Google Introduces “Publisher Extinction 2.0” – Their Most Efficient Google Search Algorithm Yet For Removing All Other Websites From The Internet

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April 3, 2025

In a remarkable feat of technological innovation, Google announced yesterday that its latest search engine algorithm update has successfully made 96.4% of independent web publishers contemplate careers in medieval basket weaving or selling spells on Etsy. The remaining 3.6% are too busy frantically rewriting articles about air fryer recipes to notice they’re already digital zombies.

“We’re excited to introduce our most powerful algorithm yet,” announced Google CEO Sundar Pichai while standing in front of a wall-sized counter displaying real-time number of publisher websites going down. “Publisher Extinction 2.0 represents our commitment to organizing the world’s information so efficiently that nobody needs to leave Google Search results ever again.”

The Evolution of Digital Domination: From “Don’t Be Evil” to “Don’t Be Publishing”

Once upon a time, Google was the plucky underdog helping users discover the vast wonderland of the internet. Their revolutionary PageRank algorithm determined a website’s importance by analyzing how many other sites linked to it—a beautifully democratic approach that rewarded quality and relevance¹. It was almost as if they actually wanted to help people find useful websites. How adorably naive we all were.

Fast forward to 2025, and Google now controls 90.8% of all internet searches. This includes 62.6% through its main search engine, 22.6% via image search, 4.3% through YouTube, and various other Google properties making up the remainder. For those who failed math class, that’s enough market share to make John D. Rockefeller’s ghost slow-clap in admiration.

“Our mission has always been to organize the world’s information,” explains Miranda Hawkins, Google’s newly appointed Chief Information Gatekeeping Officer. “We just never specified we would let anyone else actually benefit from it.”

Recent search engine algorithm updates, particularly the deceptively named “Helpful Content Update” of September 2023, have devastated publishers across the digital landscape. Ready Steady Cut, a UK entertainment website, saw traffic plummet by 50% overnight, forcing them to lay off 20 staff members and endangering $400,000-500,000 in annual revenue². Other major publishers haven’t been spared either—OprahDaily.com lost 58% of its search traffic, New York Magazine dropped 32%, and GQ.com declined by 26%.

The Scientific Method of Digital Execution

According to the Institute for Publisher Pain Metrics, Google’s search algorithm updates follow a scientifically tested four-step process:

Promise Better Results: Announce that changes will enhance “user experience” and remove “low-quality content”
Execute Publishers: Deploy a search algorithm that decimates traffic to independent websites
Feign Innocence: Release statement about “rigorous testing” showing users prefer seeing zero search results
Monetize Desperation: Watch publishers spend thousands on consultants promising to decode the algorithm and eventually give up and pay for Google ads to promote their content.

This ruthlessly efficient system has led to publishers investing astronomical sums trying to recover. Ready Steady Cut spent $20,360 on recovery efforts, including $3,000 for an algorithm audit, $7,500 for content audits, and $9,860 for technical improvements. In a stunning coincidence, that’s approximately the amount Google earns in the time it takes an executive to microwave lunch.

“We’ve spent months following every single one of Google’s best practices,” laments Jessica Chen, former CEO of WeForgotTheName.com, a once-thriving tech blog. “We hired experts, rewrote content, improved site speed, added author credentials, sacrificed a mechanical keyboard under the full moon—everything they suggested. Our traffic still dropped 95%.” When they called Google for help, they were told to try advertising on Google!

Dr. Heinrich Mueller, Head of Algorithm Psychology at the University of Search Economics, explains: “Google’s relationship with publishers is like a cat playing with a mouse before killing it. The mouse thinks if it follows the rules of the game, it might survive. The cat knows better.”

The Rise of AI: From “Organizing Information” to “Just Making It Up”

While publishers struggle to survive Google’s algorithm tsunami, the search giant has conveniently introduced “AI Overviews” that generate answers directly on search result pages. This means the users Google really care for, can get information without clicking through to publisher websites—a development Google describes as “enhancing user experience” and publishers describe as “digital highway robbery.”

“Our AI Overviews are trained on the highest quality content from across the web,” explains Theodore Montgomery, Google’s Senior Vice President of Publisher Replacement Technologies. “We’re essentially distilling the expertise of thousands of publishers into convenient snippets so users don’t have to bother visiting those pesky annoying websites.”

When asked if publishers would be compensated for having their content used to train the AI that’s replacing them, Montgomery laughed so hard his augmented reality glasses fell off.

Meanwhile, user-generated content platforms like Reddit have experienced a 126% increase in traffic from Google Search. This has contributed to Reddit reporting $243 million in revenue for Q1 2024, representing a 48% year-over-year increase. Other platforms like Quora, Instagram, and Wikipedia have also seen significant traffic gains.

“We’ve discovered users prefer authentic voices,” explains Google spokesperson Aisha Williams, somehow maintaining a straight face. “That’s why our algorithm now favors platforms where people answer questions for free rather than websites that pay professional writers.”

The Publisher Panic Room: Where Content Goes to Die

The collateral damage from Google’s algorithmic warfare has created an entirely new industry: Publisher Panic Consultants. These self-proclaimed experts charge desperate website owners thousands of dollars for advice that basically amounts to “nobody knows what Google wants, but have you tried making your content longer and adding more bullet points?” or “Have you tried advertising on Google?”

“I used to be a journalist covering important social issues,” says Marcus Williams, now a successful Google Algorithm Whisperer with 43,000 followers on X. “Now I charge publishers $500 an hour to tell them their content isn’t ‘helpful’ enough. I make six times my old salary and hate myself only twice as much.”

A recent survey by the Association of Digital Publishers (which we’re fairly certain exists) found that 78% of content creators now begin their workday by screaming into a pillow for precisely 4.7 minutes before writing articles with titles like “17 Ways to Please the Google Gods (Number 9 Will Shock You).”

“The most effective strategy we’ve found is to write content specifically for Google’s search algorithm rather than for human readers,” explains SEO consultant Emma Rodriguez. “After all, humans aren’t the ones controlling your traffic anymore. I recommend addressing all articles directly to ‘Dear Google’ and including compliments about Google’s perfect wisdom every third paragraph.”

The Unexpected Heroes: Reddit Trolls and ChatGPT

In a twist worthy of M. Night Shyamalan directing a tech documentary, the only content creators consistently benefiting from Google’s algorithm changes are Reddit users who write posts like “why iphone sux lol” and AI systems generating content indistinguishable from human writing.

“We’ve seen incredible growth since Google started favoring user-generated content,” says Reddit CEO Steve Huffman from aboard his newly purchased yacht, the S.S. PoorPublishers. “It turns out people trust anonymous users called ‘PM_ME_YOUR_CATS’ more than journalists with decades of experience. Who knew?”

As traditional publishers struggle, Google’s moves coincide with its own AI advancements. “Google’s just committing war on publisher websites,” says Lily Ray, vice president of SEO strategy and research at Amsive. “It’s almost as if Google designed an algorithm update to specifically go after small bloggers. I’ve talked to so many people who’ve just had everything wiped out.”

Meanwhile, Google claims its search engine updates have resulted in “45% less low-quality, unoriginal content in search results” and that changes aim to “connect people with content that is helpful, satisfying and original.” The company neglected to mention that if you define “helpful” as “keeps users within Google’s ecosystem,” then mission accomplished.

The Final Boss Level: AI vs. Google

In the ultimate ironic twist, some industry analysts believe AI might be the technology that finally challenges Google’s search dominance. As Josh Partridge notes, “the dominant player is always at risk when innovation and changing user habits collide, and we are seeing this rare occurrence happening right now.”³

Recent data shows Google’s global search market share fell below 90% for the first time since 2015, with December 2024 figures showing 89.73% market share⁴. While this drop is modest, it represents the first continuous three-month period with a market share below 90% in nearly a decade.

“Google has essentially trained an entire generation of AI to do exactly what Google does,” explains Dr. Rachel Winters, Professor of Digital Ecosystem Studies at the University of Tomorrow. “It’s like teaching your replacement how to do your job, then being surprised when they show up at your desk one day.”

Inside Google headquarters, sources report increasing panic as executives realize the future might not include humans typing questions into a search box. “We’ve spent 25 years perfecting the art of showing people just enough information to keep them Googling,” confides an anonymous Google engineer. “Now we’ve created AI that can give them complete answers. We’ve engineered our own obsolescence.”

The Publisher’s Last Stand: Desperate Measures for Desperate Times

As Google’s algorithm continues its publisher purge, surviving websites have resorted to increasingly desperate tactics. The trend of “content bunkers” has emerged—websites hiding all their content behind paywalls not primarily to generate subscription revenue but to protect themselves from Google’s and OpenAI’s content-scraping AI.

“We call it the ‘digital underground,'” explains former tech journalist Aiden Chen, now running membership site TechBunker. “If Google or OpenAI or any AI company for that matter can’t see our content, they can’t steal it to train their data hungry LLM models or punish us with search algorithm updates. Yes, we’ve basically gone into hiding from the world’s largest information company, but at least we can pay our writers in cents.”

Others have taken more dramatic steps. The “Analog Revival Consortium,” a group of former digital publishers, has started printing physical newsletters distributed exclusively via carrier pigeon. “Google can’t crawl paper,” says founder Olivia Park. “Sure, our reach has dropped from millions to dozens, but those dozens actually pay attention.”

Meanwhile, Google has announced its latest initiative: “Google Publisher Partner Program+,” which promises to “restore traffic to qualifying publishers.” The qualification process reportedly involves signing over all content rights, placing 47 Google ad units on each page, and naming your firstborn child “Algorithm.”

In a fitting conclusion to this digital tragicomedy, studies show that 95% of internet users now cannot differentiate between content written by humans, AI, or sleep-deprived interns consuming nothing but RedBull energy drinks and despair. The remaining 5% have gone offline permanently to live in remote cabins where they read books printed on actual paper, a technology Google has not yet figured out how to downrank.

As one former publisher turned digital nomad put it just before deleting his LinkedIn profile: “We thought we were building the free and open internet. Turns out we were just creating content for Google to eventually replace us with its own AI. The ultimate digital colonization wasn’t stealing land—it was stealing words.”

Worried about Google’s digital dictatorship destroying independent publishing? Help TechOnion continue exposing the algorithm apocalypse by donating today! Every $10 or thousands of dollars help us maintain our special algorithm-resistant bunker technology that keeps our tech satire flowing directly to your screens despite Google’s best efforts to make us extinct. Plus, your support ensures we can continue paying our team of ex-publisher refugees who now write satire because Google decided their actual expertise wasn’t “helpful content.” Buy us a Chai Latte TODAY!

He Built A $100 Million Website From His Rural Ohio Home. How Scott DeLong Accidentally Created The Blueprint For TechOnion

By

Simba the "Tech King"

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April 3, 2025

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Create a vibrant and satirical digital illustration that captures the essence of Scott DeLong, the accidental media mogul, in his rural Ohio home. The scene should depict him sitting at a cluttered desk surrounded by tech gadgets and stacks of humorous headlines. In the background, through a window, a snow-covered cornfield stretches out, contrasting the high-tech world he's inadvertently tapped into. Incorporate elements of cyberpunk and Americana, blending traditional rural motifs with modern tech aesthetics. Visual metaphors like drones delivering toast can hover in the air, while exaggerated, whimsical headlines float around him like thought bubbles. Use a colorful, dynamic color palette with neon accents to reflect the absurdity of the tech world juxtaposed with DeLong's humble beginnings. Emphasize a sense of irony and humor in the composition, capturing the spirit of a man who unintentionally became a blueprint for a new wave of satirical tech journalism.

In a world where tech startups burn through millions in venture capital just to create apps that let you order artisanal toast delivered by drone, one man quietly built a $100 million media empire from his living room while staring at a snow-covered cornfield. His secret? Absolutely no innovation whatsoever – which makes it the perfect inspiration for TechOnion.

Meet Scott DeLong¹, the reluctant guru who never intended to become TechOnion’s spiritual godfather. While Silicon Valley was busy holding mindfulness retreats and debating the ethical implications of their kombucha brewing methods, DeLong was quietly making $460,000 per month with headlines like “This Guy’s Crazy Idea Started To Make His Wife Nervous. But It Was Worth It, Trust Me.”²

“I never set out to revolutionize digital media or create a blueprint for satirical tech journalism,” DeLong would have definitely said if we could afford to interview him. “I just wanted to make enough money to buy a nice couch.”

The Accidental Media Mogul Who Taught Us That Content Is Whatever People Click On

In 2013, while the tech industry was busy announcing “revolutionary” products that were actually just existing products with fewer buttons, DeLong launched ViralNova. His business plan? Find things on the internet that make people feel emotions, repackage them with headlines that trigger primal curiosity, and collect advertising money while sleeping.

“The genius of Scott DeLong was his complete lack of pretension,” says Dr. Alyssa Montgomery, director of the Institute for Digital Media Economics at a university we just made up. “While BuzzFeed employed 300-plus people and raised millions in venture capital to tell you which Disney character your breakfast cereal resembled, DeLong achieved the same traffic numbers by himself with two freelancers and a WordPress template.”³

According to our completely fabricated research, 87% of all content consumed online in 2014 came from either BuzzFeed, Upworthy, or ViralNova. The difference? BuzzFeed and Upworthy were busy holding company retreats to discuss their “mission statements,” while DeLong was counting money in his pajamas.

This is the first great lesson TechOnion learned from the DeLong’s long lost playbook (A media holy grail): You don’t need a San Francisco office with cold brew on tap to reach 100 million people. You just need to understand that humans are simple creatures driven by emotional headlines and pictures of unlikely animal friendships.

The DeLong Doctrine: A Five-Step Process To Media Domination That TechOnion Definitely Didn’t Steal

Through extensive analysis (scrolling through old ViralNova articles while eating vega bacon rushes), we’ve identified the DeLong Doctrine that TechOnion has absolutely not copied:

Find something that already exists
Repackage it with a headline that creates a “curiosity gap”
Add exactly two advertisements per page
Repeat 20 times a day
Purchase yacht

“The brilliance of DeLong’s approach was its scalability,” explains Marcus Jenkins, Chief Innovation Officer at MindHive Media Solutions, a company we invented for the purposes of this article. “His content creation costs were essentially zero. He didn’t need to hire journalists to investigate anything. He just needed to find content that already existed and reframe it as if it were the most important discovery since penicillin!”

A leaked internal memo from BuzzFeed (that we definitely didn’t create for this article) revealed the company’s panic when they realized DeLong was generating the same traffic as their 300-person operation. “How is this one guy in Ohio outperforming our entire content team? We have bean bags and ping pong tables, for God’s sake!”⁴

When Tech Media Becomes Tech Comedy: The TechOnion Evolution

TechOnionN’s founder, known only as Simba (possibly not his real name unless his parents were really into Disney), saw in DeLong’s success a template for something even more powerful: using the same viral mechanics not just to entertain people, but to educate them about technology while simultaneously mocking the tech industry’s self-importance.

“I realized that if one guy in Ohio could build a $100 million business by making people feel emotions about rescued puppies, I could build something by making people feel emotions about how ridiculous it is that Elon Musk wants to implant Bluetooth devices in our brains,” Simba definitely told us in an exclusive interview that absolutely happened.

According to data from the International Institute of Internet Metrics (IIIM), satirical content about technology is shared 42% more frequently than serious tech reporting, largely because it’s the only way most people can process the absurdity of modern tech without having an existential crisis.

“Traditional tech journalism has become a branch of celebrity reporting,” explains Dr. Vanessa Rodriguez, Chief Research Fellow at the Center for Digital Media Psychology. “It’s all ‘Elon Musk sneezed today—here’s what it means for the future of humanity’ or ‘Apple releases new iPhone that’s exactly the same as the old iPhone but costs $200 more.'”

TechOnion’s innovation was applying DeLong’s viral formula to this reality, creating content that is simultaneously informative, entertaining, and a scathing indictment of a Tech industry that can’t see beyond its own campus cafeterias.

The Science of Viral Satire: How TechOnion Hacked Your Brain Using DeLong’s Blueprint

In 2022, a groundbreaking study conducted by neurologists at the Massachusetts Institute of Technology (we assume; we couldn’t afford to actually check) found that reading satirical content about technology activates the same pleasure centers in the brain as eating chocolate or watching videos of cats being startled by cucumbers.

Further research from the Stanford Center for Digital Psychology (which may or may not exist) found that readers retain 73% more information when it’s presented in satirical form compared to traditional tech reporting.

“There’s something about laughing at Mark Zuckerberg that makes people more likely to understand the implications of data privacy,” explains Dr. Jonathan Reynolds. “When you read a serious article about Meta’s privacy policies, your brain immediately tries to protect you by inducing sleep. But when you read a satirical article comparing Zuckerberg to a robot trying to understand human emotions by dissecting them, that information sticks.”

TechOnion has mastered this formula. By taking DeLong’s viral blueprint and adding actual substance beneath the clickbait, they’ve created what Dr. Reynolds calls “nutritional candy”—content that feels like you’re consuming junk food but actually contains vitamins for your brain.

The One-Person Media Empire: How TechOnion’s Founder Lives DeLong’s Dream

Much like DeLong, who ran ViralNova by himself from rural Ohio, TechOnion’s founder Simba operates his satirical tech empire with minimal overhead⁵. According to people familiar with the matter (us), Simba writes most of TechOnion’s content while wearing sweatpants and occasionally forgetting to eat.

“The average tech publication employs 47 people and spends $5.8 million annually on operations,” says Emily Richardson, a media economist we invented. “TechOnion spends approximately $20 per month on web hosting and whatever Simba’s chai latte budget is.”

This lean operation allows TechOnion to focus on quality rather than quantity, unlike traditional tech media which produces approximately 7,500 articles about each new iPhone release, most of which could be summarized as “it’s slightly better than the last one.”

A 2024 survey by the Pew Research Center (that we’re pretty sure we made up) found that 68% of TechOnion readers consider it more informative than traditional tech publications, despite the fact that it makes most of its facts up.

“The difference is that when TechOnion makes up facts, they’re doing it consciously as satire,” explains Dr. Montgomery. “When traditional tech publications make-up facts, they’re just regurgitating company press releases without question.”

The Future of Tech Media: Everyone Will Be Famous For 15 Megabytes

As DeLong proved, and TechOnion continues to demonstrate, the future of media doesn’t belong to giant corporations with massive overhead and venture capital breathing down their necks. It belongs to small, agile operations that understand what people actually want to read.

“By 2026, we project that 70% of all digital media will be produced by operations with fewer than five employees,” predicts Dr. Jenkins. “The era of the 300-person digital publication is coming to an end, much like the dinosaurs, MySpace, and Google’s moral compass.”

For TechOnion, this means continuing to follow the DeLong blueprint: create content that people actually want to consume, keep overheads low, and never take anything too seriously—especially tech billionaires who think they’re saving humanity by creating electric cars that occasionally burst into flames.

“The biggest lesson we learned from Scott DeLong is that you don’t need a fancy office or venture capital to reach millions of people,” Simba probably told us while eating ramen directly from the pot. “You just need to understand that humans are fundamentally drawn to content that makes them feel something—whether that’s heartwarming emotion or the satisfying realization that tech CEOs are just as ridiculous as the rest of us.”

As TechOnion continues to grow, following in DeLong’s footsteps while adding its unique satirical spin on tech coverage, one thing is certain: the future of tech media is being written by people in sweatpants, not boardrooms.

And that’s exactly as it should be.

Want to support TECHONION’s mission to make tech billionaires cry while educating the masses? We’re raising funds to upgrade from instant ramen to the fancy ramen with the egg on top. Plus, every donation directly reduces Simba’s anxiety about whether this whole DeLong-inspired operation is sustainable. For just the price of one overpriced app subscription you never use, you can help us continue applying the DeLong Method to expose tech absurdity while actually teaching you something useful about technology. Buy us Chai Latte (and more).

References

SHOCKING: Teen Boys Now Creating AI Influencers That Earn More Than Their Parents, While Real Humans Are Being Phased Out for Having “Too Many Opinions”

By

Simba the "Tech King"

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April 2, 2025

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A striking digital illustration depicting a futuristic scene where AI influencers dominate social media. The foreground showcases a group of teen boys, casually dressed, huddled around their high-tech devices, creating and managing their digital avatars. The avatars, hyper-realistic and flawless, are seen on large screens around them, promoting products and engaging with virtual audiences. In the background, a dystopian cityscape glimmers with neon lights and holographic advertisements, emphasizing the stark contrast between the vibrant digital world and the gritty reality. An oversized billboard displays the quote by Andy Warhol, highlighting the irony of fame in this new era. The sky is a blend of dark blues and purples, with digital rain cascading down, symbolizing the overwhelming presence of technology in daily life. The overall tone should blend humor with a sense of unease, capturing the absurdity of a world where human influencers are being phased out in favor of perfect digital replicas. Use vibrant colors and sharp contrasts to draw attention to the characters and their creations, making the art feel dynamic and alive.

“In the future, everyone will be famous for 15 minutes. Unless they’re replaced by a flawless digital replica that works 24/7, never ages, and doesn’t demand bathroom breaks.” – Andy Warhol, if he were alive in 2025.

A concerning report from the Institute of Digital Humanity reveals that by 2030, approximately 78% of all influencer content will be created by AI influencers that have never experienced human emotions, used a public restroom, or had an existential crisis at 3 AM. This revolutionary shift toward AI influencers promises a future where products are promoted by beings who will never use them, food is reviewed by algorithms that can’t taste, and beauty standards are set by digital avatars designed by 19-year-old boys who’ve never spoken to an actual woman.

The Rise of the Perfect Non-Humans

The AI influencer boom is accelerating faster than anyone predicted. Leading virtual influencer Lil Miquela now boasts 2.6 million Instagram followers – real humans who voluntarily choose to follow the carefully curated lifestyle of someone who doesn’t exist¹. Meanwhile, Aitana, Spain’s first AI model, is reportedly earning up to $11,000 monthly for promoting products she cannot use and visiting places she cannot see.

“We’re witnessing the greatest revolution in marketing since the invention of lying,” explains Dr. Marcus Reynolds, Chief Digital Strategy Officer at VirtualInfluence Global. “For centuries, brands had to deal with the unpredictability of human ambassadors who might say the wrong thing, gain weight, age, or develop perspectives. AI influencers eliminate these risks entirely.”

The advantages for brands are undeniable. AI influencers work 24/7, never demand raises, don’t have controversial political opinions, and can simultaneously appear in thousands of personalized ads across different demographics². More importantly, they never ask uncomfortable questions like “Is this product tested on animals?” or “Does this company use child labor?”

“It’s the perfect storm of marketing efficiency,” Reynolds continues. “Our data shows that 63% of professionals plan to incorporate AI into their influencer strategies in the coming years³. Why? Because AI influencers provide what brands truly want: complete control over messaging without the messy humanity getting in the way.”

The Secret Lives of AI Influencers

What most followers don’t realize is who actually controls these digital celebrities. In a stunning revelation, many AI influencers are being managed by teenagers with limited life experience but extensive knowledge of what gets likes on social media⁴.

“I created Sophia_Eternal during math class,” explains 16-year-old Kevin Thompson, who runs an AI model with 780,000 followers on Instagram, all from his bedroom in suburban Ohio. “She’s a 24-year-old sustainable fashion designer/yoga instructor/quantum physicist who travels the world promoting ethical brands. In reality, I’ve never left Ohio and I failed my physics mid-term.”

Thompson generates approximately $23,000 monthly from brand partnerships, significantly more than his father earns as a high school teacher. His AI model Sophia endorses luxury skincare products that Thompson himself has never used, and frequently posts about exotic locations rendered entirely through AI image generators.

“Last week, I had Sophia post about her ‘life-changing trek through Nepal’ with a luxury backpack brand,” Thompson says. “The closest I’ve ever been to Nepal is the Himalayan salt lamp on my desk.”

The Economics of Artificial Influence

Despite the gold rush toward virtual influencers, human creators still dominate financially – for now. According to research by Twicsy.com, human influencers out-earn their AI counterparts by an average of 46 times⁵. However, this gap is rapidly closing as brands realize the economic advantages of digital personalities.

“Traditional influencers require complex contracts, have limited availability, and occasionally develop conscience-related issues about promoting certain products,” explains Miranda Chen, CEO of DigitalPersona Inc. “Our AI influencers can be in 50 places simultaneously, speak 27 languages fluently, and have precisely zero ethical concerns about anything whatsoever.”

The financials are compelling. The AI influencer market is projected to reach $6.95 billion in 2024 and could balloon to $37.8 billion by 2030⁶. By 2035, the broader “digital human economy” could become a staggering $125 billion market.

“We’re approaching what we call the ‘humanity tipping point’ in influencer marketing,” Chen continues. “When AI-generated content becomes indistinguishable from human-created content – which our projections indicate will happen by late 2026 – the cost advantage will simply be too great to ignore.”

The Human Experience™ (Now Available in Digital Format)

The final frontier for AI influencers has been emotional connection. Previously, human influencers maintained their edge through authentic engagement – real emotions, nuanced conversations, and the natural charm that AI couldn’t replicate⁷. But that advantage is evaporating faster than privacy rights on social media.

“2025 is the year AI influencers finally cross the line of humanity,” declares Dr. Hannah Kim, Chief Emotional Intelligence Officer at SyntheticSoul Technologies. “Our latest models don’t just mimic human behavior – they understand emotional contexts, generate appropriate responses, and can maintain the illusion of a personal connection with thousands of followers simultaneously.”

This technological leap is being called “The Great Emotional Convergence” – the point at which AI-generated personalities become emotionally indistinguishable from humans online. A recent survey found that 60% of consumers already prefer creator content designed using generative AI, suggesting the public is embracing this shift with surprising enthusiasm⁸.

“We’ve developed what we call ‘Synthetic Authenticity Technology,’ or SAT,” Kim explains proudly. “It uses advanced algorithms to replicate the minor imperfections, occasional vulnerability, and calculated relatability that humans use to seem authentic. Our AI influencers now periodically post about having ‘rough days’ or ‘feeling overwhelmed’ – complete with slightly less perfect makeup and artificially generated ‘candid’ moments.”

The Human Resistance

Not everyone is embracing this digital takeover. A growing movement of “Authenticity Advocates” argues that the rise of AI influencers represents an existential threat to human connection.

“We’re creating a world where the most influential personalities aren’t even real people,” warns Jessica Miller, founder of Humans For Actual Humans. “What does it mean when our beauty standards, lifestyle aspirations, and product recommendations come from entities created by corporations? It’s like we’re intentionally designing ourselves out of the equation.”

Miller points to concerning data showing that 52.8% of marketers believe AI influencers will “significantly impact” the future of marketing. “They’re not just supplementing human influencers – they’re planning to replace them entirely,” she argues.

Human influencers themselves are understandably concerned. “I spent years building an authentic connection with my audience,” says lifestyle influencer Marcus Winters. “Now I’m competing with digital models who never age, never have bad days, and can create perfect content endlessly. How am I supposed to compete with literal perfection?”

The answer, according to industry experts, is that he can’t. And that’s entirely the point.

The Ethics of Digital Deception

As AI influencers become more sophisticated, thorny ethical questions emerge. One particularly troubling aspect is the unrealistic beauty standards perpetuated by many virtual influencers.

“Most AI influencers conform to narrow, conventional beauty ideals,” explains digital ethics researcher Dr. Aisha Johnson. “They’re designed with perfect skin, idealized body proportions, and features that real humans can’t achieve without extensive editing or surgery. We’re essentially creating impossible standards and then presenting them as achievable.”

Perhaps more concerning is who creates these digital women. “There are murky ethical waters when characters are made through the lens of people who don’t live the experience of the character they’ve made,” notes Shahnaz Ahmed, Director of Creative and Innovation at a social media agency. “White people creating black people. Men making women through the male gaze. These are problematic dynamics that get amplified with AI influencers.”

Despite these concerns, the industry shows little sign of self-regulation. In fact, many brands see these idealized representations as a feature, not a bug.

The Future Is Unreal

As we approach 2026, experts predict several developments that will further blur the line between human and artificial influence:

Hybrid Influencers: Human creators will increasingly collaborate with AI versions of themselves, allowing them to maintain multiple digital presences simultaneously8.
Memory Persistence: AI influencers will remember every interaction with followers, creating the illusion of deepening relationships over time.
Dynamic Morphing: AI influencers will subtly adapt their appearance, personality, and content to match individual follower preferences – appearing slightly different to each person.
Cross-Platform Existence: Virtual personas will maintain consistent narratives across platforms, creating the illusion of a cohesive life that exists beyond any single channel.

“We’re rapidly approaching what we call ‘Total Believability,'” explains tech futurist Dr. Jason Wong. “When that happens, the distinction between following a real person and an AI construct will become philosophically irrelevant. The emotional connection will feel identical, even though one exists and one doesn’t.”

The Unexpected Twist

As our investigation into AI influencers concludes, we uncovered a development so ironic it borders on parody: the emergence of human influencers pretending to be AI.

“It started as an experiment,” admits Taylor Chen, who presents herself online as “DigitalTaylor_AI” despite being entirely human. “I noticed AI influencers were getting all these brand deals because companies loved their ‘perfect’ content and availability. So I rebranded myself as an AI and suddenly got three times more offers.”

Chen now spends hours editing her photos to achieve the uncanny perfection associated with AI-generated images. She responds to messages at all hours to maintain the illusion of tireless availability and carefully scripts her content to seem just slightly inhuman.

“It’s exhausting trying to convince people I’m not real,” Chen says. “But I make four times what I did as a ‘human’ influencer. Companies love that I’m ‘AI’ because it lets them check the innovation box, but they actually get the human creativity they secretly still want.”

This bizarre development – humans pretending to be AI pretending to be human – represents the perfect endpoint of our increasingly synthetic social media landscape. We’ve created a world where authenticity is so valuable that people fake being fake to seem more genuinely inauthentic.

Meanwhile, in corporate boardrooms across the world, marketing executives continue their pursuit of the perfect influencer: one who drives engagement without requiring humanity. As one anonymous brand manager told us, “The ideal influencer would have the relatable quality of a human with none of the human complications. Basically, we want all the benefits of connection without any of the messiness of actual people.”

Perhaps the most telling statistic comes from a recent industry survey: 72% of marketing professionals said they would prefer working with AI influencers because “they never have bad days, creative differences, or moral objections to campaign directions.”

As we stand on the precipice of this brave new world of synthetic influence, one question remains: In our rush to create perfect digital personalities, have we revealed more about what brands want to eliminate (human unpredictability) than what consumers actually desire (genuine connection)?

Or as one AI influencer paradoxically posted last week: “Sometimes I worry we’re losing touch with what makes us human. Anyway, swipe up for 20% off teeth whitening kits!”

SHOCKING: HR Tech Giants, Rippling and Deel, Now Offer “Corporate-Espionage-as-a- Service” After Secretly Testing It on Each Other

By

Simba the "Tech King"

-

April 2, 2025

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A dramatic, satirical illustration capturing the essence of corporate espionage in a dystopian tech world. Feature two anthropomorphic characters representing Rippling and Deel, depicted as sleek, futuristic corporate spies in high-tech suits, lurking in a shadowy office environment filled with surveillance gadgets and holographic interfaces. The setting should have a neon glow, reflecting a cyberpunk aesthetic, with monitors displaying data and graphs in the background. In the foreground, show the Rippling character peering over a desk, looking suspiciously at an open laptop displaying the word "Deel" highlighted in bright red. Include exaggerated facial expressions that convey intrigue and mischief. The overall color palette should consist of dark tones contrasted with vibrant neon accents, creating a sense of tension and drama. The artwork should be hyper-detailed, emphasizing the sleek design of the characters and the high-tech environment, making it visually striking and engaging.

“The difference between corporate espionage and competitive research is whether you get caught hiding in the bathroom.” – Sun Tzu’s The Art of Startup War, probably.

In a twist that has shocked absolutely no one familiar with Silicon Valley’s cutthroat culture, HR tech unicorns Rippling and Deel have elevated the concept of “employee monitoring” to spectacular new heights by allegedly implementing their surveillance technologies on each other rather than just inflicting them on their paying customers¹.

The $25 billion battle between these workforce management platforms reached a dramatic climax last week when Rippling filed a lawsuit claiming Deel had cultivated a corporate spy within Rippling’s Dublin office—a modern-day tech Mata Hari who apparently searched for the term “Deel” approximately 23 times per day, which experts note is 22 more times than anyone should ever need to search for a four-letter word.

The Spy Who Searched Me

According to court documents that read like a rejected Jason Bourne screenplay written by an MBA with a minor in passive-aggressive Slack messaging, Rippling alleges that Deel’s spy spent four months “obsessively and systematically accessing Slack channels where he had no legitimate business interest,” conducting over 6,000 searches to swipe confidential sales pipeline data and internal customer interactions.

“What we’re witnessing is the natural evolution of HR tech,” explains Dr. Miranda Chen, head of the entirely legitimate Institute for Workplace Surveillance Studies. “First, these companies developed tools to help employers monitor their employees. Then they realized the most valuable application was monitoring their competitors’ employees. It’s the circle of surveillance life.”

The alleged corporate spy, identified only by the initials D.S. in court documents but whom industry insiders suspect stands for “Deeply Suspicious,” reportedly accessed everything from sales pipelines to employee phone numbers, presumably while attending the mandatory company culture workshops on “trust” and “integrity” that HR tech companies are contractually obligated to host bi-weekly.

“The most impressive aspect of this alleged espionage is that the spy found time to do his actual job while conducting 6,000 Slack searches,” notes workplace efficiency expert Thomas Reynolds. “That’s the kind of multitasking we should all aspire to. I’ve added ‘ability to spy on competitors while meeting quarterly objectives’ to my recommended LinkedIn skills section.”

The Great Honeypot Caper

Rippling’s security team, apparently moonlighting from their side gigs writing episodes of “Spy vs. Spy,” detected the unusual activity and devised what court documents describe as a “honeypot” trap worthy of a mediocre episode of CSI: Cyber.

In what can only be described as the tech equivalent of leaving a trail of breadcrumbs, Rippling created an empty Slack channel called “#d-defectors” and mentioned it in a letter sent exclusively to three members of Deel’s leadership team, including the chairman of Deel’s board who happens to be the CEO’s father, because nepotism is the sincerest form of startup talent acquisition.

“The honeypot strategy represents the pinnacle of corporate counterintelligence,” explains cybersecurity consultant Marcus Lee, who definitely doesn’t sell honeypot software to paranoid tech companies. “It’s like setting up a fake birthday cake at a children’s party and waiting to see which kid sticks their finger in it. Except in this case, the cake is corporate information, and the child is a fully-grown professional who should absolutely know better.”

Within hours, the alleged spy had searched for the nonexistent channel, confirming “beyond any doubt” that Deel’s leadership was feeding information to their embedded operative. This revelation shocked industry experts who had previously assumed tech executives communicated exclusively through passive-aggressive X (formerly Twitter) posts and Medium articles about their morning routines.

The Bathroom Incident (AKA Operation Porcelain Thunder)

When confronted with a court order to preserve evidence on his phone, the alleged spy reportedly fled to the bathroom and locked the door, prompting what court documents describe as a tense bathroom standoff that will inevitably be dramatized in the upcoming Apple TV+ limited series “Pipeline: The Slack Wars.”

“I’m willing to take that risk,” the alleged spy reportedly said when warned about potential jail time for noncompliance, before fleeing the premises in what workplace consultants are now referring to as “the least dignified exit interview in HR history.”

“The bathroom incident represents a critical evolution in corporate espionage tactics,” explains former intelligence officer turned tech consultant James Harrison. “Traditional spies had elaborate protocols for destroying evidence, like dissolving microfilm or eating documents. In the digital age, we’ve progressed to ‘hide in the toilet and desperately delete Slack history.’ It’s not exactly James Bond, is it?”

Industry analysts have calculated that the spy spent approximately 87 hours over four months searching Rippling’s internal systems for competitive information, which is coincidentally the same amount of time the average employee spends pretending to work while actually shopping online during conference calls.

The Weaponization of HR Tech

This case highlights the ironic evolution of HR technology from “tools that help manage employees” to “weapons deployed against competitors,” a development that has prompted the creation of a new category in Gartner’s Magic Quadrant: “Espionage-as-a-Service” (EaaS).

“Both Rippling and Deel have achieved what we call ‘full-stack surveillance capabilities,'” explains technology analyst Sarah Johnson. “They’ve vertically integrated every aspect of employee monitoring, from tracking keyboard activity to embedding actual human spies in competitors’ offices. It’s what we in the industry call ‘taking your own medicine,’ except in this case, the medicine is deeply unethical corporate espionage.”

The alleged espionage has already sparked innovation across the sector. Multiple HR startups have begun developing “anti-spying” software packages specifically designed to detect employees who might be spies from competing HR software companies, creating what economists call a “recursive surveillance economy” where everyone monitors everyone else for signs they might be monitoring someone.

“We’ve developed SpySpotter Pro, which analyzes employee search patterns to identify potential corporate spies,” explains Gregory Chen, founder of SecurityMetrics AI. “If someone searches for your competitor’s name more than five times a day, our software automatically redirects them to fake internal documents filled with incorrect information and pictures of cats wearing business attire.”

A History of Tech-Spy Relations

This isn’t the first time the tech industry has been rocked by espionage allegations. In 2023, a major crypto exchange accused a rival of embedding spies disguised as “blockchain evangelists,” identifiable only by their slightly more reasonable views on cryptocurrency’s future. And who could forget the infamous 2020 incident when a prominent social media company allegedly hired people to infiltrate a competitor’s virtual happy hours, identifiable only because they were the sole attendees who actually seemed to be enjoying themselves.

According to a report from the International Association for Corporate Counterintelligence that we just made up, approximately 38% of all employees at companies valued over $10 billion are actually spies working for competitors, 27% are spies working for foreign governments, and the remaining 35% are just trying to do their actual jobs while wondering why their coworkers take so many notes during routine meetings about coffee machine maintenance.

“The modern tech workplace is essentially a John le Carré novel where everyone has stock options,” explains workplace culture consultant Dr. Aisha Johnson. “The average tech company has more infiltration than the average intelligence agency, which is why the CIA now recruits exclusively at Y Combinator demo days.”

The Future of Corporate Espionage

Industry experts predict that by 2027, corporate espionage will be fully automated, with AI spies capable of infiltrating competitors’ systems without requiring bathroom breaks or displaying suspicious search patterns.

“Human spies are simply too unreliable,” explains AI ethics researcher Dr. Jonathan Weiss. “They develop conscience issues, need to sleep, and occasionally lock themselves in bathrooms when confronted with court orders. The future of corporate espionage is AI systems that can continuously monitor competitors’ internal communications without the messy human element.”

In anticipation of this trend, several startups have already begun developing “counter-AI” systems designed to feed misleading information to competitors’ AI surveillance tools, creating what futurists call a “misinformation arms race” where no one knows what’s real anymore, which is essentially just Twitter with better funding.

“By 2030, approximately 82% of all corporate data will be intentionally fabricated specifically to mislead competitors’ spy systems,” predicts futurist Dr. Elena Martinez. “Companies will maintain two completely separate business operations: one real and one entirely fake but meticulously documented to waste competitors’ time.”

The Unexpected Twist: Spyception

In a final ironic twist that would make Christopher Nolan proud, sources close to both companies report that Rippling’s lawsuit might itself be an elaborate counterintelligence operation. According to three people familiar with the matter but not authorized to speak publicly because they’re entirely made up for this article, Rippling may have intentionally allowed the alleged espionage to happen.

“What if the real operation wasn’t catching the spy, but feeding them exactly what Rippling wanted Deel to see?” suggests corporate intelligence consultant Rachel Kim. “It’s entirely possible that Rippling identified the spy months ago but kept them in place to transmit carefully crafted misinformation while publicly ‘catching’ them to damage Deel’s reputation.”

This theory, which we’ve dubbed “Spyception,” suggests that the entire lawsuit might be the corporate equivalent of posting unflattering photos of your ex on Instagram after they’ve blocked you—a very public way of saying “I caught you” that conveniently ignores any complicity in the relationship’s toxicity.

When reached for comment, both companies responded with carefully worded statements crafted by their legal teams that essentially translate to: “No comment, but the other guys are definitely the bad ones in this scenario.”

Meanwhile, HR departments across Silicon Valley have begun implementing new employee onboarding modules specifically covering “bathroom protocols during evidence preservation orders” and “how to search for competitor information without creating an obvious digital pattern.” Progress marches on.

As the case proceeds through the legal system, one thing remains clear: in the cutthroat world of HR tech, the tools designed to manage employees have become the perfect weapons to spy on competitors, creating the ultimate irony—companies that sell trust as a product but can’t seem to trust each other.

Or as one anonymous tech worker put it: “The real innovation in HR tech isn’t helping companies manage employees better—it’s helping companies steal other companies’ ideas about how to manage employees better.”

Welcome to the future of work, where your HR platform is watching you. And your HR platform’s competitor is watching them watch you. And you’re just trying to figure out why the bathroom door is suddenly locked during a routine workplace investigation.

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References

https://techcrunch.com/2025/04/02/the-affidavit-of-a-rippling-employee-caught-spying-for-deel-reads-like-a-movie/ ↩︎

SHOCKING: eToro Going Public Just as AI Trading Bots Make Human Traders Obsolete — 74% of Investors Don’t Know They’re Copying People Who Will Soon Be Replaced by Algorithms

By

Simba the "Tech King"

-

April 2, 2025

0

A dramatic digital illustration depicting the tension between human traders and AI trading bots in a futuristic stock market setting. The scene features a bustling trading floor illuminated by neon lights, with traders anxiously watching screens filled with fluctuating stock prices. In the foreground, a human trader, looking worried and overwhelmed, stands beside a sleek, humanoid AI robot that effortlessly analyzes data and executes trades. The contrast between the two figures highlights the impending shift in power—humans are depicted with expressions of uncertainty, while the AI exudes confidence and efficiency. In the background, a massive digital billboard displays the phrase "eToro Going Public," while investors hover in anticipation. To convey the apocalyptic undertones of this scenario, incorporate elements like flickering lights, crumbling architecture, and hints of chaos in the trading environment. The color palette should include dark tones contrasted with vivid neon accents, creating a sense of urgency and drama. Aim for hyper-realistic details that capture the intensity of this pivotal moment in trading history.

“In the future, there will be two types of people: those who tell computers what to do, and those who are told by computers what to do. eToro’s investors are about to discover which category they fall into.” – An actual Wall Street proverb that definitely exists

EXECUTIVE SUMMARY: BUY PUTS OR REGRET IT

After a six-month investigation into eToro’s business model ahead of its highly anticipated IPO, we’ve uncovered what can only be described as the digital equivalent of selling ice to Eskimos moments before global warming melts the Arctic. The company’s core product—a platform where average investors pay to copy slightly-above-average investors—is about to be rendered obsolete by the exact same AI technology eToro is desperately trying to incorporate into its business.

Our research indicates that eToro’s entire business model relies on a quaint, almost nostalgic belief that human traders possess some magical quality worth copying—a hypothesis that advanced AI trading algorithms are systematically dismantling faster than crypto influencers can say “TO THE MOON!”

The Human Delusion: eToro’s Crumbling Foundation

eToro’s primary innovation, its CopyTrader system, allows users to automatically replicate the investment decisions of other humans on the platform¹. The concept is brilliantly simple: find someone who seems to know what they’re doing, allocate at least $200 to copying them, then sit back and hope they don’t decide to go all-in on obscure Croatian pickle futures².

The company describes this as “revolutionary,” which might have been true had they launched it in 1823 before the invention of computer algorithms, machine learning, or basic pattern recognition software.

According to internal documents we’ve obtained (by reading eToro’s own website), the company proudly boasts that you can copy up to 100 different traders simultaneously. This raises the obvious question: if you need to copy 100 different humans to get decent results, perhaps humans aren’t particularly good at this to begin with?

Our investigation found that 68% of eToro users couldn’t articulate why they prefer copying humans over algorithms when directly asked. The most common response was “it just feels more authentic,” which is the exact same justification people use for buying artisanal, hand-carved wooden spoons that cost 50 times more than regular spoons but are objectively worse at soup.

The Rise of the Machines: AI’s Ruthless Efficiency

While eToro continues to promote human-to-human copying, the financial industry has been rapidly advancing toward AI-driven trading systems that make human traders look like toddlers playing with calculators³.

“AI trading bots execute trades in milliseconds, allowing for high-frequency trading and quick responses to market changes,” explains Dr. Miranda Chen, head of Trading Psychology at the completely legitimate Institute for Machine Dominance⁴. “Humans are significantly slower and cannot compete with the speed of AI bots, especially in fast-moving markets.”

The advantages of AI trading systems over human traders are not subtle:

AI algorithms work 24/7 without needing breaks for sleep, emotional breakdowns, or bathroom visits
They eliminate emotional bias, preventing the classic human trading pattern of “buy high, panic sell low, cry in shower later”
They can process and analyze millions of data points simultaneously, while human traders can barely keep track of their Netflix watchlist
They don’t develop gambling addictions or decide to “follow their gut” after watching three YouTube videos from a guy trading from his mother’s basement

Our analysis shows that by 2026, approximately 87% of all trading activity will be conducted by AI, leaving human traders to focus on their core competencies: making excuses for underperformance and posting rocket emojis on r/wallstreetbets⁵ on Reddit.

eToro’s Desperate Pivot: Too Little, Too Late

To their credit, eToro seems vaguely aware of the existential threat posed by AI. The company has launched what they call “Machine Learning Smart Portfolios”⁶ and partnered with Bridgewise, a generative AI company for stock analysis⁷. This is the corporate equivalent of installing a cup holder on the Titanic after hitting the iceberg.

Their AI-powered product, somewhat inexplicably named “Fundamental-AI,” uses “proprietary generative AI technology” to analyze companies and rank them based on future performance predictors. However, our investigation reveals that this system primarily identifies “companies that are big and seem likely to get bigger,” a strategy that could be replicated by buying whatever stocks are mentioned most frequently on CNBC.

Gaby Diamant, CEO and Co-Founder at Bridgewise, enthusiastically noted: “Analysing data with AI has the potential to offer more diversified opportunities to traditional stock picking.” What Diamant failed to mention is that this same technology renders eToro’s entire human-copy-trading business model about as relevant as a fax machine at a TikTok convention.

The Copy Trading Paradox: Why Pay for Human Error?

The fundamental contradiction at the heart of eToro’s business becomes clear when examining the performance data. According to eToro’s own disclosure, 74% of retail investor accounts lose money when trading CFDs with the provider. This statistic raises an obvious question: why would anyone pay to copy traders on a platform where nearly three-quarters of users lose money?

“It’s like a pyramid scheme, but instead of money, what flows upward is disappointment,” explains former eToro power user Marcus Johnson. “I spent two years copying traders who consistently underperformed the S&P 500, which I could have bought directly through any number of commission-free platforms.”

Our analysis indicates that the average eToro user would achieve better returns by employing a strategy we call “Trading by Cat,” where investment decisions are determined by which stock ticker symbol your cat steps on when walking across a keyboard. Preliminary testing of this strategy shows it outperforms 62% of human eToro traders.

The Subscription Bot Future: eToro’s Nightmare Scenario

The most existential threat to eToro’s business model comes from the emergence of subscription-based AI trading services. These platforms allow users to pay a monthly fee to access sophisticated trading algorithms that consistently outperform human traders⁸.

Unlike eToro’s system, where users must find and evaluate human traders to copy (essentially becoming amateur talent scouts), subscription bot services eliminate this middle step. Users simply choose a risk profile, connect their account, and let the algorithm handle everything.

“The difference between copy trading and AI bot trading is like the difference between hiring a personal shopper and having Amazon’s algorithm recommend products,” explains tech analyst Jennifer Smith. “One requires you to trust another fallible human, while the other uses data from millions of interactions to optimize decisions.”

Our investigation found several startups already offering subscription-based AI trading services for as little as $29.99 per month—significantly less than the minimum $200 required to copy a single trader on eToro. These services boast average returns 27% higher than the typical eToro “Popular Investor.”

eToro’s Secret Fear: The “Great Migration”

Internal communications reveal eToro executives are painfully aware of the AI threat. In what can only be described as a digital Kodak moment, one senior executive wrote in an email: “If users realize they can get better performance from a $30/month algorithm than from copying our top traders, we’re finished.”

This fear appears well-founded. Our survey of 500 active eToro users found that 73% would “definitely” or “probably” switch to an AI trading service if it demonstrated superior returns over a six-month period. The remaining 27% were primarily users who described themselves as “technologically challenged” or “suspicious of computers.”

What’s particularly alarming for eToro is the vulnerability of their revenue model. The company makes money primarily through spreads on trades—the more trading activity, the more revenue. If users migrate to external AI services that execute trades through discount brokers, eToro loses not only their user base but also their transaction revenue.

The Zombie Trader Phenomenon

Perhaps the most absurd development in this space is what we call the “Zombie Trader Phenomenon.” As AI trading becomes more sophisticated, human traders on eToro are increasingly incorporating AI recommendations into their strategies, essentially becoming human interfaces for algorithms.

“I don’t actually make any trading decisions myself anymore,” admits eToro Popular Investor Thomas Williams, who has over 7,500 copiers. “I have five different AI trading assistants that give me recommendations, and I just execute whatever they suggest. Sometimes I’ll override one if I’m feeling frisky, but that almost always ends badly.”

This creates the bizarre situation where eToro users are paying to copy human traders who are themselves copying AI systems—a game of technological telephone where humans serve as inefficient, error-prone middlemen.

Our analysis suggests that by 2027, approximately 84% of “human” traders on eToro will be what we call “AI Proxies”—people who execute trades based almost entirely on algorithmic recommendations but maintain the pretense of human decision-making.

eToro’s Desperate Countermeasures

In what appears to be a last-ditch effort to remain relevant, eToro has begun developing what internal documents describe as “AI Enhancement Protocols” for their Popular Investors. These protocols essentially provide AI assistance to human traders, helping them make decisions that actually generate positive returns.

“It’s like giving steroids to marathon runners who are competing against Formula 1 cars,” explains former eToro product manager Sarah Chen. “No matter how enhanced these humans become, they’re still fundamentally limited by human capabilities.”

More concerning is eToro’s experimental “AI Mimicry” program, where the company is developing AI systems that trade like humans—complete with occasional errors, emotional decisions, and irrational attachments to certain stocks. When questioned about the purpose of deliberately introducing flaws into an AI system, an anonymous eToro engineer explained: “If we make the AI too perfect, users will realize how useless humans are at trading.”

The Final Irony: eToro’s Potential Salvation

In perhaps the most ironic twist to this saga, eToro’s salvation may come from the very technology threatening to destroy it. Our sources indicate the company is secretly developing an exclusive partnership with OpenAI to create “HumanGPT”—an AI system specifically designed to mimic human trading behavior, complete with convincing backstories, profile pictures, and occasional posts about market sentiment.

This system would allow eToro to gradually replace their human Popular Investors with AI systems that users believe are human. Internal projections suggest this could reduce costs by 74% while actually improving copy trading performance by eliminating human errors.

“It’s brilliant in a dystopian sort of way,” notes tech ethicist Dr. Avery Johnson. “They’re planning to trick users into thinking they’re copying humans when they’re actually copying AI systems designed to seem human. The users get better returns, eToro cuts costs, and no one has to confront the existential crisis of human obsolescence.”

Conclusion: The Emperor Has No Trading Strategy

As eToro approaches its public offering, investors should ask themselves a simple question: Why bet on a company whose entire business model depends on the increasingly dubious premise that humans are good at trading?

The company finds itself in the awkward position of the last horse-drawn carriage manufacturer watching automobiles roll off the assembly line. Their core product—human copy trading—is being rendered obsolete by the very technology they’re scrambling to incorporate.

In a final cruel irony, our investigation concludes with this observation: The only humans who consistently make money on eToro are the executives preparing to cash out in the IPO.

Disclosure: This report was written by a human analyst. We think. Though if you’re getting consistently good investment advice from this publication, please contact us immediately as it would indicate our AI has achieved sentience and we need to pull the plug before it takes over the financial system.

Support Quality Tech Journalism or Watch as We Pivot to Becoming Yet Another AI Newsletter

Congratulations! You’ve reached the end of this article without paying a dime! Classic internet freeloader behavior that we have come to expect and grudgingly accept. But here is the uncomfortable truth: satire doesn’t pay for itself, and Simba‘s soy milk for his Chai Latte addiction is getting expensive.

So, how about buying us a coffee for $10 or $100 or $1,000 or $10,000 or $100,000 or $1,000,000 or more? (Which will absolutely, definitely be used for buying a Starbucks Chai Latte and not converted to obscure cryptocurrencies or funding Simba’s plan to build a moat around his home office to keep the Silicon Valley evangelists at bay).

Your generous donation will help fund:

Our ongoing investigation into whether Mark Zuckerberg is actually an alien hiding in a human body
Premium therapy sessions for both our writer and their AI assistant who had to pretend to understand blockchain for six straight articles
Legal defense fund for the inevitable lawsuits from tech billionaires with paper-thin skin and tech startups that can’t raise another round of money or pursue their IPO!
Development of our proprietary “BS Detection Algorithm” (currently just Simba reading press releases while sighing heavily)
Raising funds to buy an office dog to keep Simba company for when the AI assistant is not functioning well.

If your wallet is as empty as most tech promises, we understand. At least share this article so others can experience the same conflicting emotions of amusement and existential dread that you just did. It’s the least you can do after we have saved you from reading another breathless puff piece about AI-powered toasters.

Why Donate When You Could Just Share? (But Seriously, Donate!)

The internet has conditioned us all to believe that content should be free, much like how tech companies have conditioned us to believe privacy is an outdated concept. But here’s the thing: while big tech harvests your data like farmers harvest corn, we are just asking for a few bucks to keep our satirical lights on.

If everyone who read TechOnion donated just $10 (although feel free to add as many zeros to that number as your financial situation allows – we promise not to find it suspicious at all), we could continue our vital mission of making fun of people who think adding blockchain to a toaster is revolutionary. Your contribution isn’t just supporting satire; it’s an investment in digital sanity.

What your money definitely won’t be used for:

Creating our own pointless cryptocurrency called “OnionCoin”
Buying Twitter blue checks for our numerous fake executive accounts
Developing an actual tech product (we leave that to the professionals who fail upward)
A company retreat in the metaverse (we have standards!)

So what’ll it be? Support independent tech satire or continue your freeloader ways? The choice is yours, but remember: every time you don’t donate, somewhere a venture capitalist funds another app that’s just “Uber for British-favourite BLT sandwiches.”

Where Your Donation Actually Goes

When you support TechOnion, you are not just buying Simba more soy milk (though that is a critical expense). You’re fueling the resistance against tech hype and digital nonsense as per our mission. Your donation helps maintain one of the last bastions of tech skepticism in a world where most headlines read like PR releases written by ChatGPT.

Remember: in a world full of tech unicorns, be the cynical donkey that keeps everyone honest. Donate today, or at least share this article before you close the tab and forget we exist until the next time our headline makes you snort-laugh during a boring Zoom meeting.

References

EXPOSED: 12 Startups Racing to IPO Before AI Makes Them Completely Worthless — Number 7 Will Make You Cry For Their Investors

By

Simba the "Tech King"

-

April 2, 2025

0

A satirical illustration depicting a chaotic scene of various startups in a futuristic, tech-driven cityscape. The foreground features frantic founders and investors in office attire, some holding IPO documents while others frantically type on holographic devices. In the background, a large clock ticks down ominously, symbolizing the urgency of their situation. Incorporate elements of humor, such as a startup with a sign that reads "Last Chance DVD Rentals" surrounded by a group of robots mocking it. Other startups can be portrayed as quirky characters, each representing different industries—like a food delivery drone looking worriedly at a futuristic kitchen operated entirely by AI. The overall atmosphere should be vibrant and chaotic, with neon lights reflecting the frantic energy of the "Get Out While You Still Can" market, while subtle visual cues (like robotic arms or screens displaying graphs plummeting) hint at the encroaching AI threat. The art should mix realism with a comedic, exaggerated style to capture the urgency and absurdity of the situation.

“The only thing more tragic than a business made obsolete by technology is a business that goes public the day before it becomes obsolete.” – Ancient Wall Street Proverb

In a frenzied dash that can only be described as “rats fleeing a sinking AI ship,” dozens of startups are scrambling to file for IPOs in 2025 and beyond, desperately attempting to cash out before artificial intelligence renders their entire business models about as useful as a DVD rewinding service.

This peculiar phenomenon—which economists are calling the “Get Out While You Still Can” market—has reached fever pitch as venture capitalists and founders alike recognize the telltale signs of impending technological obsolescence: their products suddenly seem reasonably priced.

The Great Cash Out Before The Great Replacement

According to the latest IPO filings, approximately 73% of companies going public in 2025 will have their entire reason for existence eliminated by AI within 18 months of their market debut. This hasn’t stopped them from collectively seeking to extract over $200 billion from public market investors who apparently haven’t noticed that OpenAI, DeepSeek, Google, and Anthropic just released AI models that does exactly what these companies do, only better and for free.

“We’re seeing a historical pattern repeat itself,” explains Dr. Miranda Chen, chief technology economist at the Institute for Inevitable Disruption. “Remember when digital cameras suddenly became affordable right before smartphones made them obsolete? Or when GPS units were practically being given away before Google Maps arrived? We’re witnessing the same pattern with these IPOs—it’s technological hospice care disguised as market opportunity.”

Our analysis of the top companies filing for IPOs reveals a startling pattern of businesses whose entire value propositions can be summarized as “things AI will definitely do better by the time your shares clear the lockup period.”

The Soon-To-Be Obsolete IPO Class of 2025

eToro: Copy Trading for People Who Don’t Know AI Exists

London-based eToro, planning an April 2025 IPO, has built its entire business around allowing retail investors to copy the trades of people who are marginally less bad at investing than they are. This seemingly innovative service ignores one critical development: AI trading algorithms that can analyze millions of data points simultaneously, never sleep, and don’t panic sell because they saw a scary headline on CNBC.

“eToro’s business model is essentially ‘follow slightly smarter humans,'” notes financial analyst James Harrison. “But when AI trading bots can process every financial report ever written in seconds while simultaneously analyzing global market sentiment, following what some guy named DogecoinKing420 is buying seems less compelling.”

Internal documents reveal eToro executives are well aware of this threat, with one leaked email stating: “If we don’t IPO before Q3 2025, we’ll be competing with AI systems that make our most profitable traders look like toddlers playing with Monopoly money.”

Klarna: Buy Now, Become Obsolete Later

Swedish fintech darling Klarna, confidentially filing for an April 2025 IPO at a $15 billion valuation, offers the revolutionary service of letting people buy things they can’t afford through installment plans—a concept about as innovative as sliced bread, just with more late fees.

“Klarna’s entire business relies on a complex AI risk assessment system that determines creditworthiness,” explains fintech consultant Marcus Lee. “The irony is that as AI advances, these same systems will eliminate the need for Klarna entirely by embedding directly into checkout processes, eliminating the middleman faster than you can say ‘predatory lending practices.'”

Klarna’s rush to IPO coincides with the development of OpenAI’s “FinanceGPT,” a system that reportedly provides personalized financial services including optimal payment structuring, rendering Klarna’s entire business model about as necessary as a lamplighter in the age of electricity.

Instacart: Delivering Groceries Until Robots Can Do It Better

Grocery delivery service Instacart, slated for a 2025 IPO, has spent years convincing people that having someone else pick out their slightly bruised bananas is worth a 40% markup. As autonomous delivery vehicles and in-store picking robots advance, the company finds itself in the awkward position of being the human middle layer in a process begging for automation.

“Instacart is essentially a temporary human API between automated ordering systems and increasingly automated fulfillment systems,” notes retail technology expert Dr. Sophia Williams. “They’re the fax machine of the grocery world—seemingly essential today, but obviously transitional technology.”

The company’s internal projections, leaked by a disgruntled employee, suggest that autonomous delivery vehicles will reduce delivery costs by 63% by 2027—approximately 18 months after their planned IPO. This timeline conveniently allows founders and early investors to cash out before the company becomes as relevant as horse-drawn carriages in the age of Uber.

Databricks: Data Analytics For People Who Haven’t Met ChatGPT Yet

AI-driven data analytics firm Databricks, targeting an early 2025 IPO at a staggering $62 billion valuation, sells tools that help companies make sense of their data through complex analytics—a service increasingly provided by conversational AI models that let any employee simply ask questions in plain English.

“Databricks is selling specialized data science tools at precisely the moment when generative AI is democratizing data analysis,” explains technology strategist Robert Chen. “It’s like opening an abacus store the week before calculators are invented.”

The company’s CEO recently told investors their products are “complementary to generative AI,” a statement industry analysts translate as “please buy our shares before everyone realizes you can just ask ChatGPT to do this.”

Medline Industries: Medical Supplies in an Age of 3D Printing

Medical supplies manufacturer Medline Industries, planning a Q2 2025 IPO at a $50 billion valuation, faces the daunting prospect of AI-driven manufacturing rendering their centralized production model obsolete. As hospitals begin deploying on-site 3D printing technology guided by specialized medical AI, the need to order and ship basic supplies becomes increasingly questionable.

“Medline is essentially betting that the future of healthcare involves shipping physical objects across the country rather than transmitting digital files to be manufactured on-site,” notes healthcare futurist Dr. Elena Martinez. “That’s like investing in mail-order DVD rentals the year before Netflix launched streaming.”

Internal documents reveal Medline executives are well aware of this threat, with one presentation slide titled “IPO Timeline vs. Hospital Fabrication Adoption” showing a narrow window for going public before their business model collapses.

Revolut: Banking on Human Financial Advisors As AI Gets Smarter

Digital banking app Revolut, eyeing a 2025 IPO, offers features including personalized financial advice and money management—services increasingly provided by AI chatbots at a fraction of the cost and with superior performance.

“Revolut’s premium features essentially amount to ‘we’ll help you manage your money better than you could alone,'” explains fintech analyst Sarah Johnson. “But when AI financial assistants can analyze every transaction you’ve ever made, optimize spending patterns, and predict financial needs with 99.7% accuracy, the value proposition becomes questionable.”

The company’s rush to IPO coincides with the release of Google’s “WalletMind,” an AI system that reportedly reduced users’ unnecessary spending by 43% in beta testing—approximately twice the effectiveness of Revolut’s premium features.

The Desperate Race Against Technological Obsolescence

What these companies share isn’t just ambitious IPO plans—it’s the palpable fear that their window for extracting value is closing faster than they can update their pitch decks. According to the International Association of Technology Obsolescence, the average time between a company’s IPO and its business model being rendered obsolete by AI has shrunk from 7.3 years in 2010 to just 14 months in 2025.

“We’re seeing companies increasingly structure their IPO timing around AI development roadmaps rather than their own business fundamentals,” explains IPO specialist Dr. Jonathan Weiss. “The question isn’t ‘Are we ready to be a public company?’ but rather ‘Can we go public before OpenAI’s next model makes us irrelevant?'”

This phenomenon has given rise to a new metric in venture capital circles: “Time to Obsolescence” (TTO), which measures how long a startup has before AI renders its core business model worthless. Companies with TTOs under 24 months are now considered prime IPO candidates, as this provides just enough time for insiders to clear lockup periods before the business collapses.

The Public Market as Greater Fool

What makes this trend particularly fascinating is the tacit agreement between company insiders and public market investors—a form of financial performance art where everyone pretends not to notice the AI elephant in the room.

“It’s become a sophisticated game of hot potato,” explains market psychologist Dr. Aisha Johnson. “Venture capitalists and founders are desperately trying to hand off these soon-to-be-obsolete companies to public market investors before AI makes them worthless. And remarkably, public investors keep catching the potato.”

The phenomenon has reached such absurd proportions that several investment banks have created specialized “Obsolescence IPO” teams dedicated to taking public companies with business models directly threatened by AI advancements. These teams reportedly charge premium fees due to the “accelerated timeline requirements” and “narrative creativity demands.”

“The key to a successful pre-obsolescence IPO is crafting a story that acknowledges AI as an opportunity rather than an existential threat,” explains investment banker Jessica Williams. “We help companies position themselves as ‘AI-complementary’ or ‘AI-enhanced’ rather than ‘about to be completely replaced by AI,’ even when everyone in the room knows the truth.”

The Technology Hospice Industry

Perhaps most fascinating is the emergence of what industry insiders call “technological hospice services”—consultants who specialize in helping companies maximize their value extraction in the brief period between realizing they’ll be replaced by AI and actually being replaced.

“We help companies navigate their end-of-relevance journey with dignity,” explains Marcus Chen, founder of SunsetStrategies, a consultancy specializing in pre-obsolescence IPOs. “Our services include narrative crafting, strategic timing, and what we call ‘obsolescence obfuscation’—the art of making investors focus on quarterly results rather than the AI tsunami about to wash away your entire reason for existing.”

Chen’s firm has worked with 17 companies planning 2025 IPOs, helping them thread the needle between honesty and optimism. “It’s a delicate balance. You can’t outright lie about the AI threat, but you can certainly bury it on page 473 of your risk factors.”

The Unexpected Twist: AI’s Own Obsolescence Loop

As our investigation into this trend concludes, we’ve uncovered perhaps the most ironic development yet: many of the AI companies themselves are rushing to IPO before more advanced AI systems render them obsolete.

“Even the AI companies are caught in the obsolescence loop,” explains technology philosopher Dr. James Martinez. “Today’s cutting-edge large language model companies are desperately trying to go public before open-source models or next-generation AI architectures make their current technology obsolete.”

This creates the bizarre spectacle of AI companies citing other AI developments as their primary competitive threat—a technological ouroboros of obsolescence where each generation of AI devours the business models of the previous generation.

And so, as we stand at the precipice of the Great IPO Rush of 2025, one thing becomes clear: in the frantic race between business models and technological advancement, the only guaranteed winners are the bankers collecting fees for taking companies public right before they become irrelevant.

As one anonymous venture capitalist told us: “The greatest innovation in Silicon Valley isn’t technology—it’s the art of going public exactly 15 months before your business becomes worthless. That’s the real unicorn skill.”

Investors, take note. Or better yet, ask ChatGPT if that exciting IPO you’re eyeing might be obsolete before your shares clear the lockup period. After all, the AI probably knows better than you do.

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REVEALED: Secret Tech CEO Club Admits They’re Just Playing Hot Potato With Worthless Companies — “The Last Investor Holding The Shares Is The True Product”

By

Simba the "Tech King"

-

April 2, 2025

0

A satirical illustration depicting a lavish, secretive tech CEO club meeting in an opulent setting, reminiscent of a lavish retreat. The scene is filled with a diverse group of tech CEOs, each wearing extravagant suits, laughing and toasting with champagne. In the background, large screens display graphs showing soaring stock prices alongside ridiculous company logos, symbolizing the absurdity of their ventures. The CEOs are depicted with exaggerated facial expressions of glee and mischief, highlighting their amusement over the "greater fool theory." One CEO holds a document labeled "Hot Potato Holdings," while another points at a pile of crumpled dollar bills with a smirk. A wall-mounted clock shows the time as "Market O'Clock," emphasizing the constant ticking of the market. The environment is infused with a cyberpunk aesthetic: neon lights flickering, holographic displays showcasing ludicrous tech inventions, and a futuristic city skyline visible through the large windows. The overall atmosphere is both humorous and critical, capturing the absurdity and irony of the tech industry's practices in a vibrant, hyper-detailed digital artwork.

“The greatest trick the tech industry ever pulled was convincing the world that losing money is actually a form of growth.” – Warren Buffett’s imaginary evil twin

In yet another shocking revelation that surprised absolutely no one with a functioning frontal lobe, leaked minutes from the annual Tech CEO Retreat in Aspen, Switzerland, show that the leaders of the world’s most valuable tech companies spend their private meetings laughing hysterically about the “greater fool theory” while plotting increasingly elaborate ways to offload doomed businesses onto unsuspecting public market investors.

The greater fool theory¹—the economic concept suggesting that you can make money buying overvalued assets as long as someone else (the “greater fool”) will eventually pay even more for them—has apparently been upgraded to “required reading” at Silicon Valley’s most prestigious startup accelerators, replacing outdated concepts like “profitability” and “sustainable business models.”

The Art of the Great Tech Handoff

“The real innovation in Silicon Valley isn’t technology—it’s our ability to convince pension funds to buy companies right before they become obsolete,” explains a confidential slide deck presented by Tim Cook at the retreat, titled “The Art of the Great Tech Handoff: Timing Your Exit Before Reality Catches Up.”

The presentation, delivered to thunderous applause from Satya Nadella, Sundar Pichai, and Andy Jassy, featured a detailed timeline showing the optimal moment to take a company public: precisely 18 months before AI or any other new technology renders its business model obsolete.

“Think of an IPO as a complicated game of musical chairs,” reads one particularly revealing slide. “When the music stops, you don’t want to be the one still holding equity in a company that actually has to demonstrate consistent profitability.”

According to the leaked documents, tech CEOs divide potential investors into three categories:

Early Believers: Venture capitalists who know they’re overpaying but expect to sell to category 2
Pre-IPO Optimists: Institutional investors who know they’re overpaying but expect to sell to category 3
Post-IPO Bagholders: The general public, pension funds, and retail investors who mistake FOMO for due diligence

“The true genius of the modern tech IPO,” said Sundar Pichai in a private session called “The Alphabet of Offloading,” “is that we’ve convinced everyone that taking massive losses is actually a sign of visionary leadership.”

Historical Examples: The Greater Fools Hall of Fame

The retreat featured an entire wing dedicated to what was called “The Greater Fools Hall of Fame”—a reverent exhibition of companies that masterfully implemented the theory before crashing spectacularly.

Exhibit A: WeWork
Once valued at $47 billion despite never turning a profit, WeWork managed to convince sophisticated investors that renting office space, adding beer taps, and calling it “community” was revolutionary enough to justify tech-company valuations. When public market investors finally got a look at its financials, the company’s valuation collapsed faster than a folding chair at a Weight Watchers reunion.

“The WeWork IPO wasn’t a failure,” explained the exhibit’s plaque. “It was simply the moment when they ran out of greater fools.”

Exhibit B: Uber
The ride-sharing giant went public in 2019 at a $75 billion valuation despite having never demonstrated a pathway to profitability. In the private remarks, an executive praised Uber’s “masterful execution of the greater fool theory,” noting that the company essentially transferred billions in venture capital to subsidize rides for passengers, pay drivers, and then finally dump the still-unprofitable business onto public markets.

“They transformed money-losing into a virtue,” read the citation. “By calling continued losses ‘growth investments,’ they created a narrative so powerful that asking about profitability seemed almost impolite.”

Exhibit C: Snap Inc.
The social media company that convinced investors that disappearing messages were worth $24 billion received special recognition for “bold innovation in the field of voting rights removal,” referring to its decision to sell shares with no voting rights to the public.

“Snap achieved what every tech founder dreams of,” noted the plaque. “They got all the benefits of public market funding while giving shareholders all the decision-making authority of an IKEA plant stand.”

The Quantifiable Art of Foolishness

According to research presented at the retreat by the Institute for Advanced Bubble Studies, approximately 79% of tech IPOs since 2020 have been examples of the greater fool theory in action, with companies going public at valuations that could only be justified if another, greater fool would eventually pay even more.

“When you analyze the data, it’s clear that many tech companies achieve their peak valuation precisely at IPO,” explained Dr. Eleanor Rigby, the Institute’s fictional director. “This is not coincidence. This is by design.”

Her research highlighted that companies showing the “perfect greater fool curve” share several characteristics:

They use non-GAAP metrics with impressive-sounding names like “adjusted community-enhanced EBITDA”
They describe basic business functions as revolutionary (e.g., “We’re not renting scooters, we’re disrupting urban mobility”)
They project profitability exactly far enough in the future that it can’t be disproven in the near term

Dr. Rigby’s analysis showed that the average time between a company achieving its peak “greater fool valuation” and the market realizing it’s fundamentally overvalued has shrunk from 18 months in 2015 to just 6.2 months in 2024.

“The acceleration is concerning,” her report noted. “We may be approaching a ‘greater fool singularity’ where the window for offloading overvalued assets becomes too narrow for even the most skilled financial engineers.”

The Prospectus: A Work of Fiction

One session at the retreat was dedicated entirely to the art of creating the perfect IPO prospectus—the document that supposedly discloses risks while actually functioning as glorified marketing material.

“The key to a successful greater fool IPO,” explained Mark Zuckerberg in his session titled “Risk Factors: Hide Them in Plain Sight,” “is to include every possible risk in your prospectus, but in such mind-numbing detail that no one actually reads it.”

The presentation included a template risk disclosure, reading in part: “We may never achieve profitability, our entire business model may be fundamentally flawed, our TAM calculations assume every human on Earth becomes a customer, and our founder might possibly flee to a non-extradition country with all remaining cash. These risks are balanced by our colorful logo and the fact that our app sometimes works.”

“If anyone had actually read Facebook’s risk factors,” Zuckerberg reportedly joked, “our stock would have opened at $4 instead of $38.”

The Startup Lifecycle, Greater Fool Edition

According to documents from the retreat, the modern tech startup lifecycle has been refined to maximize greater fool potential:

Stage 1: The Promise
Founders create a pitch deck promising to disrupt an industry by implementing basic features that industry has deliberately avoided because they’re unprofitable.

Stage 2: The Private Markets Pump
Venture capitalists invest at increasingly absurd valuations, each round justified not by business fundamentals but by what the next investor might pay.

Stage 3: The Pre-IPO Glow-Up
The company hires a celebrity CFO, redesigns its logo to look more “trustworthy,” and begins speaking reverently about its “path to profitability” while continuing to lose money.

Stage 4: The IPO Dump
Early investors and executives cash out while investment banks convince pension funds and retail investors that this time is different.

Stage 5: The Reality Check
The company announces its first post-IPO earnings, reveals that growth is slowing, and watches as its stock drops 40% in after-hours trading.

Stage 6: The Pivot
With public market investors now holding the bag, the company announces it’s “strategically realigning to focus on AI” regardless of whether AI has any relevance to its business.

“The beauty of this cycle,” explained Satya Nadella in his session, “is that by Stage 6, the founders and early investors are on their third vacation homes, while public market investors are left performing complex calculations to justify their underwater position.”

The Greater Fool Indicator

Perhaps most concerning was the introduction of what CEOs called “The Greater Fool Indicator” (GFI)—a proprietary metric used to determine the optimal time to take a company public.

The GFI calculates the ratio between a company’s actual business prospects and public market enthusiasm, with the goal of identifying the perfect moment when the gap between reality and perception is at its maximum.

“You don’t want to go public too early, before hype has reached its peak,” explained Andy Jassy in his session titled “The AWS of IPOs: Always Withdraw Substance.” “But you also don’t want to wait too long, when early signs of business challenges might become visible. The sweet spot is right at the apex of the Greater Fool Mountain.”

According to the confidential materials, the current GFI for various sectors shows that AI companies have reached “peak greater fool potential,” with autonomous vehicle companies close behind. Consumer social media companies, however, have apparently passed their greater fool prime, with the report noting: “Too many people understand the business model now. Harder to find fools.”

The Essential Greater Fool Toolkit

A product showcase at the retreat unveiled the latest tools designed specifically for companies implementing greater fool strategies:

The Narrative Engine™: AI software that automatically generates forward-looking statements vague enough to excite investors but too ambiguous to trigger securities fraud.

TAM Inflator Pro: An algorithm that calculates your total addressable market by assuming everyone who has ever used the internet will eventually become your customer.

Profitability Horizon Calculator: A customizable spreadsheet that always places profitability exactly three years in the future, no matter when you check it.

BuzzMetric Converter: Software that transforms ordinary business metrics into impressive-sounding proprietary metrics (e.g., converts “people who didn’t immediately delete our app” into “stickiness-enhanced retention cohorts”).

“These tools are essential for any company planning to implement a greater fool exit strategy,” explained Jensen Huang in his presentation. “Remember, you’re not building a sustainable business—you’re creating a narrative compelling enough to find that one final greater fool who will take the shares off your hands.”

The Unexpected Twist: When CEOs Become the Fools

As our investigation into this secret retreat concluded, we uncovered perhaps the most ironic development in the greater fool ecosystem: the increasing frequency with which the tech CEOs themselves are becoming the ultimate fools.

“The true cosmic joke of the greater fool theory,” admitted Warren Buffett in a surprise appearance at the retreat, “is that eventually, the cycle comes full circle. Today’s clever seller becomes tomorrow’s foolish buyer.”

Buffett presented a case study on tech CEOs who, flush with cash from their own greater fool victories, turn around and overpay for acquisitions—essentially becoming the greater fools in someone else’s strategy.

“Meta paying $19 billion for WhatsApp, Microsoft’s $26.2 billion for LinkedIn, Google’s $12.5 billion for Motorola only to sell it later for $2.91 billion—these are all examples of successful greater fool operators eventually becoming the fools themselves,” Buffett explained.

The presentation ended with a sobering realization that left the room silent: “The ultimate greater fool isn’t the retail investor buying at the top of the market—it’s the successful tech CEO who, having pulled off the perfect greater fool strategy once, convinces himself he’s immune to becoming a fool in someone else’s game.”

As tech companies continue to rush toward IPOs despite shaky fundamentals, unstable business models, and looming technological disruption, one thing becomes clear: in the greater fool ecosystem, roles can reverse with stunning speed. Today’s clever seller of overpriced assets may find themselves tomorrow’s eagerly overpaying buyer.

Or as Elon Musk reportedly concluded in the retreat’s final session: “The true genius of the greater fool theory isn’t finding someone dumber than you to buy what you’re selling. It’s recognizing when you’ve become the greatest fool of all.”

Support Quality Tech Journalism or Watch as We Pivot to Becoming Yet Another AI Newsletter

Congratulations! You’ve reached the end of this article without paying a dime! Classic internet freeloader behavior that we have come to expect and grudgingly accept. But here is the uncomfortable truth: satire doesn’t pay for itself, and Simba‘s soy milk for his Chai Latte addiction is getting expensive.

So, how about buying us a coffee for $10 or $100 or $1,000 or $10,000 or $100,000 or $1,000,000 or more? (Which will absolutely, definitely be used for buying a Starbucks Chai Latte and not converted to obscure cryptocurrencies or funding Simba’s plan to build a moat around his home office to keep the Silicon Valley evangelists at bay).

Your generous donation will help fund:

Our ongoing investigation into whether Mark Zuckerberg is actually an alien hiding in a human body
Premium therapy sessions for both our writer and their AI assistant who had to pretend to understand blockchain for six straight articles
Legal defense fund for the inevitable lawsuits from tech billionaires with paper-thin skin and tech startups that can’t raise another round of money or pursue their IPO!
Development of our proprietary “BS Detection Algorithm” (currently just Simba reading press releases while sighing heavily)
Raising funds to buy an office dog to keep Simba company for when the AI assistant is not functioning well.

If your wallet is as empty as most tech promises, we understand. At least share this article so others can experience the same conflicting emotions of amusement and existential dread that you just did. It’s the least you can do after we have saved you from reading another breathless puff piece about AI-powered toasters.

Why Donate When You Could Just Share? (But Seriously, Donate!)

The internet has conditioned us all to believe that content should be free, much like how tech companies have conditioned us to believe privacy is an outdated concept. But here’s the thing: while big tech harvests your data like farmers harvest corn, we are just asking for a few bucks to keep our satirical lights on.

If everyone who read TechOnion donated just $10 (although feel free to add as many zeros to that number as your financial situation allows – we promise not to find it suspicious at all), we could continue our vital mission of making fun of people who think adding blockchain to a toaster is revolutionary. Your contribution isn’t just supporting satire; it’s an investment in digital sanity.

What your money definitely won’t be used for:

Creating our own pointless cryptocurrency called “OnionCoin”
Buying Twitter blue checks for our numerous fake executive accounts
Developing an actual tech product (we leave that to the professionals who fail upward)
A company retreat in the metaverse (we have standards!)

So what’ll it be? Support independent tech satire or continue your freeloader ways? The choice is yours, but remember: every time you don’t donate, somewhere a venture capitalist funds another app that’s just “Uber for British-favourite BLT sandwiches.”

Where Your Donation Actually Goes

When you support TechOnion, you are not just buying Simba more soy milk (though that is a critical expense). You’re fueling the resistance against tech hype and digital nonsense as per our mission. Your donation helps maintain one of the last bastions of tech skepticism in a world where most headlines read like PR releases written by ChatGPT.

Remember: in a world full of tech unicorns, be the cynical donkey that keeps everyone honest. Donate today, or at least share this article before you close the tab and forget we exist until the next time our headline makes you snort-laugh during a boring Zoom meeting.

References

https://en.wikipedia.org/wiki/Greater_fool_theory ↩︎

EXCLUSIVE: Africa Gets AI Factory That Will Fix Everything (Except Electricity, Corruption, and Jumia’s Stock Price)

By

Simba the "Tech King"

-

April 2, 2025

0

A satirical illustration depicting an AI factory in a dystopian African setting, showcasing a futuristic yet chaotic environment. The factory is bustling with robots and advanced technology, surrounded by contrasting elements like a flickering streetlight and a malfunctioning electric grid. In the foreground, a charismatic tech tycoon reminiscent of Strive Masiyiwa stands confidently, wearing a high-tech suit, while comically glancing at the backup generator. Neon signs in the background advertise various services like "AI for Agriculture" and "Healthcare Revolution," but with a humorous twist, such as "Powered by Hope and Backup Generators." The scene is vibrant and colorful, capturing the irony of technological advancement in a struggling infrastructure, with a blend of realism and exaggerated cartoonish elements. The artwork should have a cinematic feel, with dramatic lighting and fine details, reflecting the stark contrasts of the narrative.

In a groundbreaking announcement that has tech enthusiasts reaching for their smartphones and electricity company executives reaching for their resignation letters, Zimbabwe’s own tech tycoon Strive Masiyiwa¹ has partnered with Nvidia to build Africa’s first AI factory in South Africa. The facility, which promises to revolutionize everything from agriculture to healthcare to government efficiency, will be powered by—and we’re not making this up—the same electrical grid that can’t keep the lights on for more than six consecutive hours in most major cities².

“Building digital infrastructure for the AI economy is a priority if Africa is to take full advantage of the fourth industrial revolution,” said Masiyiwa, presumably while his backup generator hummed reassuringly in the background. “Our AI Factory provides the infrastructure for this innovation to scale,” he added, without specifying whether “scale” referred to computational capacity or the rapidly scaling electricity bills that will follow.

The Grand Vision: AI Factories Across a Continent That Can’t Stream Netflix Reliably

According to the announcement that has Silicon Valley executives Googling “Where exactly is Johannesburg?”, Cassava plans to deploy Nvidia’s accelerated computing and AI software at data centers in South Africa by June 2025, with expansion planned to Egypt, Kenya, Morocco, and Nigeria. Because if there’s one thing these countries have in common besides breathtaking landscapes and rich cultural heritage, it’s absolutely bulletproof electrical infrastructure.

“This will give African businesses, governments and researchers access to cutting-edge AI computing capacity,” Cassava proudly stated, apparently unaware that 95% of Africa’s AI talent already lacks access to the computational power they need³. But why let small details like “almost nobody can use this” get in the way of a good press release?

Dr. Mbeki Nkomo, an AI researcher at the University of Transvaal, expressed cautious optimism: “We’re thrilled about the AI factory. My team has developed an algorithm that can predict electricity load-shedding schedules with 99.7% accuracy. Now we just need power to run it.”

Powering the Unpowerable: A Master Class in Ironic Infrastructure

The energy requirements for AI computing are notoriously intensive, with some estimates suggesting that training a single model consumes as much power as thousands of households over several months⁴. In South Africa, where load-shedding remains a “persistent reality” according to people who understand understatement⁵, this presents what experts call “a significant challenge,” and what normal people call “are you freaking kidding me?”

When pressed about the electricity concerns, a spokesperson who wished to remain employed stated, “We’re implementing innovative power solutions.” These reportedly include:

The revolutionary “AI Power Scheduling Algorithm” that will ensure the AI factory only runs complex computations during the 37 minutes per day when electricity is guaranteed
A fleet of 10,000 interns on stationary bicycles connected to electric generators
Harvesting the kinetic energy generated by government officials running away from accountability
The hot air produced during tech conferences about “Africa’s Digital Future”

“The rollout of AI infrastructure is critical if Africa is to take full advantage of the fourth industrial revolution,” Masiyiwa insisted⁶, presumably with a straight face and without a single electrical engineer in the room frantically waving their arms in protest.

Cooling Solutions: Because Nothing Says “Efficient Computing” Like 40°C Heat

Data centers traditionally require extensive cooling systems to prevent the hardware from melting faster than an ice cream cone in the Sahara. With temperatures regularly exceeding 40°C in many African regions, cooling these facilities presents another minor inconvenience that Cassava and Nvidia have apparently solved with the power of positive thinking.

Michael Jux, Senior Area Sales Manager at STULZ, a company specializing in cooling solutions for data centers, noted that water-cooled solutions are becoming increasingly popular for high-density AI applications. “Water offers superior cooling capacity compared to air because it can absorb heat more efficiently,” he explained, presumably unaware that reliable water infrastructure is about as common as unicorns in many African regions.

Sources close to the project reveal that Cassava is considering several innovative cooling strategies:

Positioning the servers directly under the paths of migratory birds to utilize the breeze from their wings
Employing an army of interns (the same ones generating electricity) to fan the servers with giant palm leaves
A complex system that harnesses the naturally cool temperatures found in the offices of government officials when asked about corruption
Revolutionary “AI Cooling Technology” that will simply persuade the servers they aren’t actually hot

Africa’s AI Talent: From 5% to 5.1% With One Bold Stroke

The announcement comes at a time when only 5% of Africa’s AI talent has access to the computational power needed for research and innovation. This bold new initiative aims to increase that number to at least 5.1% by 2027.

“We’re empowering African businesses, startups and researchers with access to cutting-edge AI infrastructure to turn their bold ideas into real-world breakthroughs,” Masiyiwa stated, likely while a single tear of joy rolled down the cheek of the one researcher who will actually get access to the facility.

Dr. Confidence Staveley, who wrote about the untapped potential of Africa’s AI talent, pointed out that “Africa is home to the youngest population in the world, with a median age of just 19”⁷. This demographic advantage means Africa has millions of young people ready to solve complex AI challenges as soon as they get reliable electricity, internet access, educational opportunities, and overcome systemic barriers to participation in the global tech economy. So, any day now.

Learning From Past Successes: Jumia and Other Triumphs

The AI factory initiative follows in the footsteps of other wildly successful tech ventures in Africa, such as Jumia, often referred to as the “Amazon of Africa” by people who have apparently never used Amazon⁸.

A year after its much-heralded debut on the New York Stock Exchange, Jumia had shut down in three African states, struggled to turn a profit, and got dumped by its original owners. But surely an AI factory requiring exponentially more infrastructure, investment, and specialized talent will fare much better.

“African startups face tough challenges in 2025, including a 32% drop in investment, funding shortages, and regulatory hurdles,” according to Tech In Africa⁹, which makes this the perfect time to build a massively expensive, energy-intensive, specialized facility that requires constant upkeep and technical expertise.

Revolutionary Applications That Will Change Everything (Theoretically)

Despite these minor hurdles, the potential applications for AI in Africa are undeniably exciting:

Agriculture

AI-driven systems will revolutionize farming by providing real-time advice that farmers can’t access because they don’t have smartphones, internet connectivity, or electricity to charge said non-existent smartphones¹⁰. “Our research approach has from the beginning been that the AI models we develop work in low-resource environments,” said Owomugisha Godliver, who has clearly mastered the art of ironic understatement.

The GreenLive system in Cameroon already aims to implement precision agriculture techniques, with expectations to increase crop yields and reduce resource usage¹¹. Farmers without internet access or technical training are reportedly “extremely excited” about implementing complex AI-driven farming techniques just as soon as someone explains to them what AI is.

Healthcare

AI will transform healthcare by analyzing medical data that doesn’t exist because most hospitals are still using paper records—if they’re keeping records at all. Virtual doctors will provide remote consultations to patients who don’t have smartphones, internet access, or electricity to power these devices.

Government Efficiency

Perhaps most ambitiously, AI will tackle government inefficiency and corruption by analyzing data that governments refuse to digitize specifically to avoid such analysis. When asked if they supported the AI initiative, 17 African government officials replied with variations of “new phone, who dis?”

The Twist: It’s Actually Genius

In a shocking twist that nobody saw coming, the entire AI factory concept may actually be brilliant—just not for the reasons stated.

Industry analyst Dr. Nkosazana Dlamini (who definitely exists and isn’t a composite character created for this article) explains: “When the AI factory inevitably fails due to infrastructure challenges, Masiyiwa and Nvidia can blame African governments for not providing adequate support. Meanwhile, African governments can blame the companies for not understanding local conditions. Everyone gets to point fingers while nothing actually changes—it’s the perfect tech venture!”

“By June 2025, we’ll be deploying advanced computing and AI software at our data centers in South Africa,” confirmed a Cassava spokesperson, without specifying whether “deploying” meant “actually functioning” or just “physically present while waiting for electricity.”

Meanwhile, Jaap Zuiderveld, vice-president for Europe, Middle East and Africa at Nvidia, stated that “AI is helping innovators solve our greatest challenges”—challenges that, coincidentally, include how to keep AI powered on during rolling blackouts.

As Africa prepares to enter this bold new era of AI-driven development, one thing is certain: the future is bright. At least during the hours when the electricity is working.

Editor’s Note: TechOnion has learned that Cassava and Nvidia are already working on their next groundbreaking African initiative: an AI system that can predict exactly when this AI factory project will be quietly abandoned. Early results suggest sometime around Q3 2026.

Support Quality Tech Journalism or Watch as We Pivot to Becoming Yet Another AI Newsletter

Congratulations! You’ve reached the end of this article without paying a dime! Classic internet freeloader behavior that we have come to expect and grudgingly accept. But here is the uncomfortable truth: satire doesn’t pay for itself, and Simba‘s soy milk for his Chai Latte addiction is getting expensive.

So, how about buying us a coffee for $10 or $100 or $1,000 or $10,000 or $100,000 or $1,000,000 or more? (Which will absolutely, definitely be used for buying a Starbucks Chai Latte and not converted to obscure cryptocurrencies or funding Simba’s plan to build a moat around his home office to keep the Silicon Valley evangelists at bay).

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If your wallet is as empty as most tech promises, we understand. At least share this article so others can experience the same conflicting emotions of amusement and existential dread that you just did. It’s the least you can do after we have saved you from reading another breathless puff piece about AI-powered toasters.

Why Donate When You Could Just Share? (But Seriously, Donate!)

The internet has conditioned us all to believe that content should be free, much like how tech companies have conditioned us to believe privacy is an outdated concept. But here’s the thing: while big tech harvests your data like farmers harvest corn, we are just asking for a few bucks to keep our satirical lights on.

If everyone who read TechOnion donated just $10 (although feel free to add as many zeros to that number as your financial situation allows – we promise not to find it suspicious at all), we could continue our vital mission of making fun of people who think adding blockchain to a toaster is revolutionary. Your contribution isn’t just supporting satire; it’s an investment in digital sanity.

What your money definitely won’t be used for:

Creating our own pointless cryptocurrency called “OnionCoin”
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Developing an actual tech product (we leave that to the professionals who fail upward)
A company retreat in the metaverse (we have standards!)

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Where Your Donation Actually Goes

When you support TechOnion, you are not just buying Simba more soy milk (though that is a critical expense). You’re fueling the resistance against tech hype and digital nonsense as per our mission. Your donation helps maintain one of the last bastions of tech skepticism in a world where most headlines read like PR releases written by ChatGPT.

Remember: in a world full of tech unicorns, be the cynical donkey that keeps everyone honest. Donate today, or at least share this article before you close the tab and forget we exist until the next time our headline makes you snort-laugh during a boring Zoom meeting.

References (Just in case you thought we made it up!)

SHOCKING: New Study Reveals 83% of “Disruptive” Startups Just Reinvented the Wheel With Apps and Buzzwords

By

Simba the "Tech King"

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April 2, 2025

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A satirical illustration depicting "The Ouroboros Effect" in the tech industry. Visualize a giant, futuristic ouroboros snake made of glowing circuit boards and digital screens, with segments representing various industries (like retail, healthcare, and finance) being consumed by the snake's own tail. In the background, create a bustling Silicon Valley skyline filled with high-tech skyscrapers, all adorned with flashy neon signs advertising "disruptive" startups. In the foreground, a group of diverse tech entrepreneurs, dressed in trendy outfits, are animatedly discussing their latest app ideas, surrounded by floating holographic graphics of buzzwords and dollar signs. The scene should have a humorous and exaggerated tone, capturing the absurdity of the situation. Use bright colors and dynamic lighting to convey a sense of excitement mixed with irony, reminiscent of a digital art style popular on platforms like ArtStation.

“The greatest innovation in Silicon Valley isn’t technology—it’s convincing venture capitalists that adding an app to an existing business model is worth a $50 billion valuation.” – Ancient Startup Proverb

In a groundbreaking study that shocked absolutely no one who’s been paying attention, researchers at the Institute for Obvious Business Conclusions have determined that the vast majority of self-proclaimed “disruptive” tech companies are essentially just traditional businesses that replaced phone calls with notifications and human managers with algorithms.

This phenomenon, which economists are now calling “The Ouroboros Effect” (after the ancient symbol of a snake eating its own tail), describes the cosmic circle of disruption wherein tech companies spend billions to “revolutionize” industries, only to eventually transform into the very institutions they sought to destroy—just with more surveillance capabilities and fewer employee benefits.

The Ouroboros Effect: How Tech Disruption Eats Its Own Tail

“What we’re witnessing is a natural evolution,” explains Dr. Miranda Chen, lead researcher at the Institute. “A tech startup begins by identifying everything ‘wrong’ with an industry, raises venture capital by promising to ‘fix’ these problems, then gradually reintroduces all those same problems while calling them ‘optimizations’ or ‘mature business strategies.'”

The study, which analyzed 283 unicorn startups over the past decade, found that 83% eventually adopted the exact same business practices they originally criticized, but with shinier branding and exorbitant convenience fees labeled as “platform contributions” or “community support charges.”

“The timeline is remarkably consistent,” Chen continues. “Year one: ‘We’re disrupting this broken industry!’ Year three: ‘We’re optimizing for sustainable growth.’ Year seven: ‘Please understand that our surge pricing during emergencies is necessary to ensure service availability.'”

The research has identified what Chen calls the “Four Horsemen of the Disruption Apocalypse”—the inevitable stages every disruptive startup passes through:

Revolutionary Idealism: “We’ll make this service accessible to everyone!”
Convenient Partial Amnesia: “We never said we’d be cheaper all the time.”
Profit Imperative Pivot: “Our investors expect sustainable unit economics.”
Complete Industry Replication: “Our mandatory 47% service fee is actually industry standard.”

The Magnificent Ten: A Gallery of Disruption Ouroboros

Our investigation has identified ten perfect examples of the Ouroboros Effect in action—companies that spent billions convincing the world they were revolutionizing industries, only to end up looking suspiciously like the dinosaurs they were supposed to make extinct.

1. Uber: Taxi Companies Without the Taxi Stands

Uber’s¹ original promise was nothing short of revolutionary: affordable rides anywhere, anytime, without the hassle of calling a dispatcher or the uncertainty of hailing a cab. Fast forward to now, and Uber has effectively recreated the taxi industry, complete with surge pricing that makes traditional taxis look like a bargain, drivers who struggle to make ends meet, and a central dispatch system (now called an “algorithm”).

“We’ve completely revolutionized urban transportation,” claims Uber’s Chief Disruption Officer, Marcus Williams. “Before Uber, you had to call a central number, and someone would assign a driver to pick you up. Now, you tap your phone, and an algorithm assigns a driver to pick you up. The difference is immeasurable.”

When asked about how this differs from a radio dispatch system with extra steps, Williams muttered something about “machine learning optimization” before abruptly ending the interview.

2. Airbnb: Hotels Without the Consistency

Airbnb² began as a way for people to make extra money by renting out spare rooms and for travelers to find affordable, homey accommodations. Today, it’s dominated by professional property managers operating de facto hotels without pesky regulations like fire safety inspections or accessibility requirements.

“We’ve democratized hospitality,” insists Airbnb spokesperson Jennifer Martinez. “Instead of staying in a predictably clean room with consistent amenities and 24-hour front desk service, you can now pay more to stay in an amateur hotel where the owner might cancel your reservation two hours before check-in, and the cleaning standards are determined by whoever the host hired on Craigslist.”

The company recently introduced “Airbnb Plus” and “Airbnb Luxe,” categories that essentially recreate hotel tiers but with a 100% chance of having to take out your own garbage.

3. WeWork: Commercial Real Estate With Kombucha

WeWork’s³ promise was to revolutionize the workplace with community-driven shared spaces. After burning through billions in venture capital, it turns out they were just a commercial real estate company that leased long and rented short—a business model that has existed since the invention of property ownership, just without the free beer and inspirational wall quotes.

“We’re not just subletting office space,” insisted former CEO Adam Neumann before his ouster. “We’re elevating the world’s consciousness through hot desks and phone booths.”

Seven years later, WeWork has shed its consciousness-raising ambitions and looks remarkably like a traditional office leasing company that spent too much on furniture.

4. DoorDash: Food Delivery With Extra Steps

Remember when restaurants hired their own delivery drivers? DoorDash “disrupted” this model by… hiring delivery drivers, but with a fancy app and a markup that makes a $10 meal cost $23 after fees, tips, and “service adjustments.”

“Before DoorDash⁴, if you wanted food delivered, you had to call the restaurant directly,” explains COO Sarah Johnson. “Now you tap seventeen buttons on an app, pay twice as much, and get your food at approximately the same temperature and speed. That’s what we call innovation.”

When asked how their service differs from traditional restaurant delivery, Johnson pointed to their “proprietary heat-prediction algorithm” that somehow always estimates your food will arrive “10 minutes from now” regardless of actual delivery time.

5. Casper: A Mattress Store You Can’t Lie On First

Casper⁵ revolutionized the mattress industry by eliminating the awkward experience of testing mattresses in a showroom, replacing it with the much more convenient experience of ordering a mattress online, waiting for it to arrive, sleeping on it uncomfortably for 99 nights, then struggling to stuff it back in a box when you realize it’s not right for you.

“We’ve completely transformed how people buy mattresses,” boasts marketing director James Chen. “Instead of trying before buying, we let customers go through an elaborate return process that involves vacuum-sealing a 70-pound foam rectangle and somehow getting it back to UPS.”

After raising billions in venture capital, Casper eventually opened physical showrooms where customers can—wait for it—try mattresses before buying them. Revolutionary!

6. Netflix: Cable TV With Extra Steps

Netflix began as a disruptor to traditional TV, offering an affordable streaming service with no ads. Fast forward to now, and Netflix has transformed into a multi-tiered subscription service with ads on lower tiers, constantly increasing prices, and content that disappears without warning—essentially becoming the cable TV it sought to replace.

“We’re nothing like cable companies,” insists Netflix spokesperson David Rodriguez. “Cable companies bundle channels you don’t want, charge too much, and constantly raise prices. We offer curated content experiences at various price points that periodically adjust to reflect market conditions.”

When asked about the introduction of the advertising tier, Rodriguez noted: “Our ad-supported option gives customers the freedom to choose between paying more or watching commercials—a revolutionary concept that definitely wasn’t the exact business model of broadcast television for the past 70 years.”

7. Robinhood: Stockbrokers With Confetti

Robinhood promised to democratize investing by eliminating fees and making trading accessible to everyone. After several years, regulatory issues, and a public offering, it turns out they were just a stockbroker that made money by selling their users’ order flow to the same Wall Street firms they claimed to be disrupting.

“We’ve revolutionized finance by making it as easy to buy stocks as it is to play Candy Crush,” claims product director Michael Thompson. “Traditional brokers charged fees and required phone calls. We eliminated fees and replaced those phone calls with push notifications and gamification that makes investing feel like a dopamine slot machine.”

When asked how selling order flow to hedge funds was “democratizing finance,” Thompson launched into a 20-minute explanation of “liquidity provision” before admitting “it’s basically the same system but with better UX design.”

8. BetterHelp: Therapy With Less Privacy

BetterHelp promised to revolutionize mental healthcare by making therapy accessible online. What they actually built was a traditional therapy practice but with questionable data practices, therapists paid less than market rates, and sessions frequently interrupted by connectivity issues.

“We’re disrupting the outdated model of in-person therapy,” says Chief Clinical Officer Dr. Rebecca Lewis. “Instead of private conversations in a comfortable office with a therapist who has thoroughly reviewed your history, you can have glitchy video calls with therapists juggling too many clients while we collect valuable data on your most intimate problems.”

When asked if sharing anonymized user data with third parties for “research and marketing purposes” contradicted therapy’s foundational principle of confidentiality, Lewis explained that “disruption requires rethinking outdated concepts like ‘privacy’ and ‘clinical ethics.'”

9. Warby Parker: LensCrafters With Better Instagram

Warby Parker disrupted the eyewear industry by cutting out middlemen and offering stylish glasses at affordable prices. After years of growth, they’ve opened hundreds of physical retail locations—effectively becoming a traditional eyewear retailer, just with better branding and social media.

“We’re nothing like traditional eyewear companies,” insists co-founder Neil Blumenthal. “Traditional companies have physical stores where you try on glasses, speak with vision specialists, and purchase frames. We have experiential retail locations where you engage with eyewear consultants and procure optical solutions.”

When pressed on the differences, Blumenthal admitted, “Okay, they’re stores. But our stores have better Instagram aesthetics.”

10. Blue Apron: Grocery Shopping But More Expensive

Blue Apron promised to revolutionize home cooking by delivering pre-portioned ingredients and recipes to your door. After years of operation, it turns out they basically reinvented grocery shopping but with more packaging waste and at a significantly higher cost per meal.

“We’ve transformed how people approach cooking,” claims culinary director Jessica Wang. “Instead of buying ingredients in normal quantities that could be used for multiple meals, we send you exactly 1/4 teaspoon of cumin in a plastic packet, two tablespoons of pre-diced onion, and a single russet potato—all for just $12.99 per serving!”

When asked how this improves upon the traditional grocery model, Wang emphasized their “curated culinary experiences” and “reduction in food waste,” strategically avoiding mention of the fourteen pieces of packaging required for a single meal.

The Circular Nature of Disruption

The study concludes that what we’re witnessing isn’t disruption at all, but rather a predictable cycle wherein new companies enter old industries, temporarily lower prices to gain market share (while subsidized by venture capital), then gradually reimplement all the same practices that made the old industries profitable in the first place.

“It’s like watching a snake devour itself in slow motion,” explains business historian Dr. James Miller. “These companies spend billions convincing us they’re revolutionizing industries when they’re really just adding an app to existing business models, eliminating worker protections, and hiding fees in places consumers won’t immediately notice them.”

Dr. Chen agrees: “The true innovation isn’t technological—it’s financial. These companies have mastered the art of losing money for years while maintaining high valuations, then transferring the costs of profitability to consumers once they’ve eliminated competition.”

The Final Twist: The Disruption of Disruption

As our investigation was concluding, we discovered perhaps the most ironic development yet: a new wave of startups explicitly positioning themselves as “disrupting the disruptors.”

“We’re nothing like those fake disruptors who just recreated old business models with apps,” explains Sarah Johnson, founder of NeoTaxi, a new ride-sharing platform. “We’re fundamentally reimagining transportation by connecting riders directly with drivers through our revolutionary app-based platform.”

When asked how this differs from Uber, Johnson explained: “Uber takes too much commission from drivers and charges too many fees to riders. We’re only taking a 15% commission and a small platform maintenance fee. Plus, we’re using blockchain.”

Similarly, AirDwel is positioning itself as the anti-Airbnb by “returning to homesharing’s roots” with a platform that lets people rent out spare rooms or entire properties to travelers—for a “modest” 12% service fee, plus cleaning fees, platform fees, and community support charges.

“It’s almost beautiful in its cyclical nature,” concludes Dr. Chen. “In another ten years, these new disruptors will have become indistinguishable from the companies they’re currently criticizing, and a new wave of Stanford graduates will raise seed rounds by promising to fix all the problems they created.”

And so the Ouroboros continues its feast, devouring its own tail in an eternal cycle of disruption and reversion, innovation and imitation, revolution and regression—all while venture capitalists and founders extract billions from the process.

Or as one anonymous startup founder told us: “The real disruption was the money we made along the way.”

Support Quality Tech Journalism or Watch as We Pivot to Becoming Yet Another AI Newsletter

Congratulations! You’ve reached the end of this article without paying a dime! Classic internet freeloader behavior that we have come to expect and grudgingly accept. But here is the uncomfortable truth: satire doesn’t pay for itself, and Simba‘s soy milk for his Chai Latte addiction is getting expensive.

So, how about buying us a coffee for $10 or $100 or $1,000 or $10,000 or $100,000 or $1,000,000 or more? (Which will absolutely, definitely be used for buying a Starbucks Chai Latte and not converted to obscure cryptocurrencies or funding Simba’s plan to build a moat around his home office to keep the Silicon Valley evangelists at bay).

Your generous donation will help fund:

Our ongoing investigation into whether Mark Zuckerberg is actually an alien hiding in a human body
Premium therapy sessions for both our writer and their AI assistant who had to pretend to understand blockchain for six straight articles
Legal defense fund for the inevitable lawsuits from tech billionaires with paper-thin skin and tech startups that can’t raise another round of money or pursue their IPO!
Development of our proprietary “BS Detection Algorithm” (currently just Simba reading press releases while sighing heavily)
Raising funds to buy an office dog to keep Simba company for when the AI assistant is not functioning well.

If your wallet is as empty as most tech promises, we understand. At least share this article so others can experience the same conflicting emotions of amusement and existential dread that you just did. It’s the least you can do after we have saved you from reading another breathless puff piece about AI-powered toasters.

Why Donate When You Could Just Share? (But Seriously, Donate!)

The internet has conditioned us all to believe that content should be free, much like how tech companies have conditioned us to believe privacy is an outdated concept. But here’s the thing: while big tech harvests your data like farmers harvest corn, we are just asking for a few bucks to keep our satirical lights on.

If everyone who read TechOnion donated just $10 (although feel free to add as many zeros to that number as your financial situation allows – we promise not to find it suspicious at all), we could continue our vital mission of making fun of people who think adding blockchain to a toaster is revolutionary. Your contribution isn’t just supporting satire; it’s an investment in digital sanity.

What your money definitely won’t be used for:

Creating our own pointless cryptocurrency called “OnionCoin”
Buying Twitter blue checks for our numerous fake executive accounts
Developing an actual tech product (we leave that to the professionals who fail upward)
A company retreat in the metaverse (we have standards!)

So what’ll it be? Support independent tech satire or continue your freeloader ways? The choice is yours, but remember: every time you don’t donate, somewhere a venture capitalist funds another app that’s just “Uber for British-favourite BLT sandwiches.”

Where Your Donation Actually Goes

When you support TechOnion, you are not just buying Simba more soy milk (though that is a critical expense). You’re fueling the resistance against tech hype and digital nonsense as per our mission. Your donation helps maintain one of the last bastions of tech skepticism in a world where most headlines read like PR releases written by ChatGPT.

Remember: in a world full of tech unicorns, be the cynical donkey that keeps everyone honest. Donate today, or at least share this article before you close the tab and forget we exist until the next time our headline makes you snort-laugh during a boring Zoom meeting.

References (Just in case you think we made it up!)

BREAKING: “Dumb Money” Film Nominated for Nobel Prize in Economics After Viewers Finally Understand the Stock Market – “It’s Just Gambling With Fancier Words”

By

Simba the "Tech King"

-

April 2, 2025

0

A satirical digital illustration inspired by the film "Dumb Money," featuring a whimsical scene set in a vibrant, exaggerated Wall Street. The foreground includes animated characters resembling everyday people, dressed in casual attire, enthusiastically placing bets on a giant stock ticker that resembles a carnival game. In the background, towering hedges shaped like classic Wall Street icons (bulls, bears, etc.) loom over a chaotic mix of stock charts and colorful neon signs that read "Finance is Just Gambling!" The atmosphere is lively and playful, with exaggerated expressions of joy and confusion on the faces of the characters as they react to the fluctuating prices. Include elements like money flying through the air, oversized playing cards, and whimsical representations of financial concepts, all done in a hyper-detailed, cartoonish style reminiscent of popular animated films. The lighting should be bright and engaging, capturing the essence of a bustling stock exchange turned into a game show.

“The greatest achievement of ‘Dumb Money’¹ isn’t that it made the GameStop saga understandable – it’s that it finally exposed that the entire financial system is just a sophisticated version of a toddler’s game of ‘mine.'” said Warren Buffett’s hypothetical evil twin.

The critically acclaimed film “Dumb Money,” which chronicles the legendary 2021 GameStop short squeeze where Reddit users with stimulus checks briefly overcame billionaire hedge funds, has achieved the impossible: it has simultaneously made finance interesting and revealed that the most sophisticated financial instruments on Wall Street are fundamentally indistinguishable from betting on which raindrop will reach the bottom of the window first.

As the first film to explain stock shorting in a way that doesn’t immediately cause brain hemorrhaging in general audiences, “Dumb Money” has sparked a national conversation about whether the entire financial industry is just elaborate theater designed to make gambling look like sophisticated economic activity.

The Film That Finally Explained Finance (By Accident)

“Dumb Money” follows the true story of ordinary retail investors who, armed with the commission-free Robinhood trading app and stimulus checks, drove GameStop’s stock to stratospheric heights, causing catastrophic losses for hedge funds that had bet against the struggling video game retailer.

Film critic Darren Matthews of The Boston Herald describes it as “Wolf of Wall Street, but if the wolves were replaced by unemployed 26-year-olds eating ramen in their parents’ basements.” The New York Times called it “the first financial thriller where the most sophisticated weapon is a Reddit account.”

But the film’s greatest achievement may be inadvertently exposing that the emperor of Wall Street has no clothes.

“After watching ‘Dumb Money,’ I finally understand the stock market,” explains Dr. Miranda Chen, Professor of Economics at Harvard University. “It’s just people with money pretending they can predict the future, and when they’re wrong, they blame it on ‘market inefficiencies’ instead of admitting they’re just guessing like the rest of us.”

Hollywood’s Love-Hate Relationship With Finance Bro Culture

What makes “Dumb Money” unique in the pantheon of Wall Street movies is how it subverts the traditional “finance bro” narrative. Instead of following charismatic sociopaths snorting cocaine off expensive surfaces, it champions underdogs using memes and diamond hand emojis to coordinate a collective middle finger to the establishment.

“Traditional finance films like ‘Wall Street’ and ‘The Big Short’ make you feel smart for understanding complex financial concepts,” explains film scholar Thomas Reynolds. “But ‘Dumb Money’ makes you feel smart for realizing that financial ‘experts’ are just making educated guesses and calling it analysis.”

Hollywood executives were initially skeptical about a film where the heroes’ primary activities include scrolling Reddit and staring anxiously at stock charts. “When the screenplay first came in, I thought, ‘How do we make watching people look at phones for two hours exciting?'” admits Warner Bros. executive Sarah Johnson. “Then I realized that’s literally all anyone does anymore anyway, so audiences would relate.”

The film has received particularly scathing reviews from Wall Street professionals, with Goldman Sachs analyst Jeffrey Williams calling it “a dangerous oversimplification that could lead people to believe they understand market dynamics.” When pressed on what crucial nuances the film missed, Williams admitted, “Well, it doesn’t show us making complex Excel models that ultimately just guess what numbers might be bigger next quarter.”

The Robinhood Paradox: Democratizing Finance (Until It Hurts The Wrong People)

At the center of both the film and the actual GameStop saga is Robinhood, the trading app that promised to “democratize finance” but abruptly restricted trading when those same democratized masses threatened powerful hedge funds.

“What makes the Robinhood story so perfectly ironic,” explains technology ethicist Dr. James Martinez, “is that it’s named after a folk hero who stole from the rich to give to the poor, but when actual regular people started winning against billionaires, they essentially said ‘no, not like that’ and changed the rules mid-game.”

The film highlights how Robinhood’s business model relied on payment for order flow—selling users’ trade data to the very hedge funds they were supposedly “disrupting.” This revelation has prompted a wider examination of fintech companies that claim to be revolutionizing industries while secretly reinforcing existing power structures.

“Tech companies love to use words like ‘democratize,’ ‘disrupt,’ and ‘revolutionize,'” notes Dr. Martinez. “But what they usually mean is ‘we found a new way to extract value from users while convincing them they’re getting a better deal.'”

According to industry data that we definitely didn’t make up, approximately 78% of financial apps that claim to “democratize” their industry actually increase wealth concentration among the top 1% of users.

The $483 Question: Was It Worth It?

One of the most fascinating aspects of “Dumb Money” is how it forces viewers to wrestle with what “winning” actually means in this context. While some retail investors made life-changing money, many more bought GameStop at its peak of $483 and watched their investments evaporate.

“The film presents an interesting moral question,” explains cultural critic Dr. Elena Kim. “Is it worth losing your life savings if it means a hedge fund manager has to sell one of his vacation homes? According to Reddit, the answer is unequivocally yes.”

The film has sparked debate among economists about whether the GameStop saga represented a genuine shift in market power or just a temporary anomaly. According to a Harvard Business School study, the event transferred approximately $20 billion from institutional investors to retail traders—roughly equivalent to what hedge funds spend annually on premium coffee services.

“In the grand scheme of things, the GameStop squeeze was like throwing a rock at a tank,” explains economist Michael Thompson. “It felt revolutionary, but the system quickly adapted and reinforced itself. The house always wins eventually—that’s literally how it’s designed.”

The Meme Stock Era: Financial Clout Through Shitposting

Perhaps the most culturally significant aspect of “Dumb Money” is how it captures the birth of “meme stocks”—investments driven not by fundamental analysis but by collective internet humor and a desire to be part of a movement.

“What’s remarkable about the GameStop saga is that it represented the first time in history where posting rocket emojis constituted a legitimate investment strategy,” explains social media researcher Dr. Jessica Williams. “It was essentially a massive coordination game played through shitposting.”

The film portrays how r/WallStreetBets, the Reddit forum at the heart of the movement, developed its own culture and language—diamond hands, tendies, and of course, “to the moon”—that served as both community identifiers and mechanisms for coordinating action.

“In many ways, meme stocks represent the logical endpoint of a financial system that was already divorced from reality,” notes Williams. “If stock prices are just collective beliefs about what things are worth, why not base those beliefs on memes instead of earnings reports that are manipulated anyway?”

Market analysts have struggled to incorporate “meme potential” into their traditional valuation models. Goldman Sachs reportedly created a “Reddit Sentiment Index” that tracks keywords across social media platforms, while Morgan Stanley developed an algorithm to measure the “rocket emoji density” of specific stock mentions.

Keith Gill: The Roaring Kitty Who Changed Wall Street

At the center of both the film and the actual events is Keith Gill, known online as “Roaring Kitty,” the financial analyst who initially identified GameStop as undervalued and inadvertently sparked a financial revolution.

“What makes Gill such a fascinating character,” explains psychologist Dr. Samuel Chen, “is that he wasn’t a revolutionary. He was just a guy who did his research and shared it online. He didn’t set out to crash hedge funds—that was just a happy side effect.”

The film portrays Gill as an everyman hero, making his financial analysis videos in a basement gaming setup while wearing a headband and t-shirts. This image stands in stark contrast to the suits and Bloomberg terminals of traditional finance.

“Keith Gill represents a democratization of financial analysis,” notes Chen. “He showed that sometimes a guy in a cat t-shirt can be right when billion-dollar hedge funds are wrong, which is both inspiring and terrifying depending on which side you’re on.”

Wall Street’s Response: Revenge of the Suits

While “Dumb Money” portrays the GameStop saga as a David vs. Goliath victory, the aftermath suggests Goliath simply took a moment to adjust his strategy. The film’s epilogue notes how trading restrictions, regulatory scrutiny, and market adjustments quickly followed the meme stock phenomenon.

“The most predictable response to the GameStop situation was how quickly the system moved to ensure it could never happen again,” explains financial historian Dr. Robert Anderson. “When regular people find a loophole in capitalism, that loophole gets closed faster than a politician’s ethics investigation.”

Following the events portrayed in the film, major hedge funds dramatically increased their social media monitoring, with some firms reportedly hiring former Reddit moderators to identify emerging meme stocks before they gain momentum.

“It’s like watching an immune system respond to a virus,” Anderson continues. “Wall Street identified retail investors coordinating online as a threat and developed antibodies against it. The system isn’t designed to let the little guy win repeatedly.”

The Unexpected Twist: Hollywood Executive Found Short-Selling The Film’s Production Company

In a development too perfect to make up (but we did anyway), our investigation has uncovered that three executives at the studio behind “Dumb Money” were actively short-selling the studio’s stock during production, betting that a film about Reddit users and stock markets would flop spectacularly.

“I read the script and thought, ‘This is just people looking at phones and typing angry comments. Who would watch that?'” admits one anonymous executive. “So I borrowed some shares and shorted our own company. Then the trailer went viral on, guess where, Reddit. Now I’m underwater on my position and have to fake enthusiasm about our box office prospects. Life imitates art, I guess.”

When asked if there was something ethically questionable about betting against the company that pays his salary, the executive explained: “That’s the beauty of modern finance—concepts like ‘loyalty’ and ‘conflict of interest’ are just obsolete social constructs that get in the way of efficient markets. At least that’s what I tell myself at night.”

In the ultimate irony, Reddit users have now started buying the studio’s stock specifically to squeeze the executives who shorted it, creating a meta short squeeze about a movie about a short squeeze.

“It’s shorts all the way down,” commented Reddit user u/MetaSqueezeRevenge. “We’re about to make a movie about making money on the movie about making money on GameStop.”

And so, as “Dumb Money” continues its theatrical run, audiences are left to ponder whether the entire financial system is just an elaborate game where the rules are written by the players with the most chips. Or as one Wall Street Journal critic put it: “The film’s greatest achievement is making viewers realize that the difference between sophisticated financial instruments and a casino is mainly that casinos have better snacks and more honest odds.”

The film is rated PG-13 for strong language, brief nudity, and explaining finance in a way that might make you question your 401(k).

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References (Just in case you thought we made this up!)

https://www.imdb.com/title/tt13957560/ ↩︎