Welcome to Tomorrow You Never Asked For

They promised us a decentralized utopia. They delivered a dystopia where your refrigerator owns more of your data than you do.

Remember when the Internet was going to save us all? And when blockchain was the answer to every question, including ones nobody asked? Well, congratulations, we’re about to do it all over again, except this time with more AI, more biometrics, and somehow even less privacy. Welcome to Web, where the Web doesn’t just track you! It predicts, preempts, and probably judges you for that 3 AM pizza order. Well, at least the ads will be really accurate.

The “Good Old Times”

Let’s start our journey by taking a nostalgic trip down memory lane, back when the Internet was merely bad, not apocalyptically terrible.

Perhaps, Web1 could be considered the digital equivalent of reading a newspaper that never updates. Static pages, slow modems, and the comforting sound of your phone line dying every time someone wanted to call…You’d wait seventeen minutes for a single image to load, one agonizing pixel row at a time. Websites looked like they were designed by someone who just discovered the font menu and couldn’t help themselves.

But here’s the thing: it was honest in its limitations. A website couldn’t track you because it was barely functional to begin with, as cookies were things you ate, and not things that followed you across the web for years. Your data was safe because nobody had figured out how to monetize it yet. In its essence, the old Internet was more like a library where nothing moved and everything was under construction (remember those eternal “under construction” GIFs?), but at least the library wasn’t reporting your browsing history to advertisers.

You could visit a website and leave. Just… leave. Close the browser. The website didn’t care, it didn’t remember you, and didn’t try to re-engage you. It just sat there, static and lonely, waiting for the next visitor. Simpler times. Dumber times. Better times that are forever gone now.

The 2000s Way

Then came Web2, and everything went to hell in a very profitable handbasket. Suddenly, everyone became a “content creator,” which is corporate-speak for “unpaid laborer generating data for billionaires while we gaslight you into thinking it’s empowerment.” Meh. You weren’t working for Facebook, you were “sharing your life.” You weren’t generating revenue for YouTube. Instead, you were “building your brand.” And of course, you weren’t surrendering your privacy for convenience as you were “joining the conversation.” Indeed.

The platforms were initially free, which should have been the first red flag. When you’re not paying for the product, you are the product — a cliché old as dirt that everyone repeated and nobody took seriously enough. Facebook knew your political leanings before you did, Google finished your sentences and read your emails to serve you better ads, and Amazon recommended products before you knew you needed them, or more accurately, before they made you think you needed them through algorithmic manipulation so subtle you believed the desire was your own.

We called it the “attention economy,” which sounds so much better than “weaponized psychology for profit” or “industrial-scale addiction engineering.” Infinite scroll wasn’t designed for your convenience, but rather to …well, just keep you scrolling! Notifications weren’t keeping you informed, but they were keeping you anxious and checking for sure, 16/7. Every interface element was A/B tested thousands of times to find the exact design that would maximize engagement from your limited conscious awareness! The list can go on.

So, the social networks figured out that anger drives engagement, so they algorithmically promoted content that made you angry. Misinformation spreads faster than truth because lies are more interesting than the actual reality. Your best friend became a conspiracy theorist not because he’s stupid, but because the algorithm learned that conspiracy content kept him on the platform seventeen minutes longer per session, and seventeen minutes equals more ad impressions equals X3 more money.

And we all just…accepted it, because the convenience was undeniable. Why remember phone numbers when your contacts are synced? Or print directions when GPS exists? Why meet people in person when you can swipe right? Each compromise seemed reasonable, and each surrender of privacy came with a certain benefit. At the end of the day, we sold ourselves for free email and next-day shipping, and we pretended we got the better end of the deal.

Here Comes the “Revolution” You Didn’t Ask For

Now, the most fascinating part starts! Then Web3 crashed through the door like a drunk relative at Thanksgiving, shouting about revolution.

Decentralization! Blockchain! Cryptocurrencies that would definitely replace fiat currency any day now! NFTs that would undoubtedly hold their value and were absolutely not just digital Beanie Babies for people who learned nothing from previous bubbles! The pitches were quite intoxicating: take power back from Big Tech, own your data, control your digital destiny, stick it to The Man!

Remember when people paid six figures for pixel art of bored apes last time? Or when Twitter execs put laser eyes in their profile pictures. When every conversation somehow ended up being about whether you understood what blockchain really was. (Narrator: Nobody understood what blockchain really was, including the people explaining it.)

The future was supposed to be financial sovereignty and digital ownership. Own your data, own your identity, and your tweets. In 2025, what we’ve got is financial casinos with worse odds than Vegas, scams operating in broad daylight because “code is law” apparently, and environmental destruction as a feature… not a bug, because apparently burning enough electricity to power a small nation per transaction was the price of decentralization.

The crypto bros promised that blockchain would eliminate the need for trust. They were technically correct as you definitely couldn’t trust them since the NFT market was 95% wash trading and self-dealing. The “play-to-earn” games turned out to be pyramid schemes with better graphics, while the majority of DAOs (or Decentralized Autonomous Organizations) turned out to be regular organizations, except slower, more expensive, and with worse and sometimes really crazy, governance.

And the VCs loved it! Billions poured into projects that were either vaporware or solutions looking for problems. Do you need blockchain for supply chain management? No. For voting? Certainly not. For anything other than speculative mania and illicit transactions? The jury’s still out, and by “out,” we mean “has rendered a verdict of no, but people keep appealing it.”

Web3 was supposed to save us from Web2’s surveillance capitalism, but instead, it added financial speculation on top of it. Every transaction on a public blockchain is permanent and visible, and your wallet address becomes your identity, linkable to your real identity through numerous vectors. It’s surveillance, but now it’s decentralized and permanent. Call it the Progress!

Welcome to the Future You Unimagined

Now here comes Web4, stumbling onto the scene like it’s trying to prove that third strikes and fourth strikes are both possible... And oh boy, have we learned nothing.

The pitch sounds familiar because it’s essentially Web3’s greatest hits album, except now with AI doing the scamming for us, automating the dystopia for efficiency. And it promises an “intelligent” web that anticipates your needs through predictive algorithms that definitely won’t be biased or creepy. Powered by quantum computing (whatever that means this week — the definition changes depending on who’s trying to raise venture capital) and neural interfaces, it will let you browse the web with your thoughts (because typing was apparently too much effort, and privacy was overrated anyway).

Marketeers say that hyper-personalized experiences will be tailored to you by AI that knows you better than you know yourself. Furthermore, it might be seamlessly integrated with the physical world as they claim — your smart home, smart car, smart clothes, smart toothbrush, smart toilet paper whatsoever, all talking to each other and sharing data about you. The future of human-computer interaction, they swear, and by “interaction” they mean “the computer makes decisions for you.”

Web4 proponents talk about the “spatial web,” and “ambient computing,” and “the embodied Internet.” What they mean is: cameras everywhere, sensors everywhere, your every movement and biometric reading captured and analyzed. They mean: AI agents making decisions on your behalf, whether you want them to or not. They also mean: the final merger of physical and digital space, such that opting out of the digital panopticon means opting out of participating in society.

The reality? It will feel more like Web2’s surveillance apparatus merged with Web3’s speculative mania and cryptographic false promises, wrapped in an AI that makes decisions you can’t understand, can’t appeal, and definitely can’t escape. It’s machine learning models trained on humanity’s worst impulses, given authority over life-altering decisions. Likewise, it’s smart contracts that execute automatically based on conditions determined by algorithms, enforcing rules written by people who didn’t consider edge cases because they were too busy raising Series B funding.

Feels like somebody watched every Black Mirror episode, took notes, and thought, “Yes, but what if we made it mandatory and integrated it into every aspect of daily life? What if we made it impossible to opt out? What if we made the dystopia the default setting?”

And the most terrifying part? We’re going to accept it. Not all at once, no one would accept that, no sir! But piece by piece, convenience by convenience, efficiency by efficiency. Each step will seem reasonable in isolation, every new intrusion will come with a benefit, so in the end, each surrender will be justified by the improvements to the user experience.

We’re not building Web4 because we want it. Corporations see it as profitable. After all, the technology makes it possible, and because we’ve already demonstrated that we’ll accept anything if you make it convenient enough and roll it out slowly enough that we don’t notice the cage being built around us.

Welcome to the future. It’s going to be so much worse than you imagine, and you’re going to pay a subscription fee for it.

The Dark Future of the Online World. Part I. The Descent From Web1 to Web4. was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.

Greetings team,
I’ll be speaking at AI Edge in two weeks. Come join us at what’s shaping up to be a standout AI event.

Today’s edition covers a wild week in the AI world: Kimi K2 just outperformed every major model, signaling how fast Chinese open-source systems are advancing while keeping costs dramatically lower. Anthropic is now on track to hit profitability years ahead of OpenAI, and a new Silicon Valley-backed startup is raising the question none of us expected so soon: Would you edit your future baby’s DNA?

Let’s dive in — and stay curious.

• Anthropic to be Profitable before OpenAI
• AI Tools
• Kimi K2 AI Model Beats all other LLMS
• AI Guides
• Would You Edit Your Future Baby’s DNA?

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📰 AI News and Trends

• xAI works on Grok Code Remote to rival OpenAI’s Codex
• Lovable has surged to nearly 8 million users and sees 100,000 new projects built daily.
• OpenAI to sell compute capacity to other companies, putting the company in direct competition with Amazon, Microsoft, and Google. Being a cloud provider would help fund big AI spending.
• Altman and Masayoshi Son Back 27-Year-Old Louis Andre’s Bid to Build “A New Bell Labs” With Episteme, a San Francisco Research Lab Aiming to Free Top Scientists From Bureaucracy and Turn Breakthrough Ideas Into World-Changing Products
• Wikipedia urges AI companies to use its paid API and stop scraping
• OpenAI is weighing a move into consumer health apps

Other Tech News

• SoftBank sold 32.1 million shares of Nvidia in October. It also sold part of its stake in T-Mobile for $9.17 billion to finance OpenAI
• With $19 billion in quarterly sales, TikTok Shop now rivals eBay
• Apple Plans Major New Satellite-Powered Features for iPhones
• China-Backed $23B Simandou Mine Launches, Promising Cheaper Steel and a Potential Guinea Boom Amid Growing Environmental Fears
• Tesla Breaks Ground on Massive Giga Texas Plant to Build Millions of Optimus Humanoid Robots

Anthropic to be Profitable before OpenAI

The Information

Anthropic and OpenAI are on wildly different financial paths. New documents show Anthropic is set to break even by 2028, while OpenAI expects $74B in operating losses that same year, about 75% of revenue driven by massive chip and data-center spending.

OpenAI plans to burn 14× more cash than Anthropic before reaching profitability in 2030, fueled by Sam Altman’s push for scale and $1.4T in long-term compute commitments. Anthropic, valued at $183B vs. OpenAI’s $500B, is growing its business more efficiently by focusing on corporate customers (80% of revenue) and avoiding compute-heavy ventures like video generation. In 2024, both companies burned roughly 70% of revenue, but Anthropic’s burn rate drops to 9% by 2027, while OpenAI’s remains high. OpenAI is betting big that demand will justify its infrastructure buildout, spending nearly $100B on backup data-center capacity alone, while Anthropic opts for steadier, revenue-aligned growth.

Courtesy of Sacra

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Kimi K2 AI Model Beats all other LLMS

Kimi 2 Thinking Benchmarl

Moonshot’s new Kimi K2 Thinking, just changed the AI landscape. The fully open-source model is now outperforming GPT-5, Claude Sonnet 4.5, and Grok-4 on major benchmarks in reasoning, coding, retrieval, and agentic tool use.

Built as a 1T-parameter MoE (32B active), K2 Thinking scores 44.9% on HLE, 60.2% on BrowseComp, and 71.3% on SWE-Bench. Verified all frontier-level results. It supports 256k context, native INT4 inference, and long autonomous tool chains (200–300+ calls), while staying far cheaper than closed models. Moonshot released it under a modified MIT license, making it one of the most permissive high-end models available. The breakthrough marks a turning point: open-weight systems are now matching and in many cases beating proprietary giants like OpenAI and Anthropic. At a time when U.S. labs face scrutiny over trillion-dollar compute spending, K2 Thinking shows that frontier AI doesn’t require massive capital infrastructure, just efficient architectures.

For enterprises, it raises a blunt question: why pay for closed APIs when a free open model now leads the benchmarks?

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Would You Edit Your Future Baby’s DNA?

A Silicon Valley startup called Preventive, backed by Sam Altman and Coinbase CEO Brian Armstrong, is researching whether gene-editing human embryos can safely prevent hereditary diseases, sparking fierce ethical and legal debate.

The company has raised $30 million and is studying CRISPR-based embryo editing in San Francisco, even though implanting a gene-edited embryo is illegal in the US and banned in most countries. Preventive says it isn’t trying to create a baby now, only to prove the technology can be made safe, but critics warn it risks sliding into “designer baby” territory and eugenics. Some insiders say the startup has explored doing future trials in countries with looser rules, while supporters argue it could one day eliminate devastating genetic disorders like cystic fibrosis or sickle-cell disease.

💰Anthropic to be Profitable before OpenAI was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.

💥Microsoft’s $33B Compute Gambit Turns Cloud Partners into AI War Machines

Brought to you by Delve:

The AI race is quickly becoming a battle for cloud power. Tech giants now sit on more GPUs than the electric grid can support, turning compute and energy into the new oil of the digital era. China is countering with massive energy subsidies that could tilt the balance in its favor, while Microsoft and others play chess-like moves to lock up cloud access and outsource power capacity.

For the rest of us, the best strategy is to stay ahead of the curve, keep learning, and experimenting. So today, we’re sharing 3 powerful AI-augmented tools to explore and a set of free AI courses to level up your skills. Let’s dive in and stay curious.

• China’s Cheap Power Push To Tilt the AI Race
• AI Tools — AI-augmented Workflows Tools
• Microsoft’s $33 B Compute Gambit Turns Cloud Partners into AI War Machines
• AI Guides — Three New Free AI Courses You Can’t Miss.

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📰 AI News and Trends

• AI Giants Face Power Crunch as OpenAI and Microsoft Admit Energy Shortages Now Limit Growth
• Apple will rely on Google Gemini models for the new Siri experience, moving away from competing with existing AI chatbots.
• Microsoft signed one multibillion-dollar data center deal with Australia’s IREN, and another with Lambda.
• Anthropic Projects $70 Billion in Revenue, $17 Billion in Cash Flow in 2028

Other Tech News

• Tesla’s European Sales Collapse as Chinese EV Rivals Erode Market Share, but
• Tesla has reportedly signed a deal with South Korea’s Samsung SDI to purchase over $2.1 billion in energy storage system (ESS) batteries across three years.
• Dating Apps are still hot, Facebook Dating has reached 21M+ daily users since its 2019 launch
• Kimberly-Clark makes $49B bet that Tylenol risk is overblown.
• Starbucks to sell 60% of China business to Boyu.

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China’s Cheap Power Push To Tilt the AI Race

China is cutting electricity costs by up to 50% for major data centers using domestic AI chips from Huawei and Cambricon, according to the Financial Times. Local governments in regions like Guizhou, Gansu, and Inner Mongolia are offering massive energy subsidies to tech giants, including ByteDance, Alibaba, and Tencent, a move to offset U.S. chip bans and boost homegrown computing power.

With industrial electricity dropping to ~$0.056/kWh (half U.S. rates), China could rapidly expand its AI infrastructure, training more models and deploying AI at scale. US AI companies are struggling to power GPUs and are sitting on more hardware than they can power. Cheaper energy may help Chinese firms narrow the compute gap with the West, even if their chips are less efficient. Lower-cost AI experimentation, faster scaling, and a stronger domestic ecosystem all powered by state-backed energy policy.

WSJ — Data Centers are being built in rural America at record paces, but the energy to power them may not be reliable.

The AI race has become an energy race, and those with access to more and cheaper energy will have the upper hand.

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What we are reading:

• Learn How To Achieve Financial Freedom With a Business Model Called Instagram Automation
• Join 280,000+ entrepreneurs as we dive into wealth-building strategies, cash flow management, tax strategy, investing, and lifestyle design.

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AI-augmented Workflows Tools

• Workstreams.ai — If you’re looking to embed AI workflows inside your team communication and task management stack, which is aligned with your fractional CTO and automation role, this tool is a practical pick.
• AflowMind — Helps in the planning/ideation phase of workflows. Not full agent orchestration, but strong for mapping complex processes, startup idea planning, etc.
• Langflow — A visual drag-and-drop workflow builder for LLM chains, agents, memory, and vector stores. It’s positioned as a direct alternative to other AI workflow builders like Flowise.

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Microsoft’s $33 B Compute War

Courtesy of Reuters.

Microsoft has quietly turned the cloud race into a power play. Its latest $9.7 billion deal with IREN converts a former bitcoin miner into a GPU fortress for AI workloads, following a $17.4 billion contract with Nebius and earlier multi-billion-dollar pacts with CoreWeave. These “NeoCloud” alliances give Microsoft instant access to hundreds of thousands of Nvidia GB300 chips without waiting years to build data centers. In effect, Microsoft is outsourcing infrastructure risk while securing a near-monopoly on high-end compute capacity.

These NeoClouds act as leveraged shock troops, borrowing billions against Microsoft contracts to rapidly deploy liquid-cooled GPU farms. It’s a new kind of industrial policy funded by debt and fueled by AI hype. This leads to computing that comes online faster than regulators or power grids can respond. Microsoft gains agility and scale; its partners gain survival-level revenue; Wall Street gains another asset class built on AI infrastructure.

Competitors like Amazon and Google are countering with their own massive compute commitments, while China is cutting energy costs by half to power domestic AI chips. Microsoft’s strategy resembles a chess match for compute dominance, trading capex for strategic positioning and locking up GPU supply before anyone else. The risks are over-leveraged partners, soaring energy costs, and a race that may outpace real AI demand.

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Three New AI Courses You Can’t Miss.

1. University of South Florida Free Micro-Course on AI Skill Building — A new self-paced micro-course launched in early November 2025 for non-technical professionals and educators. No coding background required; focuses on how to incorporate AI into work and life.
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Brought to you by Delve: was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.