 50 per cent the cost of using closed models like GPT-4o, according to industry analysis. However, gross margins for AI companies average 50 to 60 per cent compared to 80 to 90 per cent for traditional software-as-a-service businesses, with 67 per cent of AI startups reporting that infrastructure costs are their number one constraint to growth.

The infrastructure arms race is staggering. Nvidia's data centre revenue surged by 279 per cent year-over-year, reaching $14.5 billion in the third quarter of 2023, primarily driven by demand for large language model training. Some projections suggest infrastructure spending could reach $3 trillion to $4 trillion over the next ten years.

This creates a paradox: open-source models democratise access to AI capabilities, but the infrastructure required to utilise them remains concentrated in the hands of cloud giants. Spot instances can reduce costs by 60 to 80 per cent for interruptible training workloads, but navigating this landscape requires sophisticated technical expertise.

Monetisation Models

If open-source AI infrastructure is to rival proprietary alternatives, it needs sustainable business models. The community has experimented with various approaches, with mixed results.

The Hugging Face Model

Hugging Face, valued at $4.5 billion in a Series D funding round led by Salesforce in August 2023, has pioneered a hybrid approach. Whilst strongly championing open-source AI and encouraging collaboration amongst developers, it maintains a hybrid model. The core infrastructure and some enterprise features remain proprietary, whilst the most valuable assets, the vast collection of user-contributed models and datasets, are entirely open source.

The CEO has emphasised that “finding a profitable, sustainable business model that doesn't prevent us from doing open source and sharing most of the platform for free was important for us to be able to deliver to the community.” Investors include Google, Amazon, Nvidia, AMD, Intel, IBM, and Qualcomm, demonstrating confidence that the model can scale.

The Stability AI Rollercoaster

Stability AI's journey offers both warnings and hope. The creator of Stable Diffusion combines open-source model distribution with commercial API services and enterprise licensing, releasing model weights under permissive licences whilst generating revenue through hosted API access, premium features, and enterprise support.

Without a clear revenue model initially, financial health deteriorated rapidly, mounting $100 million in debts coupled with $300 million in future obligations. However, in December 2024, new CEO Prem Akkaraju reported the company was growing at triple-digit rates and had eliminated its debt, with continued expansion expected into film, television, and large-scale enterprise integrations in 2025. The turnaround demonstrates that open-source AI companies can find sustainable revenue streams, but the path is treacherous.

The Red Hat Playbook

Red Hat's approach to open-source monetisation, refined over decades with Linux, offers a proven template. Red Hat OpenShift AI provides enterprise-grade support, lifecycle management, and intellectual property indemnification. This model works because enterprises value reliability, support, and indemnification over raw access to technology, paying substantial premiums for guaranteed uptime, professional services, and someone to call when things break.

Emerging Hybrid Models

The market is experimenting with increasingly sophisticated hybrid approaches. Consumption-based pricing has emerged as a natural fit for AI-plus-software-as-a-service products that perform work instead of merely supporting it. Hybrid models work especially well for enterprise AI APIs where customers want predictable base costs with the ability to scale token consumption based on business growth.

Some companies are experimenting with outcome-based pricing. Intercom abandoned traditional per-seat pricing for a per-resolution model, charging $0.99 per AI-resolved conversation instead of $39 per support agent, aligning revenue directly with value delivered.

Avoiding the Tragedy of the Digital Commons

For open-source AI infrastructure to succeed long-term, it requires governance structures that balance innovation with safety, inclusivity with direction, and openness with sustainability.

The Apache Way

The Apache Software Foundation employs a meritocratic governance model that fosters balanced, democratic decision-making through community consensus. As a Delaware-based membership corporation and IRS-registered 501©(3) non-profit, the ASF is governed by corporate bylaws, with membership electing a board of directors which sets corporate policy and appoints officers.

Apache projects span from the flagship Apache HTTP project to more recent initiatives encompassing AI and machine learning, big data, cloud computing, financial technology, geospatial, Internet of Things, and search. For machine learning governance specifically, Apache Atlas Type System can be used to define new types, capturing machine learning entities and processes as Atlas metadata objects, with relationships visualised in end-to-end lineage flow. This addresses key governance needs: visibility, model explainability, interpretability, and reproducibility.

EleutherAI's Grassroots Non-Profit Research

EleutherAI represents a different governance model entirely. The grassroots non-profit artificial intelligence research group formed in a Discord server in July 2020 by Connor Leahy, Sid Black, and Leo Gao to organise a replication of GPT-3. In early 2023, it formally incorporated as the EleutherAI Institute, a non-profit research institute.

Researchers from EleutherAI open-sourced GPT-NeoX-20B, a 20-billion-parameter natural language processing AI model similar to GPT-3, which was the largest open-source language model in the world at the time of its release in February 2022.

Part of EleutherAI's motivation is their belief that open access to such models is necessary for advancing research in the field. According to founder Connor Leahy, they believe “the benefits of having an open source model of this size and quality available for that research outweigh the risks.”

Gary Marcus, a cognitive scientist and noted critic of deep learning companies such as OpenAI and DeepMind, has repeatedly praised EleutherAI's dedication to open-source and transparent research. Maximilian Gahntz, a senior policy researcher at the Mozilla Foundation, applauded EleutherAI's efforts to give more researchers the ability to audit and assess AI technology.

Mozilla Common Voice

Mozilla's Common Voice project demonstrates how community governance can work for AI datasets. Common Voice is the most diverse open voice dataset in the world, a crowdsourcing project to create a free and open speech corpus. As part of their commitment to helping make voice technologies more accessible, they release a cost and copyright-free dataset of multilingual voice clips and associated text data under a CC0 licence.

The dataset has grown to a staggering 31,841 hours with 20,789 community-validated hours of speech data across 129 languages. The project is supported by volunteers who record sample sentences with a microphone and review recordings of other users.

The governance structure includes advisory committees consulted for decision-making, especially in cases of conflict. Whether or not a change is made to the dataset is decided based on a prioritisation matrix, where the cost-benefit ratio is weighed in relation to the public interest. Transparency is ensured through a community forum, a blog and the publication of decisions, creating a participatory and deliberative decision-making process overall.

Policy and Regulatory Developments

Governance doesn't exist in a vacuum. In December 2024, a report from the House Bipartisan Task Force called for federal investments in open-source AI research at the National Science Foundation, National Institute of Standards and Technology, and the Department of Energy to strengthen AI model security, governance, and privacy protections. The report emphasised taking a risk-based approach that would monitor potential harms over time whilst sustaining open development.

California introduced SB-1047 in early 2024, proposing liability measures requiring AI developers to certify their models posed no potential harm, but Governor Gavin Newsom vetoed the measure in September 2024, citing concerns that the bill's language was too imprecise and risked stifling innovation.

At the international level, the Centre for Data Innovation facilitated a dialogue on addressing risks in open-source AI with international experts at a workshop in Beijing on 10 to 11 December 2024, developing a statement on how to enhance international collaboration to improve open-source AI safety and security. At the AI Seoul Summit in May 2024, sixteen companies made a public commitment to release risk thresholds and mitigation frameworks by the next summit in France.

The Open Source Initiative and Open Future released a white paper titled “Data Governance in Open Source AI: Enabling Responsible and Systematic Access” following a global co-design process and a two-day workshop held in Paris in October 2024.

The Open Safety Question

Critics of open-source AI frequently raise safety concerns. If anyone can download and run powerful models, what prevents malicious actors from fine-tuning them for harmful purposes? The debate is fierce and far from settled.

The Safety-Through-Transparency Argument

EleutherAI and similar organisations argue that open access enables better safety research. As Connor Leahy noted, EleutherAI believes “AI safety is massively important for society to tackle today, and hope that open access to cutting edge models will allow more such research to be done on state of the art systems.”

The logic runs that closed systems create security through obscurity, which historically fails. Open systems allow the broader research community to identify vulnerabilities, test edge cases, and develop mitigation strategies. The diversity of perspectives examining open models may catch issues that homogeneous corporate teams miss.

Anthropic, which positions itself as safety-focused, takes a different approach. Incorporated as a Delaware public-benefit corporation, Anthropic brands itself as “a safety and research-focused company with the goal of building systems that people can rely on and generating research about the opportunities and risks of AI.”

Their Constitutional AI approach trains language models like Claude to be harmless and helpful without relying on extensive human feedback. Anthropic has published constitutional principles relating to avoiding harmful responses, including bias and profanity, avoiding responses that would reveal personal information, avoiding responses regarding illicit acts, avoiding manipulation, and encouraging honesty and helpfulness.

Notably, Anthropic generally doesn't publish capabilities work because they do not wish to advance the rate of AI capabilities progress, taking a cautious stance that contrasts sharply with the open-source philosophy. The company brings in over $2 billion in annualised revenue, with investors including Amazon at $8 billion, Google at $2 billion, and Menlo Ventures at $750 million.

Empirical Safety Records

The empirical evidence on safety is mixed. Open-source models have not, to date, caused catastrophic harms at a scale beyond what proprietary models have enabled. Both open and closed models can be misused for generating misinformation, creating deepfakes, or automating cyberattacks. The difference lies less in the models themselves and more in the surrounding ecosystem, moderation policies, and user education.

Safety researchers are developing open-source tools for responsible AI. Anthropic released Petri, an open-source auditing tool to accelerate AI safety research, demonstrating that even closed-model companies recognise the value of open tooling for safety evaluation.

The Global South Challenge

Perhaps the most compelling argument for open-source AI infrastructure is equitable access. Proprietary models concentrate power and capability in wealthy nations and well-funded organisations. Open-source models theoretically democratise access, but theory and practice diverge significantly. The safety debate connects directly to this challenge: if powerful AI remains locked behind proprietary walls, developing nations face not just technical barriers, but fundamental power asymmetries in shaping the technology's future.

The Promise of Democratisation

Open-source AI innovation enables collaboration across borders, allows emerging economies to avoid technological redundancy, and creates a platform for equitable participation in the AI era. Open-source approaches allow countries to avoid expensive licensing, making technology more accessible for resource-constrained environments.

Innovators across the Global South are applying AI solutions to local problems, with open-source models offering advantages in adapting to local cultures and languages whilst preventing vendor lock-in. According to industry analysis, 89 per cent of AI-using organisations incorporate open-source tools in some capacity, driven largely by cost considerations, with 75 per cent of small businesses turning to open-source AI for cost-effective solutions.

The Centre for Strategic and International Studies notes that open-source models create opportunities for AI innovation in the Global South amid geostrategic competition, potentially reducing dependence on technology from major powers.

The Infrastructure Reality

Despite these advantages, significant barriers remain. In the Global South, access to powerful GPUs and fast, stable internet is limited, leading some observers to call the trend “algorithmic colonialism.”

The statistics are stark. According to research on African contexts, only 1 per cent of Zindi Africa data scientists have on-premises access to GPUs, whilst 4 per cent pay for cloud access worth $1,000 per month. Despite apparent progress, the resources required to utilise open-access AI are still not within arm's reach in many African contexts.

The paradox is cruel: open-source models are freely available, but the computational infrastructure to use them remains concentrated in data centres controlled by American and Chinese tech giants. Downloading LLaMA costs nothing; spinning up enough GPU instances to fine-tune it for a local language costs thousands of dollars per hour.

Bridging the Gap

Some initiatives attempt to bridge this divide. Open-source tools for managing GPU infrastructure include DeepOps, an open-source toolkit designed for deploying and managing GPU clusters that automates the deployment of Kubernetes and Slurm clusters with GPU support. Kubeflow, an open-source machine learning toolkit for Kubernetes, streamlines end-to-end machine learning workflows with GPU acceleration.

Spot instances and per-second billing from some cloud providers make short training runs, inference jobs, and bursty workloads more cost-efficient, potentially lowering barriers. However, navigating these options requires technical sophistication that many organisations in developing countries lack.

International collaboration efforts are emerging. The December 2024 workshop in Beijing brought together international experts to develop frameworks for enhancing collaboration on open-source AI safety and security, potentially creating more equitable participation structures.

The Production-Grade Reality Check

For all the promise of open-source AI, the question remains whether it can truly match proprietary alternatives for production deployments at enterprise scale.

Where Open Source Excels

Open-source infrastructure demonstrably excels in several domains. Customisation and control allow organisations to fine-tune models for specific use cases, languages, or domains without being constrained by API limitations. Companies like Spotify use LLaMA to help deliver contextualised recommendations to boost artist discovery, combining LLaMA's broad world knowledge with Spotify's expertise in audio content. LinkedIn found that LLaMA achieved comparable or better quality compared to state-of-the-art commercial foundational models at significantly lower costs and latencies.

Cost optimisation at scale becomes possible when organisations have the expertise to manage infrastructure efficiently. Whilst upfront costs are higher, amortised over millions of API calls, self-hosted open-source models can be substantially cheaper than proprietary alternatives.

Data sovereignty and privacy concerns drive many organisations to prefer on-premises or private cloud deployments of open-source models, avoiding the need to send sensitive data to third-party APIs. This is particularly important for healthcare, finance, and government applications.

Where Proprietary Holds Edges

Proprietary platforms maintain advantages in specific areas. Frontier capabilities often appear first in closed models. GPT-4 generally outperforms LLaMA 3 70B across benchmarks, particularly in areas like common knowledge and grade school maths, logical reasoning and code generation for certain tasks.

Ease of use and integration matter enormously for organisations without deep AI expertise. Proprietary APIs offer simple integration, comprehensive documentation, and managed services that reduce operational overhead. According to industry surveys, 72 per cent of enterprises use an API to access their models, with over half using models hosted by their cloud service provider.

Reliability and support carry weight in production environments. Enterprise contracts with proprietary vendors typically include service-level agreements, guaranteed uptime, professional support, and liability protection that open-source alternatives struggle to match without additional commercial layers.

The Hybrid Future

The emerging pattern suggests that the future isn't binary. Global enterprise spending on AI applications has increased eightfold over the last year to close to $5 billion, though it still represents less than 1 per cent of total software application spending. Organisations increasingly adopt hybrid strategies: proprietary APIs for tasks requiring frontier capabilities or rapid deployment, and open-source infrastructure for customised, cost-sensitive, or privacy-critical applications.

The Sustainability Question

Can open-source AI infrastructure sustain itself long-term? The track record of open-source software offers both encouragement and caution.

Learning from Linux

Linux transformed from a hobbyist project to the backbone of the internet, cloud computing, and Android. The success stemmed from robust governance through the Linux Foundation, sustainable funding through corporate sponsorships, and clear value propositions for both individual contributors and corporate backers.

The Linux model demonstrates that open-source infrastructure can not only survive but thrive, becoming more robust and ubiquitous than proprietary alternatives. However, Linux benefited from timing, network effects, and the relatively lower costs of software development compared to training frontier AI models.

The AI Sustainability Challenge

AI infrastructure faces unique sustainability challenges. The computational costs of training large models create barriers that software development doesn't face. A talented developer can contribute to Linux with a laptop and internet connection. Contributing to frontier AI model development requires access to GPU clusters costing millions of dollars.

This asymmetry concentrates power in organisations with substantial resources, whether academic institutions, well-funded non-profits like EleutherAI, or companies like Meta and Mistral AI that have raised hundreds of millions in venture funding.

Funding Models That Work

Several funding models show promise for sustaining open-source AI:

Corporate-backed open source, exemplified by Meta's LLaMA releases, allows companies to commoditise complementary goods whilst building ecosystems around their platforms. Mark Zuckerberg positioned LLaMA 3.1 as transformative, stating “I believe the Llama 3.1 release will be an inflection point in the industry where most developers begin to primarily use open source.”

Academic and research institution leadership, demonstrated by EleutherAI and university labs, sustains fundamental research that may not have immediate commercial applications but advances the field.

Foundation and non-profit models, like the Apache Software Foundation and Mozilla Foundation, provide neutral governance and long-term stewardship independent of any single company's interests.

Commercial open-source companies like Hugging Face, Mistral AI, and Stability AI develop sustainable businesses whilst contributing back to the commons, though balancing commercial imperatives with community values remains challenging.

Where We Stand

So can community-driven open-source infrastructure rival proprietary stacks for production-grade AI? The evidence suggests a nuanced answer: yes, but with important caveats.

Open-source AI has demonstrably closed the performance gap for many applications. Models like LLaMA 3.3 70B and Mixtral 8x7B compete with or exceed GPT-3.5 and approach GPT-4 in various benchmarks. For organisations with appropriate expertise and infrastructure, open-source solutions offer compelling advantages in cost, customisation, privacy, and strategic flexibility.

However, the infrastructure requirements create a two-tiered system. Well-resourced organisations with technical talent can leverage open-source AI effectively, potentially at lower long-term costs than proprietary alternatives. Smaller organisations, those in developing countries, or teams without deep machine learning expertise face steeper barriers.

Governance and business models are evolving rapidly. Hybrid approaches combining open-source model weights with commercial services, support, and hosting show promise for sustainability. Foundation-based governance like Apache and community-driven models like Mozilla Common Voice demonstrate paths toward accountability and inclusivity.

Safety remains an active debate rather than a settled question. Both open and closed approaches carry risks and benefits. The empirical record suggests that open-source models haven't created catastrophic harms beyond those possible with proprietary alternatives, whilst potentially enabling broader safety research.

Equitable access requires more than open model weights. It demands investments in computational infrastructure, education, and capacity building in underserved regions. Without addressing these bottlenecks, open-source AI risks being open in name only.

The future likely involves coexistence and hybridisation rather than the triumph of one paradigm over another. Different use cases, organisational contexts, and regulatory environments will favour different approaches. The vibrant competition between open and closed models benefits everyone, driving innovation, reducing costs, and expanding capabilities faster than either approach could alone.

Meta's strategic bet on open source, Mistral AI's rapid ascent, Hugging Face's ecosystem play, and the steady contribution of organisations like EleutherAI and Mozilla collectively demonstrate that open-source AI infrastructure can absolutely rival proprietary alternatives, provided the community solves the intertwined challenges of governance, sustainability, safety, and genuine equitable access.

The insurgency isn't just mounting a challenge. In many ways, it's already won specific battles, claiming significant territory in the AI landscape. Whether the ultimate victory favours openness, closure, or some hybrid configuration will depend on choices made by developers, companies, policymakers, and communities over the coming years.

One thing is certain: the community-driven open-source movement has irrevocably changed the game, ensuring that artificial intelligence won't be controlled exclusively by a handful of corporations. Whether that partial accessibility evolves into truly universal access remains the defining challenge of the next phase of the AI revolution.

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References and Sources

1. GitHub Blog. (2024). “2024 GitHub Accelerator: Meet the 11 projects shaping open source AI.” Available at: https://github.blog/news-insights/company-news/2024-github-accelerator-meet-the-11-projects-shaping-open-source-ai/

2. TechCrunch. (2024). “Google's Gradient backs Cake, a managed open source AI infrastructure platform.” Available at: https://techcrunch.com/2024/12/04/googles-gradient-backs-cake-a-managed-open-source-ai-infrastructure-platform/

3. Acquired.fm. (2024). “Building the Open Source AI Revolution with Hugging Face CEO, Clem Delangue.” Available at: https://www.acquired.fm/episodes/building-the-open-source-ai-revolution-with-hugging-face-ceo-clem-delangue

4. Meta AI Blog. (2024). “The future of AI: Built with Llama.” Available at: https://ai.meta.com/blog/future-of-ai-built-with-llama/

5. Meta AI Blog. (2024). “Introducing Llama 3.1: Our most capable models to date.” Available at: https://ai.meta.com/blog/meta-llama-3-1/

6. Meta AI Blog. (2024). “With 10x growth since 2023, Llama is the leading engine of AI innovation.” Available at: https://ai.meta.com/blog/llama-usage-doubled-may-through-july-2024/

7. About Meta. (2024). “Open Source AI is the Path Forward.” Available at: https://about.fb.com/news/2024/07/open-source-ai-is-the-path-forward/

8. McKinsey & Company. (2024). “Evolving models and monetization strategies in the new AI SaaS era.” Available at: https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/upgrading-software-business-models-to-thrive-in-the-ai-era

9. Andreessen Horowitz. (2024). “16 Changes to the Way Enterprises Are Building and Buying Generative AI.” Available at: https://a16z.com/generative-ai-enterprise-2024/

10. FourWeekMBA. “How Does Stability AI Make Money? Stability AI Business Model Analysis.” Available at: https://fourweekmba.com/how-does-stability-ai-make-money/

11. VentureBeat. (2024). “Stable Diffusion creator Stability AI raises $101M funding to accelerate open-source AI.” Available at: https://venturebeat.com/ai/stable-diffusion-creator-stability-ai-raises-101m-funding-to-accelerate-open-source-ai

12. AI Media House. (2024). “Stability AI Fights Back from Collapse to Dominate Generative AI Again.” Available at: https://aimmediahouse.com/ai-startups/stability-ai-fights-back-from-collapse-to-dominate-generative-ai-again

13. Wikipedia. “Mistral AI.” Available at: https://en.wikipedia.org/wiki/Mistral_AI

14. IBM Newsroom. (2024). “IBM Announces Availability of Open-Source Mistral AI Model on watsonx.” Available at: https://newsroom.ibm.com/2024-02-29-IBM-Announces-Availability-of-Open-Source-Mistral-AI-Model-on-watsonx

15. EleutherAI Blog. (2022). “Announcing GPT-NeoX-20B.” Available at: https://blog.eleuther.ai/announcing-20b/

16. Wikipedia. “EleutherAI.” Available at: https://en.wikipedia.org/wiki/EleutherAI

17. InfoQ. (2022). “EleutherAI Open-Sources 20 Billion Parameter AI Language Model GPT-NeoX-20B.” Available at: https://www.infoq.com/news/2022/04/eleutherai-gpt-neox/

18. Red Hat. “Red Hat OpenShift AI.” Available at: https://www.redhat.com/en/products/ai/openshift-ai

19. CSIS. (2024). “An Open Door: AI Innovation in the Global South amid Geostrategic Competition.” Available at: https://www.csis.org/analysis/open-door-ai-innovation-global-south-amid-geostrategic-competition

20. AI for Developing Countries Forum. “AI Patents: Open Source vs. Closed Source – Strategic Choices for Developing Countries.” Available at: https://aifod.org/ai-patents-open-source-vs-closed-source-strategic-choices-for-developing-countries/

21. Linux Foundation. “Open Source AI Is Powering a More Inclusive Digital Economy across APEC Economies.” Available at: https://www.linuxfoundation.org/blog/open-source-ai-is-powering-a-more-inclusive-digital-economy-across-apec-economies

22. Stanford Social Innovation Review. “How to Make AI Equitable in the Global South.” Available at: https://ssir.org/articles/entry/equitable-ai-in-the-global-south

23. Brookings Institution. “Is open-access AI the great safety equalizer for African countries?” Available at: https://www.brookings.edu/articles/is-open-access-ai-the-great-safety-equalizer-for-african-countries/

24. Apache Software Foundation. “A Primer on ASF Governance.” Available at: https://www.apache.org/foundation/governance/

25. Mozilla Foundation. “Common Voice.” Available at: https://www.mozillafoundation.org/en/common-voice/

26. Mozilla Foundation. (2024). “Common Voice 18 Dataset Release.” Available at: https://www.mozillafoundation.org/en/blog/common-voice-18-dataset-release/

27. Wikipedia. “Common Voice.” Available at: https://en.wikipedia.org/wiki/Common_Voice

28. Linux Insider. (2024). “Open-Source Experts' 2024 Outlook for AI, Security, Sustainability.” Available at: https://www.linuxinsider.com/story/open-source-experts-2024-outlook-for-ai-security-sustainability-177250.html

29. Center for Data Innovation. (2024). “Statement on Enhancing International Collaboration on Open-Source AI Safety.” Available at: https://datainnovation.org/2024/12/statement-on-enhancing-international-collaboration-on-open-source-ai-safety/

30. Open Source Initiative. (2024). “Data Governance in Open Source AI.” Available at: https://opensource.org/data-governance-open-source-ai

31. Wikipedia. “Anthropic.” Available at: https://en.wikipedia.org/wiki/Anthropic

32. Anthropic. “Core Views on AI Safety: When, Why, What, and How.” Available at: https://www.anthropic.com/news/core-views-on-ai-safety

33. Anthropic. “Petri: An open-source auditing tool to accelerate AI safety research.” Available at: https://www.anthropic.com/research/petri-open-source-auditing

34. TechTarget. (2024). “Free isn't cheap: How open source AI drains compute budgets.” Available at: https://www.techtarget.com/searchcio/feature/How-open-source-AI-drains-compute-budgets

35. Neev Cloud. “Open Source Tools for Managing Cloud GPU Infrastructure.” Available at: https://blog.neevcloud.com/open-source-tools-for-managing-cloud-gpu-infrastructure

36. RunPod. (2025). “Top 12 Cloud GPU Providers for AI and Machine Learning in 2025.” Available at: https://www.runpod.io/articles/guides/top-cloud-gpu-providers

37. CIO Dive. “Nvidia CEO praises open-source AI as enterprises deploy GPU servers.” Available at: https://www.ciodive.com/news/nvidia-revenue-gpu-servers-open-source-ai/758897/

38. Netguru. “Llama vs GPT: Comparing Open-Source Versus Closed-Source AI Development.” Available at: https://www.netguru.com/blog/gpt-4-vs-llama-2

39. Codesmith. “Meta Llama 2 vs. OpenAI GPT-4: A Comparative Analysis of an Open Source vs Proprietary LLM.” Available at: https://www.codesmith.io/blog/meta-llama-2-vs-openai-gpt-4-a-comparative-analysis-of-an-open-source-vs-proprietary-llm

40. Prompt Engineering. “How Does Llama-2 Compare to GPT-4/3.5 and Other AI Language Models.” Available at: https://promptengineering.org/how-does-llama-2-compare-to-gpt-and-other-ai-language-models/

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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

Today, I’m writing not because I have something substantially meaningful to tell the world. Because the reality is that even if I had anything like that on my mind, no one reads this journal anyway. So, what’s the difference? But right now I’m desperate for the process, not the outcome.

I always want to write more. I think about that daily, but I rarely have ideas beyond race reports and other bike-related stuff, which can get old even to myself. And on top of that, I also have a history of writing some stupid crap and then having the audacity to post it for an audience broad enough to learn the lesson. What’s the lesson? Being more self-critical, I suppose. So, I figured, I’ll write about why today is so special. For a moment, I feel like I can overcome the fear of oversharing.

Our small town got its first substantial snowfall of the season. It’s always special. Even if it’s already the beginning of December in the Ski Country, and we haven’t started the winter season yet. So yeah, anticipation would be too weak a word to describe the situation. So, when I told my friend that I had to plow the driveway three times today, I wasn’t complaining. I was bragging about this cozy attribute of rural life.

And once you come back inside, it just makes sense to make a coffee, get a blanket, grab a notebook, and write a story. Fortunately, modern MacBooks fit into this setting just as well as a Moleskine would do. So, I’d go with that.

The story is about time. Not the time that has been carved out of the daily cycle of work, family, and training. But the one that has been forcefully given. The true offseason. Only a week ago, the weather around here was so unusually pleasant that I would’ve rather jumped on my bike and gotten lost for a couple of hours. A few weeks from now, if in the same situation, I’d perhaps throw my twigs into the trunk and go hit the slopes. But right here, right now, I can’t do shit. Well, I tried running, but that was so embarrassing I didn’t even post it on Strava. And, in a nutshell, what I wanna say about this time is that I’m wholeheartedly grateful for it! Praised be the boredom.

The roses...

It’s like clipping a junkie to a heating radiator. Same concept and similar outcomes. Detox for the body that tends to be in a permanent state of exhaustion. Reflection for the mind that is otherwise too obsessed with performance right now, or tomorrow, or at the race next weekend. The only difference is that after everything is said and done, a junkie-me goes straight back to his dopamine dealer. Because it’s not a cure, I don’t want to be cured. But it’s a welcome medicine to keep the “bad habits” sustainable. It feels weird calling a physically active lifestyle bad, even taken in quotes, but in the context of an imposed recovery, it’s a “too much of a good thing” kind of situation that I’m talking about.

Training-wise, I’m not in a full OFF-mode either. After a short break for friends and family on Thanksgiving week, I'm already back to training. But now, being free from any self-imposed commitments, I can switch things up (or worse) to no regret. And somehow it feels like fun for a moment, and not like an endless, daunting grind.

... and the thorns

It’s not all pink ponies and sparkles. Self-reflection ruthlessly reveals everything, and the dark side found its way out.

Even though Mt Herman Rd begins pretty much in my backyard, in the years prior, I’d ride it up maybe 3 or 4 times a year. In 2025, I did that climb too many times to count. Sometimes it’s a necessary effort to earn the turns. But it’s not always that way. And when I got there once again in the middle of October, one of the fellow HS coaches asked me what I was finding up there. Serenity, I replied, sincerely. But the nature of serenity implies solitude, doesn't it?

Overabundance, when applied to the things you love the most, can be a curse in disguise. As calm and peaceful as it is, loneliness can be painful too. And it hurts the most when you pause numbing it, willfully or not, and admit its existence.

There are moments in life when God does not ease us into faith. He throws us into it. He does not whisper growth. He commands it through storms, loss, hunger, fear, and impossible situations that demand more than comfort Christianity can offer. Matthew 14 is one of those chapters. It is not gentle. It is not neat. It is not safe. It is raw, disruptive, confrontational, and breathtaking. This chapter is where easy belief dies and living faith is born.

Matthew 14 opens not with a miracle, but with a murder. It opens with pain before power, injustice before wonder, cruelty before compassion. It opens with the beheading of John the Baptist. This matters more than most people realize, because John was not just a prophet to Jesus—he was family, forerunner, and friend. And now, at the whim of a drunken king and the manipulation of a bitter woman, he is gone. No trial. No defense. No divine rescue. Just silence… and a platter.

Herod’s conscience was already screaming, but fear made him cruel. He wanted approval. He wanted to save face. He wanted to look powerful in front of guests. And in trying to preserve his image, he destroyed a righteous life. This is one of Scripture’s clearest reminders that cowardice kills just as surely as malice. Herod did not hate John. He feared him. He admired him. And that made John dangerous. So when pressure came, Herod chose popularity over truth and lost his soul in the process.

When Jesus hears this, He does not preach. He does not confront Herod. He withdraws. He grieves. He steps away to be alone. This is one of the most tender moments in the entire Gospel—because the Son of God, who will soon raise the dead and command seas, still steps away to mourn. Jesus shows us here that grief is not weakness. Solitude is not lack of faith. Withdrawal is sometimes holy.

But the crowds do not let Him be alone.

They follow Him into the wilderness.

And instead of sending them away, He heals them.

This is where the emotional depth of Jesus becomes unmistakable. He is grieving. He is exhausted. He has just lost someone He loved violently. And still, when suffering people find Him, He does not shut down. He does not recoil. He becomes compassion itself. This is the Christ so many people miss—the Christ who bleeds privately but loves publicly at the same time.

As evening comes, the disciples panic. There is no food. No resources. No supplies. Thousands of people. Empty hands. Limited wallets. And that familiar anxious logic kicks in: “Send the people away.” In other words, this problem is too big for us. It is inconvenient. It is unsafe. It is financially impossible. It is logistically absurd.

But Jesus responds with one sentence that changes the entire meaning of ministry and faith:

“They do not need to go away. You give them something to eat.”

In one line, Jesus shifts responsibility from heaven to human hands. Not because the disciples are sufficient, but because He is about to show them what happens when human insufficiency is placed into divine hands. They bring Him what they have: five loaves and two fish. It is laughable against the size of the need. They are embarrassed by its smallness. But Jesus is never offended by small beginnings. He blesses it. He breaks it. And suddenly, what was never enough becomes more than enough.

Twelve baskets left over.

Twelve.

The same number as the doubting disciples who thought it could not be done.

God always leaves leftovers to confront our unbelief.

But the chapter isn’t done. The real test of faith hasn’t arrived yet. The miracle of provision feeds the crowd. But the miracle of trust will feed the disciples.

That night, Jesus sends them back into the boat and tells them to cross the sea without Him. This is important. He sends them directly into a storm without His visible presence. They obey. They row. The wind rises. The waves grow violent. And for hours, they fight with everything they have. Exhaustion sets in. Fear begins eating at reason. Strength drains. And then, just before dawn—when they are at the breaking point—they see something walking on the water toward them.

They do not say, “It’s Jesus.”

They scream.

Terror distorts faith before it strengthens it.

Jesus speaks into the storm with words that are still doing work in the human soul two thousand years later:

“Take courage. It is I. Do not be afraid.”

Peter answers, not with confidence, but with trembling courage. He does not demand rescue. He asks permission:

“Lord, if it is You, call me to You.”

And Jesus speaks a single word that still defines discipleship:

“Come.”

That word is not comfort. It is confrontation. It is an invitation into impossibility. It is an invitation to leave what is sinking for what cannot be seen. And Peter, shaking, uncertain, terrified, steps out anyway.

For one brief, miraculous moment, a man weighs no more than faith.

Then reality crashes back in. Wind. Waves. Fear. Eyes leave Jesus. Focus shifts to chaos. And Peter begins to sink. The same water that held him moments earlier now swallows him. And he cries out the shortest prayer in Scripture:

“Lord, save me.”

And immediately—immediately—Jesus reaches out and catches him.

Not after Peter explains himself.

Not after he apologizes.

Not after he proves anything.

Immediately.

Jesus does not rescue perfection. He rescues surrender.

Then they get back into the boat together, and the storm stops. The disciples fall on their faces and finally speak words they have never spoken so clearly before:

“Truly You are the Son of God.”

Not because of the feeding.

Not because of the walking.

Not even because of the storm itself.

But because of the rescue.

The chapter ends with healing again. Everyone who touched the fringe of His garment was made whole. Not the strong. Not the important. Not the qualified. The ones who merely reached.

Matthew 14 does not teach how to avoid storms. It teaches how to walk through them with Christ. It does not promise safety. It promises presence. It does not promise calm. It promises rescue. It does not promise answers. It promises Himself.

This chapter confronts shallow faith at every level.

It confronts cowardice through Herod.

It confronts scarcity through the feeding.

It confronts grief through compassion.

It confronts fear through the storm.

It confronts pride through Peter’s sinking.

It confronts unbelief through immediate rescue.

It confronts limitation through leftovers.

It confronts exhaustion through divine strength.

And above all, it confronts the illusion that faith is safe.

Faith walks.

Faith risks.

Faith sinks.

Faith cries out.

Faith gets lifted.

Faith worships afterward.

Matthew 14 is not a story about walking on water.

It is a story about who you look at when the water starts walking on you.

The deeper truth beneath Matthew 14 is not that storms happen. Everyone already knows that. The deeper truth is that storms are often where God introduces Himself in ways calm seas never could. We do not discover what we believe about God when life is gentle. We discover it when the waves pull at our ankles and the light feels far away. The disciples had already seen miracles. They had already watched healings. They had already handed out multiplied bread with their own hands. But none of that settled the question of who Jesus truly was the way the storm did. Safety can coexist with doubt. Chaos cannot.

There is something important about Jesus sending the disciples into the storm instead of preventing it. He did not miscalculate. He did not lose control. He did not forget them. He sent them directly into the trial. That alone dismantles one of the most common lies we wrestle with—that difficulty means abandonment. Sometimes the storm is not evidence that God has left you. Sometimes it is evidence that God trusted you enough to grow you.

Peter’s story in this chapter is often reduced to walking on water, but the real miracle is not his walking—it is his asking. He does not assume power. He does not demand certainty. He says, “If it is You…” That is the prayer of honest faith. It admits uncertainty but still longs to step forward. That kind of prayer is precious to God. It does not hide doubt. It brings doubt into His presence.

And notice what Jesus does not say. He does not promise Peter that the wind will stop. He does not explain the physics. He does not slow the storm first. He simply calls him to walk in the middle of it. Which means the storm was never the main obstacle. Fear was.

Peter walked on water as long as his eyes stayed on Jesus. The moment the wind became the focus, gravity reclaimed him. That is not punishment. That is instruction. It reveals how fragile faith becomes when fear becomes our god. The wind did not change. The waves did not change. Only Peter’s focus did. And that was enough to change everything.

But the most important word in that entire moment is “immediately.” “Immediately Jesus reached out His hand.” Not later. Not after judgment. Not after hesitation. Immediately. This is the heartbeat of the Gospel compressed into one second. We sink faster than we realize how scared we are. And yet God’s mercy travels even faster.

Matthew 14 teaches that failure does not cancel calling. Peter’s stepping out of the boat did not disqualify him just because he later sank. In fact, it became part of his credibility. Every future sermon he would ever preach carried the authority of a man who once walked on water and once drowned in doubt in the same night. That is not hypocrisy. That is testimony.

Then something quiet happens that many people overlook. Once Jesus and Peter step back into the boat together, the storm stops. Not when Peter starts walking. Not when the disciples panic. Not when fear peaks. The storm stops only when relationship is restored. It stops when Jesus and the one who failed are standing together again. That alone reshapes how we understand peace. Peace is not the absence of storms. Peace is the presence of Christ beside you when the boat is shaking.

And then the disciples worship. For the first time in the Gospel narrative, they openly declare that Jesus is the Son of God. Not after the feeding. Not after earlier miracles. Not even after healings by the thousands. It took the storm. It took the terror. It took the rescue. Before that, they followed Him. After that, they surrendered to Him.

This is the unsettling truth Matthew 14 delivers without apology: sometimes God will use your fear to clarify your faith.

The closing scene of the chapter returns to healing. People recognize Jesus immediately. They bring the sick. They beg only to touch the fringe of His cloak. And every person who touches Him is healed. No theatrics. No shouting. No formulas. Just contact. This is important because it comes after the storm. It shows us that the same hands that command wind are gentle enough to restore trembling bodies. Power and tenderness exist together in Christ, not in competition.

This entire chapter is a collision between human weakness and divine sufficiency. A fearful king, a hungry crowd, grieving disciples, a sinking apostle, desperate sick bodies—all of them collide with the same Son of God, and all of them walk away changed in different ways. Some change through tragedy. Some through provision. Some through fear. Some through rescue. Some through healing. But none remain untouched.

Matthew 14 also dismantles the illusion that faith follows a straight line upward. Faith rises, sinks, cries out, worships, doubts again, gets strengthened again, falls again, gets lifted again. This chapter shows faith as a relationship, not a ladder. Peter does not climb spiritually that night. He stumbles forward in relationship. And Jesus stays.

There is also a quiet lesson in the timing. Jesus arrived at the fourth watch of the night—between three and six in the morning. That is the hour just before dawn. The moment of greatest exhaustion. The phase where hope feels irrational. The hour where many give up internally even if they keep rowing physically. Jesus arrived not at the beginning of the trial but near the end of their strength. He often does the same today. Not because He withholds care, but because He knows exactly when our hearts become honest enough to receive it.

Herod’s story still echoes through the chapter without being mentioned again. A man who feared public opinion more than God lost his peace and gained paranoia. He mistook Jesus for John resurrected because guilt never truly stays buried. Meanwhile, fishermen who feared storms learned to fear God differently—not with terror, but with surrender. Two different responses to fear. Two different outcomes. One lost his soul trying to protect his image. The other found their souls by admitting their need.

Matthew 14 ultimately teaches that fear will always ask for your allegiance. It will demand that you bow to safety, comfort, control, and appearance. Faith will ask for surrender. It will ask you to step when the surface looks unreliable. It will ask you to trust when the wind insults your logic. It will ask you to believe that presence outweighs pressure.

And the question the chapter leaves behind is not whether storms will come. The question is who you turn toward while sinking.

The chapter is not about water.

It is about trust.

It is not about power.

It is about permission.

It is not about feeding crowds.

It is about whether scarcity controls you or obedience does.

It is not about walking flawlessly.

It is about crying out quickly.

It is not about never failing.

It is about never pretending you do not need rescue.

Matthew 14 does not present a polished faith.

It presents a living one.

A faith that bleeds.

A faith that trembles.

A faith that steps anyway.

A faith that sinks.

A faith that is lifted.

A faith that worships afterward.

And perhaps the most confronting truth of all is this: Peter did not become bold by staying in the boat. He became bold by failing publicly and surviving it with Jesus still holding his hand.

This is where our modern faith often breaks down. We want certainty without risk. Victory without vulnerability. Glory without surrender. But Matthew 14 will not support that illusion. It insists that faith matures through exposure. Through storms that dismantle shallow trust and build resilient surrender.

If Matthew 14 were happening today, many would call Peter reckless, impulsive, immature. They would praise the other disciples for staying safe. But heaven still tells the story differently. Only one man knows what it feels like to stand on chaos with Christ. Only one man knows what it feels like to drown in fear and be lifted immediately. Only one man learned faith through falling forward.

And that is the man Jesus later trusted to lead His church.

This chapter confronts anyone who thinks faith is neat.

It humbles anyone who thinks fear disqualifies them.

It heals anyone who thinks sinking means the end.

It comforts anyone who feels abandoned in the boat.

It challenges anyone who refuses to step.

Matthew 14 whispers to every generation the same invitation:

Come.

Not when the storm stops.

Not when the water settles.

Not when your confidence returns.

But now.

---

Watch Douglas Vandergraph’s inspiring faith-based videos on YouTube

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— Douglas Vandergraph

#Faith #Matthew14 #WalkOnWater #JesusSaves #StormFaith #SinkingToSaving #TrustGod #ChristianEncouragement #FaithOverFear #GospelTruth #Discipleship #SpiritualGrowth

. Photo : Sony zv-e10, objectif Viltrox 15mm Air, f1.7. Traitement avec Pixlr, filtre Amber (Friends)

Petite escapade samedi soir pour l'apéro au Montreux Noël. S'il y avait du monde, la situation était tout à fait viable. La bonne idée pour se déplacer le week-end, c'est la mise à disposition gratuite des bus depuis 13h00 sur la ligne 201. Idéal.

Photo : Sony zv-e10, objectif Viltrox 15mm Air, f1.7. Traitement avec Pixlr, filtre Alex (Friends)

Je suis aussi de retour avec mon sony zv-e10, muni de mon objectif Viltrox 15mm. Pour le traitement de l'image, j'ai testé Pixlr et sa formule express. A vous de voir.

Tags : #AuCafé #journal #photographie

#book #fiction #SF #cyberpunk

Warning: Some minor spoilers

There are two common misconceptions about meritocracy. The first, that we live in one and that our position in society results from merit rather than luck, wealth or other structural factors. Second, that living in a meritocracy would be desirable in the first place. We have forgotten that ‘meritocracy’ entered the English vocabulary as a pejorative and something to avoid. Evaluating people on merit rather than connections or wealth is certainly desirable, but the corollary of granting power based on merit is the disenfranchisement of everyone considered insufficiently meritorious.

The Ten Percent Thief, Lavanya Lakshminarayan’s debut novel, skillfully takes aim at both misconceptions. It is a bold, creative and excellent satire of contemporary fixation on merit and productivity, true to Ursula K. le Guin’s dictum that the best science-fiction illuminates the present rather than prophesises the future. The title of the book is derived from an eponymous stratum in Lakshminarayan’s fictional society, which divides its citizen into an upper 20%, middle 70% and lower 10% based on their productivity. One’s placement on this curve within the corpocracy of BellCorp, a self-described ‘meritocratic technarchy’, determines one’s rights, privileges and access to consumer technology, creating a constant race to the top. Failure to perform results in demotion, expulsion from BellCorp’s Virtual City to the adjacent Analog slums, or a one-way trip to the vegetable farm. The Ten Percent Thief is not always subtle in drawing its parallels with the present, but that makes it no less effective.

The novel’s first move is immediately brave and unconventional. The Ten Percent Thief foregoes protagonist and linear plot for a linked chain of chapters that carry the narrative arc over a period of, I’m guessing here, about fifteen years. From the first chapter where we meet the titular Ten Percent Thief, we jump to a middle-manager within Bell Corporation fearing their performance review. Then we jump back over the force field separating the glittering Virtual city from the Analog slums to a young teenager drawn into the resistance, then back to a Virtual citizen stuck on a trajectory down into the bottom 10%. And on it goes. Each chapter offers both a different vantage point for the workings of Bell Corp society, and a different character through which our perspective is filtered. We meet frantic influencers and supervised retirees, upper management and frontline workers, exiles and infiltrators. The Ten Percent Thief does precisely what Ada Palmer and Jo Walton call for in their essay on the Protagonist Problem, and it does so brilliantly.

It is a creative and brave choice, with excellent results. The roving view that Lakshminarayan gives of the world of the Ten Percent Thief helps us see it from different angles and perspectives, much more so than a story confined to the point of view of a single or small set of characters. Lakshminarayan artfully uses her succession of vignettes to construct a holistic picture of the world of the Bell Curve emerges, showing us the injustices of this world at both the macro and micro level, and the harm it inflicts on both its victims and its supposed victors.

For while Apex City’s Virtual citizens may have access to the latest technologies and amenities, the constant spectre of potential demotion for insufficient productivity prevents any real enjoyment. The ‘virtual’ in Virtual citizen denotes an abundant access to technology that fosters isolation and conformity rather than connection and community. This is not fully automated luxury communism, but fully automated precarious capitalism.

Capitalism though, but to what end? From what we can tell, Bell Corp is a monopolistic megacorp with full control over the Earth’s remaining resources. It is not in competition with anything, is mostly autarchic, and has achieved remarkable levels of automation. In other words, while its ethos is based solely on the valorisation of productivity, it is never clear what this productivity is for. Most of Apex City’s citizens appear to be engaged in proper bullshit jobs, with productivity measured through social media presence, body function monitoring or online popularity contests.

This paradox allows The Ten Percent Thief to deliver its satire with a two-punch effect, because you realise that every element that seems implausible does actually have a parallel in our own world. From the ultra-wealthy influencers to the pointless upper management, every time your willing suspension of disbelief is about to break, you remember that Elon Musk, Kim Kardashian and their ilk exist.

If I were being critical, I would say that Lakshminarayan trades off the impact of her satire against the coherence her political economy. Absent a market economy, BellCorp has to simulate competition through internal contests. Cultural conformity is enforced through social pressure or, failing that, electroshocks and cybnernetic neural rewiring. There is an obvious critique of online culture here, and while it is largely on point, it misses the nuance that under actually-existing-capitalism it doesn’t matter if people tire of your flagship superhero franchise, as long as you also own all other shows. For capitalism, diversity is another opportunity to sell people the means of individuation.

Neither do Apex City’s top 10% need the armies of impoverished and precarious workers that underpin our own capitalist economies, as most socially necessary production (manufacture, teaching, healthcare, agriculture) has been automated. It is difficult to say for sure as you never really get a feel for the size of Virtual society, but it’s reasonable to wonder if its lower rungs merely serve to make the elite feel good. There is no point in being on top if you cannot lord it over some other humans in a sort of Nietzschean master/slave dynamic. Maybe the purpose of the Bell Curve is simply to sustain the Bell Curve. It wouldn’t be the first system that came to care mostly about perpetuating its own existence.

Still, I was reminded of one of the futures in Peter Frase’s Four Futures, in which the elite eventually conclude that they don’t need the proles anymore, and the sunlit uplands of fully automated luxury communism are reached by deleting the entire ‘surplus’ population. It is not entirely clear why the upper echelons at Bell Corp haven’t long reached the same conclusion. It is not as if we’re short of Malthusian ultra-rich in our own world, after all.

The weaker political economy in The Ten Percent Thief’s worldbuilding is maybe the reason why the novel’s ending, while satisfying, feels a bit contrived. Having thoroughly disempowered the subaltern classes in her world, Lakshminarayan has to reach for a technological deus ex machina to resolve her plot.

These criticisms, however, are minor. On the whole, The Ten Percent Thief is an excellent novel that captures and excoriatingly satirizes our present moment, while also managing to step away from the eurocentrism that remains so pervasive in science-fiction. Its creative form brilliant supports its substantive argument, and it was great to read an example of a novel that overcame the ‘protagonist problem’ so effectively. On the Bell Curve of works of speculative fiction, I would most certainly put The Ten Percent Thief in the top 10%.

Notes & Suggestions

• It was particularly stimulating to read a novel that overcame the protagonist problem so soon after grappling with it in my review of Mass Effect 3.
• For a more in-depth analysis of how neoliberal capitalism manages to extract value and maintain compliance without the type of direct coercion we see in The Ten Percent Thief, Hegemony Now! is a good starting point.
• It has been nearly a decade since I read it, but I remember Peter Frase’s Four Futures as a short, sharp, stimulating essay on four potential extreme endpoints of our current capitalist trajectory.

Wind-whipped mornings. How quickly life is what it was, and defined by it —

early rides in the dark; the man on a bin, slipping, scaling a wall —

I remember it because of the blood-rend in the black-night cloud;

and because I had slowed to pass your dead-locked house, again.

Now that I have the UI for simple CRUD operations, I can clean up the code a bit.

• Add shared stylings.
• Unify the code between screens.
• Add a dark mode (too much for now, but I know I will need it later).
• Proper spacing and typography

This lays a good foundation I can build upon.

It makes me happy, this feeling of having a base on which I can iterate. Make small changes and directly see improvements. I hope I can keep this feeling up while improving the app. Small changes, small Features. 🤷

Another nice thing is when the UI goes from basic to polished basic. It is not much but improves the view noticeably.

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65 of #100DaysToOffload
#log #AdventOfProgress
Thoughts?

Every person carries a moment in their life that splits everything into two parts.

Before it happened.

And after.

For some people, it’s a phone call in the night.

For some, it’s a hospital room.

For some, it’s a courtroom verdict.

For one man, it was a hill outside the city, three wooden beams, and a dying stranger in the middle.

We call him the thief on the cross.

But that wasn’t how his story began.

Not even close.

Long before anyone ever spat on him.

Long before nails pierced skin.

Long before his name vanished from polite conversation.

He was a child.

He was named.

He was kissed on the forehead.

Someone once believed his hands would build something, not steal it.

Someone once believed his life would matter.

And that belief… would be buried long before his body ever was.

We like simple stories.

Good people and bad people.

Heroes and villains.

But real lives aren’t written that cleanly.

They fray.

They bend.

They crack under weight.

And his life bent slowly.

Work was scarce.

Power lived in Rome.

Money flowed upward.

And hunger never waits for dignity.

So he took a shortcut.

Not a dramatic one.

Not a headline one.

A small one.

And then another.

And then a thousand after that.

No one wakes up one day and decides to become a lost cause.

They decide to survive.

And survival, when stripped of hope, eventually strips everything else too.

By the time iron met his wrists for the final time, he didn’t curse.

He didn’t plead.

He didn’t run.

Because exhaustion had already done what chains only finished.

The streets felt different when everyone knew your ending.

The crowd always watches differently when they believe justice is being served.

Some people came for righteousness.

Some came for entertainment.

Some brought their children because even cruelty becomes ordinary when it’s repeated often enough.

Three crosses waited.

One crime for each.

Except one of them had no crime at all.

The sign above the middle cross was meant to mock.

“King.”

Painted like a joke.

Hung like a lie.

And yet… somehow… it felt heavier than the others.

The hammer struck.

And wood accepted flesh.

And flesh accepted iron.

Every breath turned into labor.

Every second into resistance.

Pain does something strange to time.

It stretches it.

It widens it.

It turns moments into miles.

The thief watched the crowd with eyes that had seen everything except mercy.

He had seen fear.

He had seen anger.

He had seen greed, hunger, violence, survival.

He had not seen mercy given freely.

Not like this.

One of the men beside him screamed in rage.

He spit curses at soldiers.

He screamed at the crowd.

And then his voice turned toward the center cross.

“If You really are who they say… save Yourself.”

The crowd loved that.

Ridicule always makes people feel powerful.

But the other thief did not laugh.

He studied the man in the middle.

And something felt wrong with the joke.

Kings begged.

Kings negotiated.

Kings cursed.

This one didn’t.

Blood ran down His face.

But calm stayed in His eyes.

And the thief realized something that shook him deeper than the nails ever could.

This Man wasn’t dying like someone who lost.

He was dying like someone who chose.

That is a different kind of strength.

And with what little breath he had left, the thief did something he had never done his entire life.

He told the truth about himself.

“We deserve this.”

Not as self-hatred.

As honesty.

And then, pointing with nothing but his eyes at the Man beside him:

“But He doesn’t.”

That sentence would have faded into the crowd if it wasn’t followed by the next one.

A question that wasn’t really a question at all.

“Remember me.”

No bargaining.

No reasons.

No résumé.

Just four words offered from a man who had nothing left to offer.

And then the reply came.

Not from heaven.

Not from thunder.

From torn lungs and steady authority.

“Today you will be with Me.”

Today.

Not after you fix everything.

Not after you explain everything.

Not after you repay anything.

Today.

And heaven shifted.

This man never preached a sermon.

He never corrected his past publicly.

He never restored what he had broken.

He never made amends.

He never became an example of religious discipline.

And yet… he became one of the most dangerous testimonies grace has ever produced.

Because he proves something most people secretly fear is not true.

That you do not earn your way into mercy.

You collapse into it.

This man entered eternity with blood on his hands, fear in his heart, and no record of righteousness to lean on.

And heaven opened anyway.

We struggle with that.

Because deep down, we prefer systems where worth is measured.

We like ladders.

We like proof.

We like paperwork.

This story blows all of that apart.

And that is exactly why it remains so threatening to pride and so comforting to the broken.

This man did not find God at the height of hope.

He found God when hope was already bankrupt.

He did not turn to God when life came together.

He turned when everything fell completely apart.

And that is where most people meet Him.

Not in strength.

Not in certainty.

But in surrender.

The cross did not convert a good man into a believer.

It revealed a lost man who finally stopped pretending he could save himself.

And that is the difference between the two criminals.

Not their record.

Not their pain.

Not their nails.

Their response.

One mocked until his last breath.

The other surrendered with his last breath.

And eternity split on that choice.

We talk often about being close to God.

But proximity doesn’t save.

Response does.

Both men were equal distance from Jesus.

Only one entrusted his soul to Him.

And that matters.

Because many people today sit near faith their entire life.

Near Scripture.

Near prayer.

Near theology.

Near church.

Near believers.

Near Jesus.

And they still never surrender.

They die near salvation…

but not inside of it.

This is not a story about criminals.

It is a warning for the comfortable.

And a rescue rope for the hopeless.

The thief did not come down from the cross.

But he went up anyway.

And that should unsettle every religious structure built on performance.

And comfort every soul crushed under shame.

Because it means your worst chapter does not get to write your final sentence.

It means your ending is not hostage to your past.

It means the door of mercy is not guarded by your résumé.

It is guarded by your surrender.

And that changes everything.

The thief’s body never stopped hurting.

The promise didn’t erase the pain.

The words “Today you will be with Me” didn’t magically soften the nails or quiet the burning in his chest.

Salvation did not anesthetize suffering.

It sanctified it.

He still had to endure the same hours as the others.

Still had to surrender breath one at a time.

Still had to stare death in the face without the option of escape.

But everything inside him had changed.

He was no longer dying toward nothing.

He was dying toward Someone.

And that makes all the difference in the world.

The sky darkened.

The crowd unsettled.

The soldiers shifted uneasily as the earth groaned under the weight of what humanity was doing to its own Creator.

And the thief kept watching the Man in the middle.

He had stolen many things in his life.

Money.

Food.

Opportunities.

Trust.

But this… this was the first thing he would ever receive without taking it.

He would be carried.

His final breath left his body somewhere between broken agony and quiet trust.

And then… the hill disappeared.

Darkness gave way to light.

Pain loosened its grip.

And the man who entered death empty… arrived in eternity full.

He had no history of righteousness to lean on.

No lineage to quote.

No accomplishments to frame as evidence.

Only a promise.

And that promise carried him farther than his best efforts ever could.

We imagine heaven with gates and brilliance and order.

But I imagine something simpler first.

I imagine confusion.

Not the confusion of fear.

The confusion of relief.

The confusion of a man who expected judgment and found welcome instead.

And when asked why he stood there, the most honest answer he could give was the only one he had.

“The Man on the middle cross said I could.”

That sentence dismantles every illusion of earning.

It tears down every ladder of spiritual performance.

It humiliates pride and resurrects hope.

Because it means we don’t enter God’s presence by proving we deserve it.

We enter because Jesus said we could.

And that reality changes the way we look at ourselves, and the way we look at others.

It means no one is too far gone.

It means the last breath is not too late.

It means grace works faster than regret.

It means mercy outruns memory.

It means shame does not get the final word.

It means your worst chapter cannot veto God’s ending.

But this story is not only about heaven.

It’s about here.

Because we are far more like those two thieves than we are comfortable admitting.

One spent his dying seconds demanding proof, demanding rescue, demanding conditions.

The other entrusted his soul without leverage.

And both had equal access to Jesus.

Some people want God on their terms.

Others want God at any cost.

Only one walked into eternity at peace.

We can be near Jesus our whole life and never surrender.

We can attend.

We can listen.

We can nod at truth.

We can quote Scripture.

And still never trust Him with our ending.

This is the hidden danger of familiarity.

Proximity without surrender.

Religion without trust.

Belief without yielding.

The thief teaches us that it is not how long you knew about Jesus.

It is when you finally place yourself in His hands.

Some people believe early.

Some believe late.

But everyone enters the same way.

Helpless.

That is what makes the story so uncomfortable for pride.

And so beautiful for the broken.

Because it removes comparison.

No one gets in by being better.

Everyone gets in by being His.

That means the addict who relents tomorrow enters by the same door as the pastor who served faithfully for decades.

That means grace is just as complete for the last-minute surrender as it is for the lifelong disciple.

Not because effort doesn’t matter.

But because salvation is not wages.

It is inheritance.

The thief had no time to prove transformation.

But Jesus saw transformation before it ever had time to prove itself.

And that truth is painful for systems built on measuring worth.

But it is oxygen for souls crushed under guilt.

Some of you reading this have spent years punishing yourselves for who you were.

You replay old versions of yourself as if shame were a discipline.

You believe forgiveness is real, but you secretly think you forfeited it.

You believe grace exists, but not for you in full measure.

You believe God restores others, but your case feels different.

The thief on the cross destroys that lie completely.

He had no future reputation to rebuild.

No opportunity to demonstrate improvement.

No church attendance streak.

No evidence of reform.

Only surrender.

And Jesus said, “Today.”

That word still echoes.

Not tomorrow after you fix it all.

Not when you finally become who you think you should have been.

Today.

This is why the story terrifies legalism and heals the wounded.

Because it doesn’t flatter effort.

It magnifies mercy.

And that is what most souls are starving for.

Mercy without suspense.

Mercy without fine print.

Mercy without negotiation.

And yet… the story does not excuse sin.

The thief did not deny his guilt.

He did not rationalize it.

He did not blame Rome.

He did not scapegoat the system.

He spoke one of the rarest sentences in human history:

“We deserve this.”

That sentence alone tells us something essential.

Grace does not require denial of guilt.

It requires ownership of it.

The thief didn’t ask Jesus to call evil good.

He asked Jesus to remember him anyway.

And that distinction matters.

You do not have to pretend you are innocent to be forgiven.

You only have to trust the One who truly is.

That is the collision of honesty and hope.

We often fear that if we truly admit what we’ve done, God will turn away.

The thief proves the opposite.

Honesty is what turned him toward God.

Because there is no safer place to be known than in the presence of mercy.

The cross holds both truths at once.

We are more broken than we ever wanted to admit.

And we are more loved than we ever dared to hope.

That is why this story endures.

Not because it is dramatic.

But because it is accurate.

It tells us what kind of God we are dealing with.

Not a God who waits at the finish line with a clipboard.

But a God who descends into human pain and lifts us out of it.

The Man on the middle cross did not save the thief by removing his cross.

He saved him by sharing one.

And that is the God revealed in Jesus.

A God who does not shout instructions from safety.

But enters suffering Himself.

So that suffering would no longer be the end of the story.

This is what reshapes how we see every broken person we encounter.

Because none of us knows when another soul will speak their “remember me” moment.

And if grace can reach a man nailed to a Roman execution stake, it can reach anyone.

Anyone.

The cross announces that no one is beyond the radius of mercy.

No addiction outruns it.

No failure outpaces it.

No shame blocks it.

No past vetoes it.

And no future fears it.

Which brings us back to the only difference between the two men that day.

Not their pain.

Not their crimes.

Not their suffering.

Their surrender.

One chose cynicism.

The other chose trust.

One died demanding evidence.

The other died trusting grace.

And eternity split right there.

So the question this story always asks is not:

“Are you good enough?”

It is:

“Who are you trusting with your ending?”

Because one day, all of us will exhale a final breath.

And whatever we have built will suddenly become very small.

What will remain is not what we achieved.

Not what we accumulated.

Not who applauded us.

Only who holds us.

The thief teaches us that no résumé follows the soul.

Only relationship does.

And that relationship was sealed with four words spoken through pain.

“Today you will be with Me.”

That promise was not just for a dying criminal.

It was for every future reader crushed under the weight of their own mistakes.

It was for every believer who ever wondered if they had waited too long.

It was for every soul that ever thought their final chapter was already decided.

That hill still speaks.

That promise still works.

That mercy still moves.

And the Man on the middle cross is still saying the same thing to surrendered hearts:

“Come with Me.”

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Your friend, Douglas Vandergraph

#GraceWins #ThiefOnTheCross #RedemptionStory #FaithThatSaves #MercyOverShame #JesusChangesEverything #HopeForTheBroken #NoOneTooFarGone