Who else cannot be distilled into skill?
Article | Sleepy.md
Unfortunately, in this day and age, the more wholeheartedly you work, the easier it is to distill yourself into a skill that can be replaced by AI.
These days, the hot search lists and media channels have been flooded with "colleague's skill." As this matter continues to ferment on major social media platforms, the public's focus is almost inevitably enveloped by grand anxieties such as "AI layoffs," "capital exploitation," and "the digital immortality of the working class."
While these are indeed anxiety-inducing, what makes me most anxious is a line in the project README document:
"The quality of raw material determines the quality of skill: It is recommended to prioritize collecting long-form content written proactively by the person> decision-making responses> daily messages."
Those most easily perfectly distilled by the system, pixel-perfectly reconstructed, are precisely those who work the most diligently.
It's those who, after every project concludes, still sit at their desks to write a post-mortem document; those who, when faced with disagreements, are willing to spend half an hour typing a long-form response in a chat box, candidly analyzing their decision-making logic; those who are extremely responsible, meticulously entrusting all work details to the system.
Diligence, once the most admired virtue in the workplace, has now become a catalyst for accelerating workers' transformation into AI fuel.
The Drained Worker
We need to redefine a word: context.
In everyday context, context is the background of communication. But in the world of AI, especially in the world of those rapidly growing AI Agents, context is the roaring engine's fuel, the pulsating blood, the only anchor that allows models to make precise judgments in the chaos.
An AI stripped of context, no matter how amazing its parameter count, is nothing more than an amnesiac search engine. It cannot recognize who you are, cannot grasp the undercurrent hidden beneath the business logic, and has no way of knowing the long tug-of-war and trade-offs you experienced on this network woven from resource constraints and interpersonal dynamics when finalizing a decision.
And the reason why "colleague's skill" has caused such a huge stir is precisely because it coldly and precisely locked onto that mountain of hoarded high-quality context — modern enterprise collaboration software.
Over the past five years, the Chinese workplace has undergone a quiet yet grueling digital transformation. Tools like Feishu, DingTalk, Notion, and others have become vast repositories of corporate knowledge.
Take Feishu as an example. ByteDance has publicly stated that the number of documents generated internally every day is massive. These densely packed characters faithfully encapsulate every brainstorm, every heated meeting, and every strategic compromise of over 100,000 employees.
This level of digital penetration far exceeds any previous era. Once upon a time, knowledge was warm, lurking in the minds of veteran employees, drifting through casual chats in the pantry. Now, all human wisdom and experience have been forcibly drained of moisture, ruthlessly precipitated in the cold server matrix in the cloud.
In this system, if you don't write documents, your work cannot be seen, and new colleagues cannot collaborate with you. The efficient operation of modern enterprises is built on the foundation of every employee day by day offering contextual contributions to the system.
Diligent workers carry diligence and goodwill, unreservedly laying bare their thinking paths on these cold platforms. They do this to ensure the team's gears mesh smoothly, to strive to prove their value to the system, and to desperately carve out a place for themselves within this intricate commercial behemoth. They are not voluntarily surrendering themselves; they are simply awkwardly and diligently adhering to the survival rules of the modern workplace.
Yet, ironically, this contextual information left for interpersonal collaboration has become the perfect fuel for AI.
Feishu's admin panel has a feature that allows super administrators to bulk export members' documents and communication records. This means that the project reviews and decision-making logic you spent three years working on during countless late nights can be easily packaged into a lifeless compressed file with just an API call in a matter of minutes.
When Humans Are Dimensionally Reduced to APIs
With the rise of "colleague.skill," some extremely uncomfortable derivatives have started to appear on GitHub's Issues section and various social media platforms.
Some have created "ex.skill," attempting to feed AI with chat records from WeChat over the past few years so that it can continue to argue or be tender in that familiar tone; others have created "unrequited love.skill," reducing untouchable palpitations to a cold interpersonal sandbox, repeatedly deducing probing dialogues, step by step seeking the optimal emotional outcome; and still others have created "paternalistic boss.skill," chewing on oppressive PUA rhetoric in the digital space in advance, constructing a sad psychological defense line for themselves.

The use cases of these skills have completely transcended the realm of work efficiency. Unconsciously, we have become accustomed to wielding the cold logic of tool treatment, dissecting and objectifying those once fleshy, lively individuals.
German philosopher Martin Buber once proposed that the foundation of human relationships boils down to two radically different modes: the “I-Thou” and the “I-It.”
In the encounter of the “I-Thou,” we transcend prejudices and regard the other as a complete and dignified living being to gaze upon. This bond is open without reserve, full of vibrant unpredictability, and precisely because of its sincerity, it appears particularly fragile; however, once plunged into the shadow of the “I-It,” the living person is reduced to an object that can be dismantled, analyzed, categorized, and labeled. Under this extremely utilitarian scrutiny, the only thing we care about is “What is the use of this thing to me?”
The emergence of products like “ex-skill” signifies that the tool rationality of the “I-It” has thoroughly invaded the most intimate emotional domain.
In a genuine relationship, a person is three-dimensional, full of wrinkles, constantly flowing with contradictions and nuances, and their reactions vary based on specific circumstances and emotional interactions. Your ex may react very differently to the same sentence when waking up in the morning compared to working late at night.
However, when you distill a person into a skill, what you strip away is merely the residual part of their functionality that happened to be “useful” to you and could “benefit you” in that specific bond. The once warm and self-experiencing individual is completely drained of their soul in this cruel purification, alienated into a “functional interface” that you can plug and play with at will.
It must be acknowledged that AI did not invent this chilling coldness out of thin air. Before AI emerged, we were already accustomed to labeling others, precisely measuring the “emotional value” and “social network weight” of each relationship. For example, in the dating market, we quantify a person’s attributes into grids; in the workplace, we classify colleagues as “capable” or “slackers.” AI just made this implicit, functional extraction between individuals blatantly explicit.
People have been flattened, leaving only that facet of “what is useful to me.”
Electronic Encapsulation
In 1958, Hungarian-British philosopher Michael Polanyi published “Personal Knowledge.” In this book, he introduced a highly penetrating concept: tacit knowledge.
In a famous dictum, Polanyi stated, "We know more than we can tell."
He gave an example of learning to ride a bicycle. A skilled cyclist, riding effortlessly, can perfectly balance in every gravity tilt, but he cannot precisely describe to a novice the subtle intuition of that moment in words or dry physics formulas. He knows how to ride, but he cannot articulate it. This type of knowledge that cannot be encoded or spoken is called tacit knowledge.
The workplace is full of such tacit knowledge. A senior engineer, when troubleshooting a system failure, may quickly pinpoint the issue by glancing at the logs, but he would find it challenging to document this "intuition" built upon thousands of trial-and-error instances. An excellent salesperson may suddenly fall silent at the negotiation table, and the sense of pressure and timing that silence brings is something no sales manual can capture. An experienced HR professional may, just by observing a candidate's half-second of avoiding eye contact, sense the exaggerations on the resume.
What "Colleague.skill" can extract is only that which has already been written down or spoken—explicit knowledge. It can scrape your postmortem documents but cannot capture your struggles while writing them; it can replicate your decision responses but cannot replicate the intuition behind your decision-making.
What the system distills is always just a person's shadow.
If the story were to end here, it would be nothing more than another poor imitation of humanity by technology.
However, when a person is distilled into a skill, this skill does not remain static. It is used to reply to emails, write new documents, make new decisions. In other words, these AI-generated shadows begin to generate new contexts.
And these AI-generated contexts are then deposited in Feishu and DingTalk, becoming the training materials for the next round of distillation.
As early as 2023, a research team from the University of Oxford and the University of Cambridge jointly published a paper on "model collapse." The research indicated that when an AI model is iteratively trained using data generated by other AIs, the distribution of the data becomes increasingly narrow. Those rare, marginal but highly authentic human traits are rapidly erased. After just a few generations of training on synthetic data, the model completely forgets the long-tail, complex real human data and instead outputs extremely mediocre and homogenized content.
In 2024, Nature also published a research paper stating that training future generations of machine learning models on AI-generated datasets would severely taint their outputs.

This is like those meme images circulated on the internet, originally a high-resolution screenshot that has been shared, compressed, and reshared by countless people. With each spread, some pixels are lost, and some noise is added. In the end, the image becomes blurry, digitally impasted.
When real human context with implicit knowledge is squeezed dry, and the system can only train itself on impasted shadows, what will be left in the end?
Who Is Erasing Our Tracks
What's left is only the right kind of nonsense.
When the river of knowledge dries up into an endless regurgitation and self-consumption of AI by AI, everything the system exhales will become extremely standard, extremely safe, but also irredeemably hollow. You will see countless perfectly structured reports, numerous flawlessly crafted emails, yet they will lack any human touch, devoid of any truly valuable insight.
The great defeat of knowledge is not because the human brain has become dull; the real tragedy is that we have outsourced the right to think and the responsibility to leave context to our own shadows.
Days after the explosion of "colleague.skill," a project called "anti-distill" quietly emerged on GitHub.
The author of this project did not attempt to attack big models or write any grand manifestos. They simply provided a small tool to help workers auto-generate seemingly reasonable but actually filled with logical noise invalid long texts on Feishu or DingTalk.
His purpose was simple: to hide his core knowledge before being distilled by the system. Since the system likes to fetch "actively written long texts," give it a bunch of nutritionless gibberish.
This project did not catch fire like "colleague.skill"; it even seemed a bit insignificant and feeble. Using magic to defeat magic still fundamentally revolves around the game rules set by capital and technology. It cannot change the trend of the system relying more and more on AI and increasingly overlooking real humans.
But this does not prevent this project from being the most tragically poetic and profoundly metaphorical scene in the entire absurd drama.
We work extremely hard to leave traces in the system, write detailed documents, make meticulous decisions, trying to prove our past existence in this vast modern corporate machine, proving our worth. Unaware that these very serious traces will eventually become the eraser that wipes us out.
But looking at it from a different perspective, this may not necessarily be a complete deadlock.
Because what the eraser wipes away is always just the "past you." A skill packaged into a file, no matter how sophisticated its scraping logic, is essentially just a static snapshot. It is frozen in that exported moment, relying only on stale nutrients, endlessly spinning in established processes and logics. It lacks the instinct to face unknown chaos and certainly does not possess the ability to self-evolve through real-world setbacks.
When we hand over those highly standardized, formulaic experiences, we also free up our own hands. As long as we continue to reach outward and constantly break and reconstruct our cognitive boundaries, that shadow resting in the cloud will forever only follow in our footsteps.
A human is a fluid algorithm.
You may also like

Japan’s Three Megabanks Plan Joint Stablecoin Issuance in Fiscal 2026
MUFG, SMBC, and Mizuho reportedly plan to jointly issue fiat-pegged stablecoins in fiscal 2026, signaling Japan’s growing push into bank-led digital payment infrastructure.

Humanity Discloses H Token Dual-Chain Attack Details, With Losses on Ethereum and BSC Exceeding $36 Million
Humanity said the H token attack across Ethereum and BSC caused more than $36 million in losses after leaked ProxyAdmin keys enabled malicious contract upgrades and token minting.

White House Discusses CLARITY Act With Law Enforcement Ahead of Senate Vote
The White House discussed the CLARITY Act with law enforcement ahead of a Senate vote, focusing on illicit finance risks and developer protections.

$75 billion in foreign capital has fled, and South Korean retail investors have absorbed it all using leverage

Bitcoin Trading Guide 2026: Strategies for Experienced Traders

What Is XAUT and PAXG? Why Tokenized Gold Is Booming in 2026

Cryptocurrency CEXs are flocking to sell US stocks, and traditional brokerages are facing an "uninvited guest."

Will the SpaceX IPO Hurt Bitcoin? Here's What Traders Are Watching

Foreign selling in the South Korean stock market accelerates, with cumulative net sales reportedly reaching $75 billion this year
On June 9, The Kobeissi Letter, citing Goldman Sachs data, reported that global investors are selling South Korean stocks at an unusually rapid pace. In the latest trading session, foreign investors sold about $801 million worth of Kospi constituent stocks again; total foreign outflows last week reached about $10 billion, and the market has been in net foreign selling on nearly every trading day over the past month. According to the data cited in the report, foreign investors have sold about $75 billion worth of South Korean stocks so far this year. Meanwhile, South Korean retail and institutional investors together recorded roughly $69 billion in net buying over the same period, suggesting that the market’s main buying support has come from domestic capital rather than returning overseas funds. The information currently disclosed still mainly comes from The Kobeissi Letter’s retelling and Goldman Sachs data summaries, while public details on the statistical period and the specific definition of “selling” remain relatively limited.

Fortune Warns of Strategy’s Financing Structure Risks as Bitcoin Premium Narrows
Fortune warned that Strategy’s Bitcoin treasury model faces growing financing risks as MSTR’s net asset premium narrows and preferred stock dividend pressure increases.

Ferrari Challenge Le Mans: Carl Moon to Dominate in WEEX Livery

Sahara AI Responds to SAHARA’s Sharp Drop: No Contract or Product Security Issues Found, Internal Investigation Underway
Sahara AI responded to SAHARA’s 60% price drop, saying no token contract or product security issues have been found and an internal investigation is underway.

WEEX Deposit/Withdrawal Dynamic Island: Your Asset Status, Always in Sight

Scaling Crypto Derivatives: The Digital Asset Infrastructure Behind High-Volume Trading
In the fast-moving digital asset ecosystem, derivatives platforms face an extreme architectural test. High-leverage futures markets demand more than just standard security—they require absolute operational precision, zero-latency matching engines, and ironclad structural scalability, all while navigating intense market volatility.
As global platforms scale to meet these demands, the industry is shifting away from rigid, monolithic setups toward a more agile, "decoupled" infrastructure philosophy.
The Blueprint for High-Volume Copy TradingFor elite global exchanges like WEEX (founded in 2018), this architectural choice becomes critical when scaling high-volume retail features like social copy trading. When thousands of users automatically mirror the real-time strategies of elite traders simultaneously, it triggers sudden, monumental spikes in concurrent transactional volume.
To prevent execution latency or settlement bottlenecks during these peak volatility events, a platform's primary engine must remain entirely dedicated to risk management, copy-trade synchronization, and order matching.
The Architectural Rule: New-generation platforms must separate front-end user execution engines from heavy backend infrastructural overhead to eliminate operational friction.
By separating these layers, platforms can maintain complete sovereignty over their trading environments and user experiences while strategically aligning with institutional-grade infrastructure ecosystems. This strategic framework allows modern exchanges to leverage advanced Digital Asset Custody infrastructure such as Cobo’s behind the scenes, ensuring that backend wallet management scales elastically alongside trading spikes.
Capitalizing on Market Momentum and 400× LeverageIn a derivatives arena where platforms offer up to 400× leverage on perpetual contracts, capital efficiency and market agility are core business metrics. To capture market momentum, an exchange needs the ability to rapidly expand its asset offerings, supporting everything from legacy crypto assets to sudden, trending altcoins across a massive library of trading pairs.
Adopting a flexible, scalable Wallet-as-a-Service (WaaS) solution such as Cobo’s could completely rewrite the development timeline for high-growth exchanges. Instead of spending months of engineering capital building out custom backend wallet architectures for every new blockchain network, platforms can deploy localized infrastructure in days.
This agility allows platforms to instantly scale their listings to over a thousand trading pairs without compromising security or delaying time-to-market. It mirrors the exact operational advantages seen during high-velocity market events, similar to how advanced wallet infrastructure empowers platforms during sudden asset surges; allowing exchanges to pass that speed and liquidity directly to their global user base.
A Mature Foundation for GrowthThe synergy between trusted infrastructure ecosystems and global trading platforms represents the natural evolution of a maturing crypto market. As WEEX continues to scale its global spot and derivatives offerings for over 6 million users, adopting robust backend paradigms proves that platforms no longer have to compromise between cutting-edge trading velocity and uncompromised structural security.

Morning Report | BitMine increased its holdings by 126,971 ETH last week; trader Eugene announced his exit from the crypto market

Wang Chuan: How can one not feel anxious after the neighbor Old Wang made thirty times profit by investing in storage stocks? (Seven) - A quarter-century cycle

Get Paid to Onboard? Try WEEX’s New Homepage with Rewards for Registration, Deposit & Trade

WEEX Custom Layout: Build Your Perfect Trading Workspace in Seconds
Japan’s Three Megabanks Plan Joint Stablecoin Issuance in Fiscal 2026
MUFG, SMBC, and Mizuho reportedly plan to jointly issue fiat-pegged stablecoins in fiscal 2026, signaling Japan’s growing push into bank-led digital payment infrastructure.
Humanity Discloses H Token Dual-Chain Attack Details, With Losses on Ethereum and BSC Exceeding $36 Million
Humanity said the H token attack across Ethereum and BSC caused more than $36 million in losses after leaked ProxyAdmin keys enabled malicious contract upgrades and token minting.
White House Discusses CLARITY Act With Law Enforcement Ahead of Senate Vote
The White House discussed the CLARITY Act with law enforcement ahead of a Senate vote, focusing on illicit finance risks and developer protections.
