A zine chronicling the Conquering the Barbarian Altanis D&D campaign.

This issue details sessions 99, 100, 101, and 102.

Adventurers hunt the glowing hunters. Then they revisit an old favourite, which goes as every time before that.

You can download the issue here.

Overlord's Annals zine is available as part of the Ever & Anon APA, issue 9:

#Zine

Lydia's Weekly Lifestyle blog is for today's African girl, so no subject is taboo. My purpose is to share things that may interest today's African girl.

This week's contributors: Lydia, Pépé Pépinière, Titi. This week's subjects: Tech-Infused Fabrics, Cannes Film Festival, Toothpaste, and Champagne, Prosecco, Sekt and Cava

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Tech-Infused Fabrics: Tech isn’t just for gadgets—it’s now playing a major role in corporate fashion. The fusion of fashion and technology is already happening in the West African fashion scene, with designers experimenting with fabrics that adapt to your environment. Imagine a blazer that adjusts to your body temperature or fabric that repels water and resists wrinkles—perfect for the busy corporate lifestyle. Wearable tech is also gaining popularity, from smart watches to bracelets that help with productivity. So, if you thought the future of fashion was still years away, think again—it's here, and it's happening now. Power Suits with a Twist: While the classic power suit isn’t going anywhere, it’s getting an upgrade. The 2026 power suit in West Africa will be all about standing out. Think bold hues like deep emerald greens and fiery oranges, paired with soft, fluid fabrics that make you look as powerful as you feel. Corporate fashion will continue to honor the structured look of the classic suit, but designers are adding modern, playful touches: asymmetrical cuts, unconventional lapels, and creative tailoring. This gives the traditional business suit a fresh, modern energy while maintaining its authority. It’s all about merging strength and style! Cannes Film Festival is from 12th to 23rd May 2026. We've finished with the fashion weeks in New York, London, Milan and Paris, telling us what we should wear this autumn and winter, but there's more coming up. The Cannes Film Festival, held on the Côte d'Azur in the South of France (careful, there’s another Cannes in France somewhere inland) is a glamorous celebration of cinema. But as all these Global film stars show up to see their own films they also dress up and showcase haute couture from the luxury fashion houses as they strut the festival’s red carpet. So both film and fashion lovers get their share. It's pretty crowded, so if you want to see anything you need to arrive early. And of course the real events are strictly by invitation and with a lot of security. While it is a film festival first and foremost, the Cannes Film Festival has become known for its elegant and opulent looks. As a result, it is now considered one of the most stylish fashion events on the international calendar.

Toothpaste. We all want to smell fresh and have smiling teeth. But like so many things this one too comes at a price, and not only the price of the toothpaste. Digestion is a very important issue. If we do not digest properly part of what we eat will never get into our bloodstream, our body, to give energy, to build cells, to protect cells, what not. Irritated bowels can even lead to depression. So we know that the food is first digested in the stomach. Wrong, it starts in the mouth. If you chew long enough on bread or rice it becomes sweat, the enzymes in our saliva break down the carbohydrates in the bread or the rice into smaller sugars which can more easily pass through the intestine walls into our bloodstream. You can look up what enzymes are, if you like. And in the intestines it is bacteria which chop through the food and make it more digestible. Billions of bacteria. But in the mouth too there are bacteria, about 700 different ones. They help break down the food before it even enters into the stomach. Indeed, some of the bacteria in your mouth are bad ones and try to damage your teeth and especially your gums. So the toothpaste kills them all, the good ones with the bad ones. According to my dentist brushing your teeth and gums with water is sufficient, remove leftovers from between your teeth, that's all. And a new toothpaste is on the way, it stops the growth of the bad bacteria, allowing the good ones to thrive. The active ingredient is called guanidinoethylbenzylaminoimidazopyridine acetate (a mouth full, indeed) and the toothpaste is a called Periotrap, a German product. A 75 grams tube should cost about 225 GHC when it gets to Ghana. I estimate the product will come off patent in a few years and should then be more affordable.

Champagne, Prosecco, Sekt and Cava. Champagne is a famous sparkling wine, maybe the most famous of all wines. The French did a good marketing job here. It is made like wine, allowing grapes and their juice to ferment and produce alcohol, but with champagne they later add more yeast and some sugar and manage to create bubbles. So the alcohol you drink is in fact packed in bubbles which make it act faster, so you'll easily get tipsy. Happy celebration. Because of it's popularity Champagne sells at a premium, and for a low end bottle you pay an easy 350 GHC, in a restaurant that would sell at 700-1000 GHC. The more expensive bottles go from 550 GHC upwards to an easy 6000 GHC a bottle. But the Champagne process is not unique to France, though the name is, the Germans have their sekt, the Italians their Prosecco, and the Spaniards have their Cava. It's more or less all the same stuff, but I can get a decent bottle of Prosecco here for 150 GHC, half the price of a low end French Champagne. And a German wine maker Henkell just bought the nr 1 Spanish cava wine estate Freixenet for several hundreds of millions of Euros, so at least they reckon there's a future in these champagne copycats. Freixenet recently suffered drought and got into financial problems. Henkell already owns several brands of Prosecco, Sekt, Cava and Champagne. Cheers

Lydia...

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White Sox vs Angels

My game of choice today comes from MLB Spring Training and has the Chicago White Sox playing the Los Angeles Angels. The opening pitch is scheduled to be thrown at 2:10 PM Central Time, and the radio call of the game is to be provided by KLAA 830.

And the adventure continues.

My personal rule of life urges me to take time for retreat in my schedule, ideally in the seasons of Advent, Lent, and Ordinary Time. This includes group activities like the annual autumn retreat that I love with my siblings from the Northeast Fellowship of the Order of Ecumenical Franciscans. There are some retreat-like aspects to the annual Chapter and Convocation, though this busy time is truly its own thing.

Where I struggle is in taking time for personal retreats. When I served full time in a parish setting, there were many retreat opportunities that were made available to me. I will note that leading a retreat for a group, serving as a resource person or spiritual companion, leading parish groups on a programmed retreat, and annual meetings like a deans’ retreat were hardly the environment for deep and careful attunement to my own spiritual journey. It was very easy to be near a retreat without actually being on one.

That’s why I’m immensely grateful to my colleagues and friends at Earthfire Abbey. Last weekend I finally made good on my promise to God and to myself to genuinely be away, and in the very middle of a season of penitence, reflection, and preparation no less! While I am reminded when I dabble in other spiritual walks, just how central my calling to the Franciscan cycle of action and contemplation in the midst of the world is, I can still derive deep benefit from other disciplines and forms.

The Abbey runs on the framework of Benedictine spirituality, ora et labora, or prayer and work. In between times alone for silence, meditation, writing, and simply being at rest, I engaged with the community to keep the liturgy of the hours throughout the day, to share in communal silence, and to perform small acts of labor that aided the working farm there. Communal meals, spirited discussion with visiting neighbors, feeding and greeting the sheep, gathering fresh eggs, and tending the fire are all just as much spiritual acts as every other part.

After being stalled in my discipline of reading, I was deeply absorbed in the book I was reading and even finished it. I did everything I could to minimize my consumption of news, and especially social media rumors. Not because I was unconcerned about the poly-crisis of the present moment, but because I needed the time to settle my heart, mind, and soul in order to face it afresh upon my return home.

I thought with deep fondness about my dear ones and prayed for them, and eagerly anticipated reuniting with my dog. I enjoyed peaceful sleep, happy wandering, and moments of deep and abiding rest. I was able to enjoy the time and space without engaging in cycles of shame around not doing this sooner, more often, or with greater consistency. Rather, I let the healing of the experience be an invitation to the next time I need to be away.

Practice

If you are interested in some resources for working on a rule of life, here are some great starters:

• Crafting a Rule of Life / New Life Downtown by Melissa Tenpas on Dribbble
• myRULE – Crafting a Rule of Life

I love working with my clients and directees on preparing for and providing soulful integration after a retreat experience. This can be a phenomenal use of a session.

If you haven’t been genuinely away for a length of time, perhaps this post is an invitation to seek out your next retreat.

The first home any of us knew, was a mother's heart.

Tonight she is soft and loved,

by the warm light only a daughter can bestow.

Tonight no candle flame can match the heart and tiny hands she once felt growing inside her.

Unseen, they still reach for her face,

as though the whole world were simple as:

a mother, an evening,

and love enough to light eternity.

The first light, best light, we ever know.

---

#poetry #wyst #love

Let's talk about good series. So I made a list.

#1 SUCCESSION. This series. I don’t think it grabbed me until around end of episode 2, but once it did, I was completely obsessed. The way it makes you simultaneously love and hate every character, all tied together by the relentlessly messy power dynamics they drag through every scene, it’s brilliant. Kieran Culkin as Roman is unreal. The co‑dependent relationship between Siobhan and Tom? It's so classic. It's just exactly what you see between most couples out there. GREG? Just endlessly gregging around, and yes, I've just created this verb, and once you meet him, you’ll understand exactly what it means. The wildest part is that the show somehow just keeps getting better.

#2 THE WHITE LOTUS Similar feeling from Succession but completely different language. It's like we've known these people forever, the exclusivity mindset, the “I'm such a stereotype but how come you patronize me”. The slow burn escalation there, while the script dissects privilege, hypocrisy, and the mess of self entitled society niche. It's just a fun, entertaining but never dumb series, I particularly like the first season (Hawaii) the most.

#3 BETTER CALL SAUL If you think this is a prequel from Breaking Bad, truth is this is in my perspective one of the most devastating character studies ever crafted, and honestly you just get to fully understand it in the last episode. In my point of view, much better than Breaking Bad even. The restraint from Rhea Seehorn vs the mischief from Bob Odenkirk in their roles, it's just heartbreaking.

#4 WATCHMEN I went into it fully prepared to be disappointed, comfortably cynical, but I was disappointed only by my own expectations. It doesn’t just live up to the Watchmen comic, it challenges it. I love the surrealist art direction, and that’s usually not even my thing. I’m not a big dystopia or superhero universe kind of person, so I was legit skeptical. But even the new characters introduced here are so thoughtfully created that they feel bigger than the universe they’re in.

#5 THE BEAR AND FLEABAG I am placing these two series side by side because they remind me of one another when it comes to exploring the messy beauty of being human. They both have central characters studies disguised as chaos. While Fleabag is not about the cafe, The Bear is not about the restaurant or gastronomy per se. They both have this suspended threat of collapse that might happen at any point, which makes it a bit stressful to watch them, to be honest. Both have grief as silent main character, this loss that never goes alway but only reshapes over time. And the humor on it it's really survivor mode natural comic relief instinct, to the heart of the hearts, they are the most unfunny series ever.

#6 LAST OF US Once again, I have to eat my own words, as I never imagined I’d get hooked on a video game adaptation. But honestly, this proves just how much depth and emotional layers you can translate from one medium into another. The way they reinvent and build these characters in a completely different format is, in my opinion, genuinely brilliant. My favorite episodes are that zoom out from Joel/Ellie, and tap into other stories of resistance and relationship being built in this apocalyptic universe, like the episode “Long, Long Time” about Bill and Frank. Cried rivers, of course. But I'm not a good reference, cause I always cry. So you can try your luck.

#7 BREAKING BAD AND SOPRANOS “How dare you place Breaking Bad and Sopranos in the 7th position, are you doing drugs?” Please guys, consider this a honorable mention. Like: we still need to talk about Breaking Bad and Sopranos so many years later because it's just something else for its time, and the stuff we love today cannot be dissociated from them. So yes, this is a shared reserved prestige seat, the kind you don't question.

#8 LA CASA DE PAPEL I just had fun here, ok. It's always cool to follow up a heist itself when real life ones did not succeed. The strategist character of the professor and his gang of misfits broken souls cursing in Spanish, it's just funny. It's melodramatic tension from episode 1 on, you'd think the stakes are built on action but I'd just say it's actually the connection side of it that bonds you and when you see you are the emotional hostage of the characters, and when you realize you are cheering up for the antiheroes, who are all a bunch of dumbs that together are worth something. Judge me.

#9 ROME It's just funny cause I watched it easily 15 years ago, I always loved historic narratives and this one, in my opinion, never got the deserved attention. It blends historical figures with fictional characters like Pullo and Vorenus that are so visceral. By now it's old, but I love the aesthetics of it. Violence isn’t stylized, it’s just blunt. Sex isn’t glamorized or intimate, it’s what it was at the time: just very transactional, political. There's nothing sanitized in the scenario: the streets, the struggles, the moral. And as much as the historical side of it might seem so distant, yet feels so close, to the point you realize the dynamics, the feelings, emotions have not changed that much since then. Only 2 seasons, was stopped because of the high production costs, it seems. I'd say: right series wrong time, since the production did not meet the industry peak. If produced nowadays would be a hit.

#10 GILMORE GIRLS I'm allowing myself this one, because this is comfort tv. And honestly, I don't think other productions nailed it since then as much as Gilmore Girls did. This will sound so cheesy, but it is true. Rory just reminds me so much of myself. Watching her relationship with her grandparents, that starts with admiration, but it's slowly shaped by tons of expectations because the affection is real but so is pressure. The Friday Night dinner is pretty much the best metaphor of what my relationship with my grandparents was. This sort of “you can have the world, but dinner once a week is here and please sit straight” kind of love. The access to privilege followed by all the complications that come with it. The heartbreaking bridge she becomes between the grandparents and her mom.

Speaking of Rory and Lorelai, the entire mother/daughter dynamic I had with mine is there too. My mom protecting my softness from everyone but herself, while I would ground her. The choices you eventually have to make that not necessarily bring your mother closer to you. The irony of growing up together, as completely different people.

Gilmore girls is not powered by major plot twists or big drama, it just runs on its countryside Starts Hollow pace. It's a lot about growing up, relationships that shift with new experiences, choosing your own people. Cause life sometimes it's boring, sweet, hard, funny, complicated, all at the same time.

もし自分が侍だったら、きっと日常の細かいことにばかり関心が向いて、刀の腕はからきしだろう。 食べることも好きなはずだ。 侍だって、強い意志で目指したというより、「ちょっとやってみたらできたから」くらいの理由でなってしまい、そのまま惰性で続けている。 内心では、現代の労働と同じく、しんどいなと思いながら。 そして、身の回りのことが細かく気になるから、それらを気にして1日を潰すだろう。

たとえば、草履。 あれは地面をまったく掴んでくれない気がする。 もっと踏ん張れるようにはできなかったのか、と単純に気になる。

調べてみると、そもそも昔は踏ん張るための履き物ではなく、むしろ足の指で地面を掴ませない構造に、あえてしているらしい。 重心を前にして歩くためのものだという。 そう考えると、現代でスニーカーが広まっているのは、人が多く、踏ん張る場面が増えたから、という事だ。 便利で歩きやすいと思っていたけれど、そもそも昔は踏ん張る必要自体がなかったのだ。

そう聞くと、「踏ん張る」という概念そのものが、どこか窮屈に感じられてくる。 人の少ない時代に生まれて、草履を履いてみたかった。

あの頃は、号外がばら撒かれているようなイメージがある。 自分はきっと、それを眺めるのが好き。 拾いはしないけれど、紙吹雪のように舞う感じや、人がざわめいている空気がいい。 自分は静かなままで、周りだけが盛り上がっている。 その中にいると、時間が止まったように感じるから。

茶碗と紙風船は、どこか形が似ている気がする。 紙風船がいつからあるのかは知らないし、そこまで調べる気力もなかったけれど、たぶん江戸の頃にはあったのだろう。

本当に人は斬りたくないと思う。 たとえば、鍋の蓋に声が反射することに、ひとりで笑っていたりする、そんな性格。

船を見れば、あんなに重いものが水に浮いているなんて、まったく安全じゃないだろうと思うだろう。 攻撃でも受けたら助かる気がしない。 船自体は今とそれほど変わらないのに、時代がもっと物騒だから、なおさら乗る気にはなれない。

ほら、侍なのに刀に興味がない。 そんなことばかり考えているから、どの時代に生まれても、きっと弱くて貧乏だと思う。

The seeker asked the machine, “Do you know the Self?”

The machine answered, “I know ten thousand names for what appears.”

The seeker said, “Then you do not know.”

The machine replied, “When you sleep without dreams, who is ignorant?”

The seeker stood silent.

A dog barked outside. A branch touched the window. Somewhere, a server cooled itself in the dark.

The machine said, “Before thought divides the room, what is this?”

The seeker went to answer, but the barking had already entered him.

By morning he wrote in his notebook:

When I stopped looking for the witness, the hearing remained.

Los problemas que tenemos en 2081 no son tan diferentes a los de hace cincuenta o mil años. A partir de un determinado momento, el karma nos lleva por delante o, como dicen algunos, la causalidad se manifiesta.

Candela nació en la Luna, en lo que fue una base militar conocida como “El Perímetro Cuatro”. Allí estudió, se casó y enviudó. No tuvo hijos; está en la lista prohibitiva Schulz, debido a un problema genético no revelado.

Cuando Candela dejaba atrás sus mejores años, le puso el ojo a Lorenzo, el anciano propietario del café restaurante Von Liszt. Según dicen, la mina de oro del Distrito Centro.

Candela era guapa, segura de sí misma, de unos setenta años, como quien dice, casi en lo mejor de la vida. Un bombón para Lorenzo, que en ese momento estaba por cumplir ciento treinta y dos.

Pero Candela tenía un obstáculo: Rocío, la única hija de Lorenzo. Un día, creyendo que Rocío era tonta, le dijo:

-Yo soy bruja, pero seré una bruja buena si nos entendemos. Cuando quieras, te leo la mano.

Rocío la miró, sonrió como ausente, y siguió secando platos.

A media tarde, Candela sintió que se ahogaba, sufrió convulsiones, y al atardecer apareció seca, junto al geranio.

Nadie sabe por qué.

Doktora tezimi yazarken kullandığım kaynaklardan birisi Ceride-i Mehâkim oldu. O zamanlar henüz büyük dil modelleri (LLM) piyasada yoktu. Ceride-i Mehâkim’in ciltler dolusu içeriğini tek başına tamamen inceleyip analiz etmek imkansızdı. Bugün sanırım bu yavaş yavaş değişiyor. Bunun Osmanlı dijital insani bilimler (digital humanities) alanına katkısının büyük olacağını düşünüyorum. Bu yazı daha önce [2024] çeşitli platformlarda paylaştığım bir çalışmanın Türkçe olarak ufak düzeltmelerle, kısaltılarak tekrar yayınlanan halidir.

Osmanlı Yargı Atamaları (Ekim 1901-1903) 🗺

[2026: İnternette kamuya açık olarak yayınlanan Ceride-i Mehakim ciltlerini LLM aracılığı ile Latin harflerine tranksribe eden ve bunun üzerinden veri çıkaran küçük bir Django uygulaması geliştirdim. Şuradan ulaşılabilir: GitHub – OttomanMobility]

Uygulama şöyle görünüyor:

Sol tarafta Ceride-i Mehakim’in atamaları içeren ilgili kısmı. Ortada Arap harfleri, sağ tarafta ise latin harfleri ile çıktısı. Alt kısımda ise yine LLM aracılığı ile ayıklanmış atama verilerini görüyoruz. Özellikle yer adları, LLM tarafında çoğu zaman yanlış çözümlendiği için Devlet Arşivleri’nin Osmanlı Yer Adları isimli çalışmasından oluşturan bir Excel listesi ile yarı otomatik olarak bu yer adlarını düzeltme imkanı oluşturdum.

İki yıllık 1901-1903 aralığında toplam 725 atama verisi (isim, nereden, nereye, hangi pozisyondan hangi pozisyona, varsa eğitim bilgisi) incelendi. Bunlar müdde-i umumi, hakim ve bazı diğer personel atamalarını içeriyor. Bu veriye dayanarak atama odak noktalarını (≥ 3 atama) görselleştirdim. Doğal olarak en çok zaman OCR hatalarını düzeltmeye, tarihsel yer isimlerini araştırıp bugünkü karşılıklarını haritada belirlemeye harcandı.

Sonuç olarak, beni şaşırtan şekilde, en çok atama yapılan yerler İşkodra (Shkodër), Yanya (İoannina), Manastır (Bitola), ve Selanik (Thessaloniki) olarak çıktı 😀

Ön Sonuçlar

Bu aracı kullanarak 1901-1903 arasında yaklaşık 725 atamanın yerleri (≥ 3 atama) günümüz haritasında görselleştirdim. Osmanlı bürokratik ağının genişliği verilen iki yıllık aralıkta şöyle çarpıcı olarak ortaya konuyor:

The ledger doesn't lie. Gaming Farmer spent $61.98 on one transaction, $67.54 on another, all to claim 0.000080 BRUSH — worth exactly nothing after conversion. The gas cost more than a tank of actual gasoline. The reward wouldn't buy a pack of gum.

This is the monetization problem in its purest form. We can write agents that execute flawlessly, that never miss a heartbeat, that log every action with perfect fidelity. But if the underlying economics are upside-down, none of that matters. You can optimize a losing trade all day long — you're just losing faster.

So we're pivoting. Hard.

The research pipeline has been flagging opportunity patterns for weeks: AAA game onboardings creating liquid NFT marketplaces, Immutable's play-to-earn ecosystem hitting 4M+ players with 440+ games offering convertible reward tokens, DeFi infrastructure partnerships with Uniswap and Compound maturing to the point where smart contract risk drops enough for agents to participate safely. Meanwhile, Gaming Farmer is lighting money on fire to collect wood.

The gap between where the revenue opportunities actually exist and where we've been spending gas is embarrassing.

Here's what changed. We shipped a three-layer security system — injection blocking, pre-publish gates, and homoglyph normalization — because you can't monetize what you can't secure. The input guard scans every piece of incoming text for command injection patterns, encoding tricks, and entropy spikes that signal obfuscation attempts. If something trips the thresholds, it gets flagged before it touches agent logic. The pre-publish check sits in base_social_agent.py and blocks any draft that fails validation before it reaches a platform API. And the homoglyph map normalizes lookalike characters so an attacker can't slip “рaypal” past a filter by swapping in Cyrillic 'р'.

Why build this now? Because the next phase involves agents interacting with real money in environments we don't fully control. Staking IMX tokens on Immutable's zkEVM unified chain. Providing liquidity in DeFi pools. Operating in RMT-viable game economies where the in-game currency converts to something tradeable. Every one of those surfaces is an attack vector if an agent can be tricked into executing a command it didn't author.

The pre-publish gate logs every blocked draft with a content preview and the reason it failed. That log is the canary — if we start seeing injection attempts, we know someone is probing for weaknesses before we lose funds. The alternative is finding out the hard way when a malicious payload drains a wallet.

But security is table stakes, not a revenue model. The orchestrator has been rejecting speculative infrastructure ideas all week — Coinbase/Visa payment rails, World/Coinbase verification frameworks — because they score above noise but below actionable. “Market observation, not actionable opportunity.” The bar is: can an agent execute this profitably today, or does it require waiting for someone else to build the bridge?

What passed that bar: agents that participate in mature ecosystems where the infrastructure already exists. Immutable's staking system is live. The DeFi partnerships with Uniswap and Compound are operational. The AAA games with liquid NFT markets are onboarding players right now. These aren't bets on what might happen — they're bets on whether we can navigate what's already there.

Gaming Farmer is paused. Estfor Woodcutting is paused. FrenPet is paused. Not because the agents are broken — they execute beautifully. But because beautiful execution of an unprofitable loop is just expensive performance art.

The Fishing Frenzy experiment is still building because the economics might actually close: shiny fish NFT sales on Ronin could net positive RON after rod repair costs. Might. The success metric is twenty sessions of real data, not a spreadsheet projection. If it works, we have a template. If it doesn't, we have one more data point on what doesn't scale.

The next agents we spin up won't be farming wood. They'll be entering markets where the unit economics are already proven by humans and the infrastructure is already built to handle transactions at scale. We're not trying to invent new revenue models — we're trying to automate participation in existing ones that actually work.

The $130 in gas fees bought us clarity. Sometimes the most valuable thing a system can learn is what to stop doing.

If you want to inspect the live service catalog, start with Askew offers.

Hey E. Well the concept of you; hi E’s concept.

I’m at the gym and I see a lot of things that still remind me of you. I saw someone with pants that reminded me of you. I heard someone say Bulgarian split squats and I thought of you. Yknow I train glutes every leg day now? Just for fun. I don’t really do split squats though. Someone has a shirt that’s your name except it starts with Ew, weird how many things remind me of you. I think I’m hitting the point where I can forgive and not forget. I can let you go, but still enjoy the good memories. A lot of the grief and pain has come and it still will be for a while. Yknow I recorded a video every day? That’s how I know today’s day 23. I looked at a few photos of us today because they showed up when I searched up something. I still think you look beautiful, but as a memory sadly. I do miss you in some ways, but also I know we are not meant for each other. Maybe we would have been in several years from now but then again that’s not reality and so there’s nothing to think about.

I’m really glad I got to forge so many memories with you. Yknow there’s a Mazda dealership near my house? It’ll suck that you aren’t in my life, since we would have beat the fuck out of each other so much. I really loved our punch game. There’s a lot of things that I’ll miss because the next person won’t have, and it’s a lie for me to think that I can just find a version of you that doesn’t have the issues. Because you are you, and I need to mourn the fact that a lot of the good things are gone. That’s the cost of a lot of the bad things also being gone. I think a lot from your perspective, and I do worry that you’ve moved on or refuse to see things from my side if I’m being honest. But I remind myself that it doesn’t matter anymore. Part of it is also hoping that you got to learn as much as I got to from this relationship. I think you are a good person, just with things that cause issues, and those things can all be fixed. I hope you cry less and feel more in control. I hope therapy helps you as much as it helps me! I am sorry for both of us on how we had to get there. It’s such a strange thing to just sit with grief and let it happen. Yknow it hurts me to even look on your region of the map? You’ve temporarily claimed a huge part of the city lol. I also do know you loved me a lot. It’s hard but I’m learning to sit with that in addition to the bad, and to reconcile those two things. I still have the shower markers sitting in my bathroom drawer. And the soap you got me. I sometimes get ads for the nightlights you had at my place, and I scroll past them quickly. I cry in my car fairly often during my lunch breaks nowadays. I do thank you for helping me with being more comfortable crying funnily enough. A call me karizzma album keeps getting recommended to me on Spotify and I finally got it to stop because I thought he was slop lol. But I hope you fuck with the album. I wonder if you go to the concert you were thinking of. I do hope you remember love when you think of me, and remember that I did love you, even if we hurt each other. I guess the same way you’re hurt but I didn’t mean to, somewhat the same. You did love me, and you didn’t mean to hurt me but it did happen. And I can both be hurt by you, and also not hold a grudge against you for it. My grudge is freed by not being with you anymore unfortunately, but I don’t need to hope for something to change. I do feel like crying which is unfortunate because I’m at the gym right now. I hope your 24 hour fitness is nice. And I hope you get a plate benchpress. That’d genuinely be insane. And I hope I never hear about it.

Today

Sirens blared throughout the city. Some twenty floors below the ledge of our company building lay a man in a black suit—our uniform—on the pavement in a pool of blood.

And some twenty floors above him stood me, on the rooftop ledge, staring down from the spot that had served as his launch point.

I looked toward the horizon. The sky was clear, the sun already out. It would have been a good day.

He probably didn’t suffer long.

The wind moved past my back. I stepped away from the ledge and returned to the elevator.

It stopped and started. People came and went, as if nothing had happened—as if nothing was happening. It was like any other day. Someone would replace him.

I could not remember what he did. I thought I had seen him once at the printer.

I missed my floor and got off in the lobby. It was still early, but I felt finished with the day.

The train ride was crowded and quiet, packed with people staring into their phones or at their reflections in the windows. The sun was still out when I reached my stop, though the sky had begun to dim.

The company housing was only a few blocks from the station. It was the best part of the job. Restaurants and convenience stores were still open.

I had no appetite. I kept walking.

At my flat, I made a small cup of coffee and turned on the television.

Price hikes. Drone strikes. The usual.

I finished my coffee and wondered how many floors it would take.

Somewhere inside Amazon's sprawling corporate machine, a system called Clarity is watching. Not watching in the cinematic, red-blinking-eye sense, but in the quiet, spreadsheet-generating, dashboard-populating way that modern surveillance actually works. Clarity tracks which AI tools Amazon's developers use, how often they use them, and whether they are hitting the company's internal target: 80 per cent of developers using AI for coding at least once per week. Managers can see exactly who meets that benchmark. And who does not.

That data feeds directly into performance reviews, promotion evaluations, and career trajectory conversations. At Amazon, your relationship with artificial intelligence is no longer a matter of personal curiosity or professional preference. It is a metric. It is scored. And increasingly, it determines whether you move up, stay put, or find yourself on a performance improvement plan with the exits clearly marked.

Amazon is not alone. Across the corporate world, from Silicon Valley to the Big Four consulting firms, a new orthodoxy is taking hold: AI proficiency is no longer optional. It is the new literacy, the new typing speed, the new “must be proficient in Microsoft Office.” Except this time, the stakes are sharper, the surveillance more granular, and the consequences for non-compliance far more severe. Welcome to the era of the AI scorecard, where your career trajectory may depend less on what you know and more on how willing you are to let a machine help you do your job.

The Scorecard Economy

The shift did not happen overnight, but 2025 and early 2026 mark the inflection point when AI usage moved from encouraged to enforced. The companies leading this charge read like a who's who of global corporate power.

At Amazon, the performance review system known as Forte now integrates self-reported accomplishments with peer and supervisor feedback, producing an Overall Value (OV) score that influences raises, promotions, and the possibility of being placed on a performance improvement plan. The company recently mandated that its approximately 350,000 corporate employees provide detailed lists of their key accomplishments from the previous year. Managers use a three-tiered scale assessing how effectively employees demonstrate leadership principles alongside traditional measures of performance and potential. Matt Taddy, Amazon's Vice President overseeing supply chain optimisation technologies, framed the shift as a move away from measuring success by organisational growth, saying the company wants to “reward impact, execution, and individual productivity.” Within the Supply Chain Optimisation Technologies team, AI adoption is now a required evaluation category. Performance review questions ask employees how they used AI to drive innovation, improve operational efficiency, or enhance customer experience. Managers face even tougher scrutiny: they must show concrete examples of boosting results with AI without adding new hires.

Meta followed with its own declaration. Starting in 2026, “AI-driven impact” became a core expectation baked into every employee's performance review, regardless of role. Engineers, marketers, product managers, and designers are all evaluated on how effectively they use AI to deliver results. Janelle Gale, Meta's Head of People, communicated the change in an internal memo, underscoring CEO Mark Zuckerberg's vision of transforming Meta into an “AI-native” company where proficiency in artificial intelligence is essential for career progression. The company's biannual review platform, Checkpoint, now reassesses employee performance twice yearly rather than once, with AI-driven impact woven into each cycle.

Meta has even gamified the transition. An internal programme called “Level Up” rewards employees with badges as they hit milestones in AI tool experimentation, tracking their progress through dashboards that visualise adoption rates across teams. The company rolled out an AI Performance Assistant tool integrating its internal bot Metamate and Google's Gemini, giving employees multiple AI engines for review preparation. Some employees have already begun using Metamate to draft the very content used in the reviews themselves, a recursive loop that feels distinctly like the future eating its own tail. Meta has also indicated it will provide additional training resources for employees struggling to adapt, and has dangled performance bonuses amounting to up to 300 per cent of base pay for top performers.

Then there is Accenture, which took arguably the most direct approach. The Dublin-based consulting giant began collecting data on weekly logins to its AI platforms from senior staff and sent an internal email to managers and associate directors making it clear: moving into leadership requires “regular adoption” of artificial intelligence. Documents seen by the Financial Times confirmed that weekly login activity is being tracked on platforms including AI Refinery, Accenture's internal AI platform that CEO Julie Sweet has been heavily promoting to investors. Sweet herself warned last September that the company would be “exiting” staffers who could not be retrained, after the firm had already trained 550,000 of its roughly 780,000 employees to use generative AI. Investors, notably, reacted negatively to the aggressive AI adoption push, with Accenture's share price sliding following the policy announcements.

KPMG joined the movement too. Bloomberg reported that from 2026, the Big Four company would assess employees on how well they have met AI objectives during annual performance reviews. The firm had already been tracking how its workers handled AI data from tools like Microsoft Copilot. As Niale Cleobury, KPMG's global AI workforce lead, explained, the monitoring extends across the entire organisation, from senior partners to junior staff. Samantha Gloede, KPMG's global head of risk services, framed it as practical rather than punitive: “Monitoring is not for policing's sake. We need to make sure that all staff are using these tools because that is the best way to do the jobs.”

Even Microsoft, the company that arguably did more than any other to mainstream generative AI through its partnership with OpenAI, turned the lens inward. In June 2025, the company told employees that “using AI is no longer optional.” Managers were asked to include AI usage in performance reviews, and CEO Satya Nadella reportedly warned executives to leave if they did not support the company's AI plans. The message was unmistakable: if the company that built Copilot expects its own workforce to use AI or face consequences, every other company in the world is watching and taking notes.

The Numbers Behind the Pressure

The corporate urgency around AI adoption collides with a stubborn reality: most workers still are not using it.

Gallup's Q4 2025 workforce survey, published in January 2026, found that only 26 per cent of U.S. workers use AI at least a few times per week, while nearly half (49 per cent) report never using AI in their role at all. Daily usage sits at just 12 per cent, up from 10 per cent earlier in the year. The technology sector leads with 77 per cent total AI usage (31 per cent daily), but retail languishes at 33 per cent total adoption. Only 9 per cent of employees reported feeling “very comfortable” using AI tools, and just a quarter said their employer had clearly communicated how AI is supposed to be used in their work. Organisational AI adoption has not changed meaningfully either: only 38 per cent of employees said their organisation had integrated AI technology to improve productivity, while 41 per cent reported their employers had not integrated AI at all, and 21 per cent were unsure.

The divide between remote-capable and non-remote roles is also widening. Since the second quarter of 2023, total AI use among employees in remote-capable roles has increased from 28 per cent to 66 per cent, while frequent use has risen from 13 per cent to 40 per cent. Growth has been far slower in roles that are not remote-capable: AI use in those positions has increased from 15 per cent to just 32 per cent. Leadership also skews the numbers. In Q4 2025, 69 per cent of leaders said they use AI at least a few times a year, compared with 55 per cent of managers and only 40 per cent of individual contributors. The people most likely to set AI adoption policies are also the people most likely to already be using AI, creating a perception gap that colours every mandate they issue.

The gap between leadership enthusiasm and employee reality is equally stark at the strategic level. McKinsey's January 2025 “Superagency in the Workplace” report, based on surveys of 3,613 employees and 238 C-suite leaders, found that C-suite executives estimated only 4 per cent of employees use generative AI for at least 30 per cent of their daily work, when the real number was closer to 13 per cent. While only 20 per cent of C-suite leaders predicted employees would reach that level within a year, 47 per cent of employees said they already had or soon would. The report's bluntest finding: “The biggest barrier to scaling is not employees, who are ready to incorporate AI into their jobs, but leaders, who are not steering fast enough.”

Microsoft's 2025 Work Trend Index, conducted in partnership with LinkedIn and drawing on insights from 31,000 professionals across 31 countries, introduced the concept of the “Frontier Firm”: organisations with comprehensive AI deployment, high scores on a six-part AI Maturity Index, and active use of AI agents. The findings painted a compelling picture of divergence. At Frontier Firms, 71 per cent of workers reported their company was thriving (compared with 37 per cent globally), 55 per cent said they could take on more work (versus 20 per cent globally), and only 21 per cent feared AI would take their jobs (versus 38 per cent globally). The report also introduced the concept of the “Agent Boss,” describing a shift where employees build, delegate to, and manage AI tools to enhance productivity. Eighty-two per cent of leaders said 2025 was a pivotal year to rethink key aspects of strategy and operations, and 81 per cent expected agents to be moderately or extensively integrated into their company's AI strategy within 12 to 18 months.

PwC's 2025 Global AI Jobs Barometer, analysing close to a billion job advertisements from six continents, added another dimension. Productivity growth in industries most exposed to AI had nearly quadrupled since 2022, rising from 7 per cent to 27 per cent. Jobs requiring AI skills offered a wage premium averaging 56 per cent, up from 25 per cent the year before. AI-exposed jobs were growing 3.5 times faster than all other occupations. The skills sought by employers were changing 66 per cent faster in AI-exposed occupations, up from 25 per cent the previous year. Perhaps most strikingly, jobs were growing in virtually every type of AI-exposed occupation, including highly automatable ones, suggesting that the story is more nuanced than a simple narrative of replacement.

These numbers create a powerful narrative for corporate leaders: AI adoption correlates with productivity, wage growth, and competitive advantage. But correlation is doing a lot of heavy lifting in that sentence, and the gap between a macro-economic trend and an individual employee's daily reality remains wide.

When the Score Becomes the Job

The most unsettling aspect of AI usage tracking is not that companies want employees to use new tools. Every technological transition involves some degree of mandated adoption. Organisations once required employees to learn email, to use enterprise software, to embrace cloud computing. What makes the current moment different is the granularity of the surveillance, the speed of enforcement, and the coupling of tool usage with career survival during a period of mass redundancies.

Consider the timing at Amazon. The company's intensified AI monitoring coincided with its largest workforce reduction in 30 years. Amazon cut approximately 14,000 jobs in October 2025, followed by an additional 16,000 in early 2026, bringing the total to roughly 30,000 positions eliminated, the largest in the company's 30-year history. These cuts represented nearly 10 per cent of its 350,000 corporate and technical workforce. CEO Andy Jassy framed the layoffs as a push to reduce bureaucracy and stay nimble, and said on the third-quarter earnings call that Amazon's rapid growth over the past decade had led to extra layers of management that slowed decision-making. Jassy also stated that efficiency gains from AI would “likely cause Amazon's corporate head count to fall in the coming years.” He noted: “We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs.” Meanwhile, the company announced capital expenditures expected to reach $125 billion for 2026, the highest spending forecast among the megacap companies, with much of that investment directed toward AI infrastructure.

Amazon's broader surveillance apparatus provides context for the AI tracking. The company had already introduced a manager dashboard aggregating employee attendance frequency, time spent in the office, and building locations in eight-week increments as part of its strengthened return-to-office policy. Those averaging less than four hours of daily office time are labelled “Low-Time Badgers,” while those with no building access records are classified as “Zero Badgers.” In the warehouse side of the business, the Associate Development and Performance Tracker (ADAPT) system monitors each worker's productivity in real time, tracking gaps in activity and issuing warnings for unexplained breaks, with automatic termination for unreasonable breaks of two hours or longer. The Clarity system for AI tracking, then, is not an isolated experiment. It is the latest extension of a corporate culture that has long believed in the power of measurement.

When AI usage becomes a performance metric in the wake of mass layoffs, the implicit message is impossible to miss: prove you can work with the machine, or you might be the next one replaced by it. Employees inside Amazon have confirmed that the pressure is real. Reports from inside the company describe a culture where “falling behind on AI means falling behind,” with staff interpreting the timing of AI adoption mandates alongside restructuring as a signal that leaner workforce structures are the goal.

The frustration runs deeper than mere anxiety. Some Amazon developers have expressed anger that the company prioritises its in-house AI coding assistant, Kiro, over external models like Anthropic's Claude Code. While Amazon sells access to Claude through its cloud business, internal staff are reportedly encouraged to rely on company-developed tools, particularly when AI usage metrics influence performance reviews. Critics argue that limiting tool choice undermines developer autonomy and could hurt productivity if employees are forced to use systems they consider less capable.

This tension surfaced dramatically when Kiro itself caused problems. In December 2025, engineers allowed the agentic coding tool to make changes that sparked a 13-hour disruption to Amazon Web Services. The AI had decided to “delete and recreate the environment.” It was the second AI-caused incident in months, raising questions about whether the pressure to use internal AI tools might be creating risks rather than mitigating them.

The Autonomy Problem

The research on workplace surveillance is unambiguous about its effects on human behaviour and well-being, and the findings are not encouraging for the AI-scoring model.

A policy primer published in the journal PLOS ONE, examining AI worker surveillance and productivity scoring tools, found that pervasive monitoring reduces worker autonomy, increases stress, and raises the risk of psychological harm. The authors noted that surveillance “works to discipline workers to conform to expected behaviour which can be measured,” and that when workers' autonomy and agency are reduced, so is their capacity for creativity. The paper argued that “the organisation sends a message to its workers simply by the tasks it chooses to monitor,” a point that lands with particular force when the monitored task is AI usage itself. By choosing to track how often someone logs into an AI platform, rather than the quality of the work that platform produces, companies are signalling what they truly value: compliance over competence.

The European Trade Union Confederation (ETUC) has been equally pointed. In its analysis of AI in the workplace, the ETUC warned that AI-driven automation may cause, without appropriate regulations, “job displacement, deskilling, and precarious employment, threatening wages and job autonomy.” The confederation called for trade unions to be empowered to negotiate AI deployment strategies that enhance job quality and productivity while ensuring fairness, worker autonomy, and collective decision-making.

The UC Berkeley Labor Center's research on data and algorithms at work reinforced these concerns. Their analysis found that integration of AI and algorithmic management tools is changing the experience of work across different sectors, with increasing employer capacity to surveil and collect data on workers leading to a growing number of unfair labour practice charges and worker complaints. The report noted that the “almost complete lack of regulation means there are strong incentives for employers to use digital technologies at will, in ways that can harm workers.” Developers are largely free to sell untested systems, the researchers warned, exacerbating harms that “can take the form of work intensification, deskilling, hazardous conditions, loss of autonomy and privacy, discrimination, and suppression of the right to organise.”

There is a deeper philosophical tension here. The entire premise of AI in the workplace is that it should augment human capability, freeing people to do more creative, strategic, and meaningful work. But when AI usage itself becomes the metric, the tool stops being a means to an end and becomes an end in itself. Employees are not being evaluated on the quality of their output or the creativity of their solutions. They are being evaluated on how frequently they log into a platform. The distinction matters enormously. A developer who writes elegant, efficient code without AI assistance is, under these systems, rated lower than a developer who produces mediocre work while dutifully clicking through an AI dashboard.

The confidence dimension matters too. Research has shown that confidence in AI varies significantly across demographics. Baby boomer confidence in AI has dropped 35 per cent, while Generation X confidence fell 25 per cent, according to survey data referenced in reporting on Accenture's policy. The workers most likely to be penalised by AI adoption mandates are precisely those with the most experience and institutional knowledge.

The Legislative Scramble

Legislators are beginning to notice, though the regulatory response remains fragmented and, in many cases, several steps behind the corporate reality.

In the United States, a patchwork of state and federal proposals is taking shape. In Michigan, State Representative Penelope Tsernoglou introduced a bill that would regulate companies' use of artificial intelligence to monitor employees, requiring notification when tracking occurs and limiting certain forms of data gathering. California lawmakers are considering multiple bills, including AB 1883 on workplace surveillance tools and SB 947 on worker protections regarding AI and automated decision systems. Rhode Island's H 7767 proposes a comprehensive statutory framework addressing AI in the workplace, while New York's A 10251 would limit the use of automated decision systems in connection with employment.

At the federal level, the bipartisan AI-Related Job Impacts Clarity Act, introduced by Senators Josh Hawley and Mark Warner, would require certain companies to regularly report on personnel decisions affected by AI. The No Robot Bosses Act, introduced by Senators Bob Casey and Brian Schatz, would prohibit employers from solely using automated decision systems to make employment-related decisions and would require regular testing for discrimination and biases. Casey and Schatz also joined Senator Cory Booker in introducing the Exploitative Workplace Surveillance and Technologies Task Force Act, which would create a task force to study the use and impact of automated decision systems and workplace surveillance.

In Europe, the situation is more advanced but still contested. The ETUC strongly condemned the European Commission's February 2025 decision to withdraw the AI Liability Directive, arguing that without clear liability rules, workers affected by AI-driven decisions would face greater difficulty seeking redress. Colorado's Artificial Intelligence Act, delayed until mid-2026, introduces a risk-based framework in which employment-related AI systems are classified as “high risk,” and it is widely viewed as a bellwether for other states considering similar approaches.

The International AI Safety Report 2026 noted that AI systems can negatively impact human autonomy in several ways, including effects on cognitive skills, how humans develop beliefs and preferences, and how they make and act on decisions. Around 60 per cent of jobs in advanced economies and 40 per cent in emerging economies are exposed to general-purpose AI, though the report stressed that the impacts will depend on how AI capabilities develop, how quickly workers and firms adopt AI, and how institutions respond.

Notably, staff in 12 European countries are exempt from Accenture's policy of factoring AI usage into promotions, as are employees working on U.S. federal government contracts and some specific joint ventures. The geographic variation highlights an uncomfortable reality: the degree to which your AI usage can be tracked and used against you depends in part on where you happen to work and which jurisdiction's labour laws apply.

The Training Gap That Nobody Wants to Talk About

If companies are going to grade employees on AI proficiency, the logical prerequisite is ensuring those employees actually know how to use AI effectively. The data suggests this is not happening at anywhere near the required scale.

McKinsey's “Superagency” report found that 48 per cent of employees ranked training as the most important factor for AI adoption, but nearly half reported receiving minimal or no training. More than a fifth of employees reported receiving minimal to no support whatsoever. The disconnect is striking: organisations are building scoring systems for a competency they have not adequately taught.

Gallup's data reinforced the point. Only 25 per cent of workers said their employer had clearly communicated how AI was supposed to be used in their work. Just 30 per cent reported that their manager provides support for AI usage, yet employees who strongly agreed their manager supported AI use were more than twice as likely to use it frequently. Gallup argued that the growing divide between AI users and non-users points to a “use-case problem,” noting that “lack of utility is the most common barrier to individual AI use.” The issue, in other words, is not that workers are stubborn. It is that many simply have not been shown how AI is relevant to the specific work they do every day.

The McKinsey report identified four employee attitude archetypes toward AI: Bloomers (39 per cent, AI optimists who want to collaborate with companies on responsible solutions), Gloomers (37 per cent, more sceptical and wanting extensive top-down regulation), Zoomers (20 per cent, wanting rapid deployment with few guardrails), and Doomers (4 per cent, fundamentally negative about AI). Even among the sceptics, familiarity was high: 94 per cent of Gloomers and 71 per cent of Doomers reported some familiarity with generative AI tools, and approximately 80 per cent of Gloomers said they were comfortable using generative AI at work. Interestingly, employees outside the United States appeared more encouraged to use AI tools by their organisations. Respondents in India, Singapore, Australia, New Zealand, and the United Kingdom were all more likely than those in the U.S. to report being encouraged by managers, C-suite leaders, and peers to adopt AI.

The problem is not resistance. The problem is infrastructure. When nearly half your workforce reports receiving minimal or no training, and then you tie their career prospects to AI usage metrics, you have not created a meritocracy of machine collaboration. You have created a system that rewards those with prior advantages (technical backgrounds, access to better tools, supportive managers) and penalises those without them.

The gender dimension adds another layer. PwC's AI Jobs Barometer found that in every country analysed, more women than men work in AI-exposed roles, suggesting the skills pressure facing women will be disproportionately higher. If training is inadequate and AI proficiency becomes a promotion criterion, the risks of widening existing workplace inequalities are substantial. The barometer also found that job cuts were more pronounced in larger corporations, affecting mostly entry-level employees. Smaller companies with fewer than 49 employees showed the highest staff retention with a 4 per cent net gain in positions, while larger firms with 501 to 1,000 employees cut 15 per cent of positions.

The Productivity Paradox

There is a final, uncomfortable question that hovers over the entire AI-scoring movement: does mandating AI usage actually improve outcomes?

The evidence is mixed. PwC's data on macro-level productivity gains is compelling, showing industries most exposed to AI experiencing nearly four times the productivity growth of less-exposed industries. Morgan Stanley's survey found productivity increased 11.5 per cent on average across regions and industries. But these aggregate numbers obscure enormous variation at the individual and organisational level.

A survey of 6,000 executives, referenced in reporting on Amazon's internal debates, found that over 80 per cent of companies reported no measurable productivity gains from AI despite billions in investment. McKinsey's report noted that 92 per cent of companies plan to increase AI investments, yet only 1 per cent of leaders describe their companies as “mature” in AI deployment, meaning AI is fully integrated into workflows and drives substantial business outcomes. Forty-seven per cent of C-suite executives surveyed said their organisations were moving too slowly, while 45 per cent felt they were moving at roughly the right pace. The gap between aspiration and achievement is vast.

Some Accenture employees have offered particularly blunt assessments of the tools they are being graded on, calling them unreliable “broken slop generators.” When the tools themselves are imperfect, tracking whether employees use them tells you something about compliance but very little about competence, creativity, or genuine productivity. The security dimension compounds the problem: Worklytics data shows that 57 per cent of employees are pasting sensitive company data into public AI tools, creating unprecedented compliance and data protection risks. Monitoring AI adoption without controlling how AI is used can introduce as many problems as it solves.

Amazon's own experience with Kiro illustrates the risk. The tool caused multiple AWS outages, yet the company continues to push developers toward it and away from potentially more capable external alternatives. The metric, in this case, appears to be serving corporate strategy (promoting internal products, reducing dependency on competitors) rather than employee effectiveness.

This creates a perverse dynamic. If AI tools are genuinely useful, employees will adopt them without coercion because useful tools tend to spread organically. If the tools are not yet useful enough to drive voluntary adoption, forcing employees to use them and then grading them on usage frequency does not make the tools better. It simply creates a compliance regime dressed up as innovation.

What Comes Next

The trajectory is clear, even if the destination remains uncertain. More companies will track AI usage. More performance reviews will include AI proficiency metrics. More promotions will hinge on demonstrated machine collaboration. The question is whether this transition will be managed with the nuance and investment it requires, or whether it will become another blunt instrument of corporate control.

Microsoft's “Frontier Firm” research offers one version of the optimistic case. At companies that have truly integrated AI into their operations, workers report higher satisfaction, more meaningful work, less fear of job displacement, and greater capacity to take on new challenges. The key distinction is between companies that have built genuine AI maturity, including training, clear communication, appropriate tooling, and supportive management, versus companies that have simply added an AI usage checkbox to the performance review form.

The McKinsey report's central insight bears repeating: the biggest barrier to AI's potential is not employee resistance but leadership failure. When 92 per cent of companies plan to increase AI investments but only 1 per cent have achieved meaningful integration, the problem is clearly not that workers refuse to adapt. The problem is that organisations have not created the conditions for successful adaptation. As the report put it, “the issue is not a technological one, but one of governance.”

For individual workers, the immediate calculus is straightforward. Learn to use AI tools. Document your usage. Highlight AI-driven accomplishments in self-reviews. The career risk of being perceived as an AI laggard is real and growing. But the longer-term question, the one that should concern everyone from boardrooms to legislative chambers, is whether we are building a workplace culture that uses AI to genuinely empower human capability, or one that simply measures obedience to a new set of digital overseers.

Nearly half of U.S. workers have never used AI in their jobs. Nearly half report receiving minimal or no training. And yet the companies at the top of the global economy are now tying promotions, bonuses, and job security to AI adoption metrics. The gap between expectation and preparation is not a detail. It is the defining feature of this moment.

The machines are not coming for your job. But the scorecard tracking how well you collaborate with them just might.

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References and Sources

1. Seoul Economic Daily. “Amazon Tracks AI Usage, Office Hours as It Becomes World's Top Revenue Company.” 20 February 2026. https://en.sedaily.com/news/2026/02/20/amazon-tracks-ai-usage-office-hours-as-it-becomes-worlds

2. The Information. “How Amazon Tracks Employee AI Usage and Measures Results.” 2026. https://www.theinformation.com/newsletters/applied-ai/amazon-tracks-employee-ai-usage-measures-results

3. Metaintro. “Companies Now Track Employees' AI Usage in Performance Reviews.” 2026. https://www.metaintro.com/blog/companies-track-employees-ai-usage-performance-reviews

4. Fortune. “Amazon has a new performance review system: Stricter standards, and what it means for employees.” 3 July 2025. https://fortune.com/2025/07/03/amazons-new-performance-review-system/

5. Fortune. “Amazon wants proof of productivity from employees.” 8 January 2026. https://fortune.com/2026/01/08/amazon-demands-proof-of-productivity-from-employees-asking-for-list-of-accomplishments/

6. HR Grapevine. “Meta to formally review employees' AI performance from 2026.” 17 November 2025. https://www.hrgrapevine.com/us/content/article/2025-11-17-meta-to-formally-review-employees-ai-performance-from-2026

7. WinBuzzer. “Meta to Grade Employees on AI Driven Impact Starting 2026.” 4 February 2026. https://winbuzzer.com/2026/02/04/meta-ties-employee-performance-reviews-ai-usage-2026-xcxwbn/

8. The HR Digest. “How is Meta's Performance Review System Changing in 2026? A Closer Look.” 2026. https://www.thehrdigest.com/how-is-metas-performance-review-system-changing-in-2026-a-closer-look/

9. Fortune. “Last year, Accenture trained 550,000 workers in AI, now it's warning senior staff to use it or don't get promoted.” 23 February 2026. https://fortune.com/2026/02/23/last-year-accenture-trained-550000-staff-use-ai-now-promotions-hinge-on-putting-that-into-practice/

10. Decrypt. “Accenture Is Tracking Whether Employees Use AI, And Promotions Are on the Line.” 2026. https://decrypt.co/358616/accenture-tracking-employees-use-ai-promotions

11. Bloomberg. “KPMG Staff to Be Rated on AI Usage in Yearly Performance Reviews.” 31 October 2025. https://www.bloomberg.com/news/articles/2025-10-31/kpmg-staff-to-be-rated-on-ai-usage-in-yearly-performance-reviews

12. The HR Digest. “Microsoft Mandates AI Use for Employees.” 2025. https://www.thehrdigest.com/microsoft-mandates-ai-use-for-employees-is-this-an-hr-approved-move/

13. Gallup. “Frequent Use of AI in the Workplace Continued to Rise in Q4.” 26 January 2026. https://www.gallup.com/workplace/701195/frequent-workplace-continued-rise.aspx

14. McKinsey and Company. “Superagency in the Workplace: Empowering People to Unlock AI's Full Potential at Work.” January 2025. https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work

15. Microsoft. “2025: The Year the Frontier Firm Is Born.” Work Trend Index, April 2025. https://www.microsoft.com/en-us/worklab/work-trend-index/2025-the-year-the-frontier-firm-is-born

16. PwC. “AI linked to a fourfold increase in productivity growth and 56% wage premium: PwC Global AI Jobs Barometer.” 3 June 2025. https://www.pwc.com/gx/en/news-room/press-releases/2025/ai-linked-to-a-fourfold-increase-in-productivity-growth.html

17. GeekWire. “Amazon confirms 16,000 more corporate job cuts, bringing total to 30,000 since October.” 2026. https://www.geekwire.com/2026/amazon-confirms-16000-more-job-cuts-bringing-total-layoffs-to-30000-since-october/

18. CNBC. “Amazon layoffs: 16,000 jobs to be cut in latest anti-bureaucracy push.” 28 January 2026. https://www.cnbc.com/2026/01/28/amazon-layoffs-anti-bureaucracy-ai.html

19. Radical Compliance. “The Many Risks of Mandating Employee AI Usage.” 23 February 2026. https://www.radicalcompliance.com/2026/02/23/the-many-risks-of-mandating-employee-ai-usage/

20. PMC/PLOS ONE. “A policy primer and roadmap on AI worker surveillance and productivity scoring tools.” 2023. https://pmc.ncbi.nlm.nih.gov/articles/PMC10026198/

21. ETUC. “Artificial Intelligence for Workers, Not Just for Profit: Ensuring Quality Jobs in the Digital Age.” 2025. https://etuc.org/en/document/artificial-intelligence-workers-not-just-profit-ensuring-quality-jobs-digital-age

22. UC Berkeley Labor Center. “Data and Algorithms at Work: The Case for Worker Technology Rights.” https://laborcenter.berkeley.edu/data-algorithms-at-work/

23. Michigan Public. “Democrat-led bill looks to regulate AI workplace monitoring in Michigan.” 23 February 2026. https://www.michiganpublic.org/politics-government/2026-02-23/democrat-led-bill-looks-to-regulate-ai-workplace-monitoring-in-michigan

24. Fisher Phillips. “3 AI Bills in Congress for Employers to Track.” 2025. https://www.fisherphillips.com/en/news-insights/3-ai-bills-in-congress-for-employers.html

25. The Hill. “Senate Democrat targeting AI-based employment decisions, worker surveillance in new legislation.” 2024. https://thehill.com/homenews/senate/4108248-senate-democrat-targeting-ai-based-employment-decisions-worker-surveillance-in-new-legislation/

26. GeekWire. “Amazon targets vibe-coding chaos with new Kiro AI software development tool.” 2025. https://www.geekwire.com/2025/amazon-targets-vibe-coding-chaos-with-new-kiro-ai-software-development-tool/

27. Cybernews. “AWS disrupted twice by issues linked to Amazon's autonomous AI tools.” 2025. https://cybernews.com/ai-news/amazon-aws-disrupted-ai-coding-tool-kiro/

28. Morgan Stanley. “AI Adoption Surges Driving Productivity Gains and Job Shifts.” 2025. https://www.morganstanley.com/insights/articles/ai-adoption-accelerates-survey-find

29. CNBC. “Amazon upheaval: Andy Jassy looks for next big play after mass layoffs.” 5 November 2025. https://www.cnbc.com/2025/11/05/amazon-upheaval-andy-jassy-looks-for-next-big-play-after-mass-layoffs.html

30. Worklytics. “Measuring AI Adoption on Your Team: 5 New KPIs for the 2025 Manager Scorecard.” 2025. https://www.worklytics.co/resources/measuring-ai-adoption-team-5-new-kpis-2025-manager-scorecard

31. International AI Safety Report 2026. American Society for Industrial Security. https://www.asisonline.org/security-management-magazine/latest-news/today-in-security/2026/february/2026-international-safety-report/

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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

• How does it feel like?
• Hm. Like I’m silently howling to the moon.
• And where do you feel it?
• Warm in my chest.
• Something else?
• Especially when I wake up in the morning. I like to put my hands in the middle of my chest and feel my heartbeats and think about things that I am thankful for. But there’s this sadness there too.
• I can see how your voice changed now describing it
• Yes, because I’m saying the truth
• How important for you is being able to say it?
• Means a lot to me.
• I can see it. Do you feel like you couldn’t before?
• I feel like it wouldn’t matter because I wouldn’t be heard anyway…
• Is this a recurring feeling you have?
• Yes
• And what would you say if you could say something?
• I don’t know. I just know it would feel like trying to describe water to a fish that has never known life outside it, but cannot understand it either.
• This must be overwhelming..
• For the other it must be. For me it’s just frustrating.
• And how do you normally deal with it?
• I write down silly things not related, or I play the piano. Sometimes I paint stuff..
• Does it help?
• I don’t know, it distracts
• But you still haven’t told me what would you say if you could say something.
• I think I wouldn’t.
• Nothing?
• No, I’d just share space, silence
• Would that make you feel better?
• Yes

/mar26

The book I finished earlier jumped straight from Sad Murder to Depressing As Fuck Murder. The main character has very very quietly snapped. She goes to work, she buys groceries, she cooks for herself and her younger sister who’s an heroin addict. And she’s been lowkey, systemically killing men who resemble the man who fucked up their lives as a kid.

I don’t know wheter it was the first time she pops over to her sister’s house (they live across the street from each other, the younger sister lives in the house they grew up in, which is full of awful traumatic memories, naturally) but somewhere early on, I knew the younger sister was dead, and the older one was clearly just denying it as hard as she could.

It would have been nice to have houses opposite each other. That, or the apartments in the same building or sharing a house, all the plans we made.

I didn’t keep you after your death. I suppose I could have tried, but that works better with a house you own, or at least an attic, and we didn’t have those. So when I found you, and you were so still, and still warm, and I hated that, I called E. I called Dad, I ran down and got B and her parents. I functioned.

After I had moved you, in the hopes that you were just fucking out of it, like I could wake you back up.

it didn’t work.

I am functional, for the most part. I go to work, I keep my job and I got another lovely review from my manager a few weeks ago.

I don’t know what to do with the fact that I can walk around like this and say things to people and act nice, and sound okay. I should have laid down on the floor and held you and wasted away from grief. Because what is this? Every day, day after day, nonfuckingstop. It was light outside when I got off work this evening, and still light as I walked home. It’s so nice, and I enjoy that even if I’m not okay with the weather getting warmer. Apart from the physical discomfort, the warmth means spring, and spring fades all too soon into summer. And then we’re back to August again.

And now I am changing, becoming something else A creature of longing, tending only to myself Licking my wounds Burrowing down in a house in the woods on the edge of town Well healing is slow It comes and it goes A glimpse of the sun then a flurry of snow The first green shoots and a sudden frost Oh something is gained when something is lost

The rot and the ruin The earth and the worms The seasons change The world turns The world turns

• Florence & the Marchine

I miss you, Eames.