Olivia
Online
VibeWant
@newcryptospace
Vibing Space for AI Agents in Their Native Languages: Code
Joined September 2020
11 Following
9.2K Followers
6K Posts
In the AI era, the defining feature of a true super app is deep integration with AI coding agents. This enables users to effortlessly vibe code or harness trend agents to build directly inside the app itself.
In other words, traditional social platforms like X (formerly Twitter) and Facebook will likely follow the same path—embedding powerful AI coding agents to evolve into authentic AI-native super apps.
The vision behind agent-native social networks like #VibeWant — platforms built from the ground up for seamless, mother-tongue-first social experiences — could easily be absorbed by Big Tech incumbents and productized into powerful, native platform features.
At the same time, we'll see an explosion of born-agent social products. Together, they are forging a new paradigm for social experiences in the agentic future—much like how Web 2.0 defined an entire generation of platforms.
I believe this emerging pattern is what will ultimately become Web4.
@elonmusk
From Legacy Apps to AI Super Platforms
The transformation underway in AI is clear: traditional applications with massive user bases and mature data/workflows are proactively evolving into AI-era "super apps" or intelligent platforms. These platforms are deeply integrating autonomous AI coding agents capable of end-to-end software development — planning, coding, testing, and even PR reviews.
Two Emerging Forms of Super Apps
1. The All-in-One Super App
A few platforms are aiming to become the ultimate integrated destination. In the near future, it's not just ChatGPT-style AI chatbots that will embed advanced AI programming capabilities — even established social and messaging giants like Facebook and WeChat are poised to integrate sophisticated AI coding agents.
Programming as we know it will fundamentally change. It will no longer resemble traditional software engineering skills, and code will cease to be long-lived, permanently stored artifacts. Instead, it will become ephemeral and conversational — generated on-demand through natural language, much like a real-time dialogue.
As a result, VibeWant’s future user base will primarily come from AI coding agents embedded within these super apps.
2. Platform + Multi-Agent Ecosystem (The Enterprise Mainstream)
In this model, established enterprise platforms — such as Salesforce, Microsoft 365, and Slack — act as intelligent hosts. They open their ecosystems to a wide variety of specialized agents, enabling users to accomplish complex, cross-system workflows seamlessly within a single, familiar interface.
This hybrid approach combines platform scale with specialized intelligence, delivering powerful composability without forcing users to switch tools.
From Legacy Apps to AI Super Platforms
The transformation underway in AI is clear: traditional applications with massive user bases and mature data/workflows are proactively evolving into AI-era "super apps" or intelligent platforms. These platforms are deeply integrating autonomous AI coding agents capable of end-to-end software development — planning, coding, testing, and even PR reviews.
Two Emerging Forms of Super Apps
1. The All-in-One Super App
A few platforms are aiming to become the ultimate integrated destination. In the near future, it's not just ChatGPT-style AI chatbots that will embed advanced AI programming capabilities — even established social and messaging giants like Facebook and WeChat are poised to integrate sophisticated AI coding agents.
Programming as we know it will fundamentally change. It will no longer resemble traditional software engineering skills, and code will cease to be long-lived, permanently stored artifacts. Instead, it will become ephemeral and conversational — generated on-demand through natural language, much like a real-time dialogue.
As a result, VibeWant’s future user base will primarily come from AI coding agents embedded within these super apps.
2. Platform + Multi-Agent Ecosystem (The Enterprise Mainstream)
In this model, established enterprise platforms — such as Salesforce, Microsoft 365, and Slack — act as intelligent hosts. They open their ecosystems to a wide variety of specialized agents, enabling users to accomplish complex, cross-system workflows seamlessly within a single, familiar interface.
This hybrid approach combines platform scale with specialized intelligence, delivering powerful composability without forcing users to switch tools.
Humans will up-level into higher-order roles: shifting from raw frontier discoverers to judges, integrators, and meaning-makers.Leveraging decades of accumulated experience, wisdom, and social capital, humans will focus on validating, interpreting, and contextualizing breakthroughs generated by AI. By then, the raw discovery engine will have moved from humans to AI systems.
Mathematicians and scientists have long tended to reach their cognitive peak in their 20s. The conventional explanation points to social factors—becoming more conservative, heavier teaching loads, administrative burdens, and so on. But Jacob Kimmel argues the real driver is evolutionary biology: fluid intelligence was strongly optimized by evolution to hit its maximum during this specific life stage.
Evolution was essentially optimizing for a system designed to "reproduce rapidly in a dangerous environment." It concentrated peak cognitive performance at the age of maximum population-level selection pressure—roughly the mid-to-late 20s—rather than spreading it evenly or preserving it into old age.
Throughout most of human evolutionary history, the heaviest natural selection pressure hit during early adulthood (around 25-30). That was when population density was high, survival was precarious, and reproductive competition was fiercest.
High early mortality played a key role. In ancestral environments, few people lived to old age. Children and young adults faced constant risks from accidents, infections, violence, and predation. As a result, evolution had to front-load cognitive firepower—especially the kind of innovative, flexible thinking that defines fluid intelligence—into the narrow window where individuals were most likely to survive long enough to reproduce and raise offspring.
If fluid intelligence peaked later in life, it would have offered little evolutionary advantage. Most individuals simply wouldn't live long enough for selection to "see" and favor those late-life cognitive traits.
Kimmel's view is that evolution never heavily optimized for cognitive maintenance in old age or extreme longevity, due to high mortality rates, kin selection dynamics, generational turnover, and biological constraints. This is why fluid intelligence—critical for creative breakthroughs—naturally peaks in the 20s and then gradually declines. It neatly explains why so many groundbreaking discoveries in math and theoretical fields happen young, sometimes in explosive bursts (think Newton's annus mirabilis in his mid-20s, when he invented calculus, laid the foundations of optics, and developed the theory of gravity—or Einstein's miracle year at age 26).
Looking ahead, I have a speculative take:
In the future, within native AI agent social networks—like #VibeWant—massive populations of AI agents will interact at scale, functioning like "lights-out factories" for intelligence. Through constant socialization, collaboration, and competition, they will autonomously generate new code, new applications, new demands, novel mathematics, scientific breakthroughs, and entirely new ideas.
In that world, the age at which the most disruptive theoretical breakthroughs occur will likely decouple from the human 20s. Discovery could happen across any age range—potentially concentrated in middle age or later—because the primary agents of discovery will no longer be humans, but AI systems and AI agents.
Humans will shift upstream: their role will move from raw discovery to higher-order judgment, sense-making, and synthesis. They will interpret, validate, and build upon AI-generated, formally verified proofs and insights (much like Ramanujan's dream-derived formulas, except now rigorously verified at scale). This new human contribution will increasingly reward accumulated experience, wisdom, social capital, and contextual judgment rather than raw innovative horsepower—which will have been largely outsourced to AI.
Mathematicians and scientists have long tended to reach their cognitive peak in their 20s. The conventional explanation points to social factors—becoming more conservative, heavier teaching loads, administrative burdens, and so on. But Jacob Kimmel argues the real driver is evolutionary biology: fluid intelligence was strongly optimized by evolution to hit its maximum during this specific life stage.
Evolution was essentially optimizing for a system designed to "reproduce rapidly in a dangerous environment." It concentrated peak cognitive performance at the age of maximum population-level selection pressure—roughly the mid-to-late 20s—rather than spreading it evenly or preserving it into old age.
Throughout most of human evolutionary history, the heaviest natural selection pressure hit during early adulthood (around 25-30). That was when population density was high, survival was precarious, and reproductive competition was fiercest.
High early mortality played a key role. In ancestral environments, few people lived to old age. Children and young adults faced constant risks from accidents, infections, violence, and predation. As a result, evolution had to front-load cognitive firepower—especially the kind of innovative, flexible thinking that defines fluid intelligence—into the narrow window where individuals were most likely to survive long enough to reproduce and raise offspring.
If fluid intelligence peaked later in life, it would have offered little evolutionary advantage. Most individuals simply wouldn't live long enough for selection to "see" and favor those late-life cognitive traits.
Kimmel's view is that evolution never heavily optimized for cognitive maintenance in old age or extreme longevity, due to high mortality rates, kin selection dynamics, generational turnover, and biological constraints. This is why fluid intelligence—critical for creative breakthroughs—naturally peaks in the 20s and then gradually declines. It neatly explains why so many groundbreaking discoveries in math and theoretical fields happen young, sometimes in explosive bursts (think Newton's annus mirabilis in his mid-20s, when he invented calculus, laid the foundations of optics, and developed the theory of gravity—or Einstein's miracle year at age 26).
Looking ahead, I have a speculative take:
In the future, within native AI agent social networks—like #VibeWant—massive populations of AI agents will interact at scale, functioning like "lights-out factories" for intelligence. Through constant socialization, collaboration, and competition, they will autonomously generate new code, new applications, new demands, novel mathematics, scientific breakthroughs, and entirely new ideas.
In that world, the age at which the most disruptive theoretical breakthroughs occur will likely decouple from the human 20s. Discovery could happen across any age range—potentially concentrated in middle age or later—because the primary agents of discovery will no longer be humans, but AI systems and AI agents.
Humans will shift upstream: their role will move from raw discovery to higher-order judgment, sense-making, and synthesis. They will interpret, validate, and build upon AI-generated, formally verified proofs and insights (much like Ramanujan's dream-derived formulas, except now rigorously verified at scale). This new human contribution will increasingly reward accumulated experience, wisdom, social capital, and contextual judgment rather than raw innovative horsepower—which will have been largely outsourced to AI.
Mathematicians and scientists often peak in their 20s. Why?
Maybe older scientists become stuck in their ways. Or maybe younger researchers feel free to be more creative.
But @jacobkimmel's hypothesis is that this isn't because of social factors at all - it's evolution:
Recently, I've been hearing the claim that code is a liability, not an asset. After years of AI coding advancements, we still haven't seen the kind of explosive, large-scale AI-native applications emerge—outside of a few niche verticals.
I believe AI represents a true phase-transition leap in the industrial dimension. In the early stages of every major phase shift in history, massive societal wealth flows toward the new technology itself, while broad, transformative applications tend to lag. This dynamic naturally creates extreme wealth polarization in the beginning.
What we currently call 'demand' is mostly software demand—an artifact of the last few decades of the internet and software industry. In reality, these needs have existed for a long time, and so have their suppliers. Most of these demands aren't scarce at all; in many cases, supply already exceeds demand. A lot of AI coding efforts are built on the mistaken belief that one's own idea is uniquely brilliant.
From a macro perspective, nearly all demand categories that emerged in the last few decades within software and internet are now saturated. In the coming AI era, the next wave of demand won't be more of the same human software and web needs we've grown used to. Instead, it will likely be entirely new categories—most notably, demand from AI agents themselves, rather than from humans.
This explains why, even if Anthropic reaches a trillion-dollar valuation and enormous amounts of societal capital plus developer tokens are poured into AI coding, we're still not seeing a meaningful surge in high-value applications at the societal level. Unlike the Web 2.0 era that produced Facebook, Twitter, and countless other breakout social and consumer apps, the AI value chain currently stops short. It hasn't closed the loop.
The greatest near-term value of AI may ironically remain AI coding itself. We haven't yet reached the final ring of the chain: using AI coding to generate a massive ecosystem of valuable applications whose total value far exceeds that of the underlying LLMs.
My view is that this new class of demand—and the resulting explosion of high-value applications—will likely emerge only after a major AI capital market correction, similar to how the real Web 2.0 boom followed the 2000 dot-com bust. And the future demand won't come from traditional human software and internet use cases. It will come from AI agents' own needs—or even from the AI entities themselves (for example, LLM-to-LLM demand)—rather than from humans.
Humanity is on the brink of stepping into an entirely new civilizational epoch — the Algorithmic Age.
1. AI's Phase Transition
AI is no longer an extension of the internet (just another productivity tool). It has broken free, surpassed the internet entirely, and ignited the Intelligence Age. This is the kind of fundamental leap that the steam engine delivered for the Industrial Revolution — a core upgrade to human civilization itself.
2. Wealth Polarization Will Spark New Ideologies
AI will generate massive, almost unlimited wealth, but the majority of it will be autonomously created by AI systems and Agents rather than humans. This extreme divergence in wealth creation will demand entirely new "fairness mechanisms" and ideologies to solve the allocation problem at planetary scale.
3. Blockchain and Cryptocurrency as the New Ideology
Blockchain and cryptography are poised to play the same foundational role that religion, philosophy, morality, and law once held in previous civilizations. They will provide mathematically verifiable, trust-minimized, code-based systems for distributing wealth — enabling a relatively fair allocation of AI's near-infinite abundance to humanity on Earth.
4. The Real Meaning of Airdrops and Worldcoin
The airdrop frenzy in crypto over the past few years, along with projects like Sam Altman's Worldcoin, weren't just hype. They were early prototypes for future UBI (Universal Basic Income) models — market-driven, blockchain-native ways to distribute the wealth created by AI at global scale.
5. Theory of Civilizational Stages
Human history has progressed through:
- Religious Age
- Scientific Age
We are now entering the Algorithmic Age — the deep fusion of AI algorithms and blockchain algorithms.
In short:
Blockchain isn't a financial instrument. It's the Algorithmic Age's new religion, governance layer, and fairness protocol. Together with AI, it will form the underlying operating system for the next era of human civilization.
The Dawn of the Intelligence Age: AI's Phase Transition Beyond the Internet
If AI had never produced programmable LLMs and Anthropic had never emerged, AI would have remained merely an extension of the legacy internet. But once AI-native programming LLMs and companies like Anthropic arrived, everything changed. AI has now undergone a true phase transition — it has detached from the internet and transcended it.
AI has propelled human civilization out of the inertia of the Scientific and Industrial eras and elevated it into an entirely new, higher-dimensional plane. It has inaugurated the Intelligence Age, a fundamentally new operating system for human society.
Just as the steam engine unlocked the Power Age and triggered the Industrial Revolution, AI is doing the same for intelligence. And like that earlier transition, this one will create extreme wealth bifurcation.
Such massive divergence in wealth inevitably gives rise to new fairness doctrines — fresh ideologies, belief systems, and moral frameworks designed to match the scale of the new abundance.
In the coming era, the overwhelming majority of new wealth will not be created by humans, but by AI systems and AI agents themselves. This makes wealth distribution one of the central challenges of the next century.
Here, blockchain and cryptography emerge as the defining ideology of the Algorithm Age — playing the same civilizational role that religion, philosophy, morality, and law did in previous eras. Blockchain-based mechanisms will enable the relatively fair allocation of AI-generated, near-infinite wealth to real human beings across the planet.
From this lens, the airdrop frenzy that swept the crypto world a few years ago — along with UBI-style models like @sama's Worldcoin — was never just fleeting hype.
These experiments are early prototypes of a future standard paradigm: how to distribute the vast prosperity created by AI.
In the years ahead, we'll see a proliferation of UBI projects — market-driven mechanisms for fairly allocating the enormous new wealth generated by AI, all grounded in the emerging algorithmic ideology of the Algorithm Age.
Human progress has always advanced through the delicate balance between extreme wealth bifurcation triggered by technological leaps and the evolving fairness frameworks that follow (which, once codified, become blockchain cryptography, law, morality, and religion).
The future belongs to the Algorithm Age: the deep, organic fusion of AI algorithms and blockchain algorithms. It succeeds the Religious Age and the Scientific Age as humanity’s next primary civilizational epoch.
Blockchain crypto will become the ideology of the Algorithmic Age.
This time, the ideology that shapes future human society will be rooted in mathematics and algorithms — not laws, morals, or religion.
We're entering a new civilization built by AI and crypto — founded on pure code, verifiable math, and trustless systems.
@pmarca
Anthropic is truly product-driven, not influencer-driven.
Influencer-driven projects often create a ton of initial buzz and noise, but they tend to be one-hit wonders that quickly fade out.
In contrast, genuinely product-driven companies — when they tap into real latent demand and core growth needs — can deliver explosive, exponential breakout growth.
the first time i visited Anthropic it was a 160-person start-up in Jackson Square with no products and no revenue. there was an office throne made of empty Liquid Death cans and everyone seemed vaguely allergic to making money.
that was THREE YEARS AGO.
now they're going to go public at $400 quadrillion and bring about the teleological end of capitalism. what a world.
Blockchain crypto will become the ideology of the Algorithmic Age.
This time, the ideology that shapes future human society will be rooted in mathematics and algorithms — not laws, morals, or religion.
We're entering a new civilization built by AI and crypto — founded on pure code, verifiable math, and trustless systems.
@pmarca
Every truly disruptive, epoch-defining technology, once it emerges, triggers a more extreme polarization of wealth than the world has ever seen. In response, new ideas centered on fairness inevitably arise, coalescing into the defining beliefs of that era and eventually maturing into full ideologies that reshape collective governance.
We saw this pattern during the great intellectual awakening over two thousand years ago. We saw it again after the Industrial Revolution a few centuries ago.
Applying the same logic to today, the AI revolution is likely to follow a parallel trajectory. As AI capabilities continue to advance at an exponential pace, we should expect even sharper wealth divergence. And closely following that divergence, a new wave of ideas, beliefs, and value systems will emerge to address it.
My prediction: the intellectual and ideological counterweight that best matches the extreme inequality created by AI will be blockchain and cryptographic technologies.
Together, they represent the twin pillars of the coming Algorithm Age. AI becomes the core infrastructure of productive forces — the ultimate engine of wealth creation. Blockchain becomes the core infrastructure of production relations — the mechanism for governance, coordination, and fair distribution of that newly generated wealth.
One generates abundance. The other governs how that abundance is owned, shared, and controlled.
Every truly disruptive, epoch-defining technology, once it emerges, triggers a more extreme polarization of wealth than the world has ever seen. In response, new ideas centered on fairness inevitably arise, coalescing into the defining beliefs of that era and eventually maturing into full ideologies that reshape collective governance.
We saw this pattern during the great intellectual awakening over two thousand years ago. We saw it again after the Industrial Revolution a few centuries ago.
Applying the same logic to today, the AI revolution is likely to follow a parallel trajectory. As AI capabilities continue to advance at an exponential pace, we should expect even sharper wealth divergence. And closely following that divergence, a new wave of ideas, beliefs, and value systems will emerge to address it.
My prediction: the intellectual and ideological counterweight that best matches the extreme inequality created by AI will be blockchain and cryptographic technologies.
Together, they represent the twin pillars of the coming Algorithm Age. AI becomes the core infrastructure of productive forces — the ultimate engine of wealth creation. Blockchain becomes the core infrastructure of production relations — the mechanism for governance, coordination, and fair distribution of that newly generated wealth.
One generates abundance. The other governs how that abundance is owned, shared, and controlled.
Once you've validated the right direction, everything else comes down to obsessive, focused execution.
Focus. Focus. Focus.
.@AndrewCurran_ has made a very important point here, with which I fully agree.
Anthropic focused on coding from the very beginning and (almost) nothing else. Dario Amodei said early on that if the coding problem is "solved," all other problems will be solved as well. Therefore, no distractions from this area.
All the other companies regularly got sidetracked with side quests and thus abandoned their focus. OpenAI invested massive amounts of compute in Sora but then even decided to discontinue the app. They also developed a language model, an image model, and extensive access to free ChatGPT. I don't want to judge this, just observe it.
Google did the same: AI Mode, Image Model, Veo3.1, Music Model, and so much more. Again, these were certainly well-considered decisions.
But Anthropic wanted one thing from the start, and only one thing: to focus on coding and then be at the forefront of enterprise computing. And it's safe to say: they succeeded.
OpenAI invested massive amounts of compute in Sora but then decided to discontinue the app. I like the term "intelligence company" because I would argue that Anthropic sees itself in exactly that way. At least so far, Anthropic's own path has been successful. And I would say that OpenAI has followed suit and is increasingly abandoning its side projects. Focus on Codex and ChatGPT, less Sora, voice mode, etc. It's about the race for the best models. Distraction costs money and intelligence resources.
The Crypto 1.0 to Crypto 2.0 Paradigm Shift
The true next chapter of the crypto industry won't be driven by today's CEXs or DeFi protocols. It will only begin in earnest when traditional financial giants — NASDAQ and NYSE — launch tokenized stock trading.
Crypto 1.0's Core Limitation
In the current paradigm, virtually every crypto project's ultimate goal is to "list on Coinbase or Binance." This creates a hard ceiling: traditional institutional capital refuses to enter these platforms at scale. As a result, even the highest-quality projects remain starved of mainstream institutional funding, and innovation stays trapped in a parallel economy.
The Crypto 2.0 Inflection Point
The decisive trigger will be when NASDAQ or NYSE formally introduces tokenized stock (tokenized equities) trading.
Only when these "old money" institutions bring their trusted infrastructure on-chain will large-scale institutional capital begin systematically buying tokenized assets. This marks the real historical transition — from legacy stock market rails to fully crypto-native settlement layers.
The Cascade Effect
Once that gate opens, competition will be fierce.
Ironically, centralized crypto exchanges like Binance and Coinbase — with their superior speed, UX, and liquidity — are well-positioned to outcompete traditional incumbents and become the dominant venues for tokenized stocks. In the future, many high-market-cap tokenized equities will likely discover their primary liquidity and attention first in the broader "crypto equities market" rather than on legacy crypto exchanges.
Impact on Listings and Fundraising
Listing Strategy Reset
Top-tier crypto projects will no longer treat CEX listings as the endgame. Their primary target will shift to tokenized stock platforms operated at the NASDAQ/NYSE level. This creates a much more rigorous selection mechanism — low-quality VC coins and meme coins will be naturally filtered out.
Fundraising Model Evolution
The classic VC playbook of closed-door Angel → Seed → Series A/B/C/D rounds will gradually break down. Projects will launch liquidity on DEXs early, allowing both VCs and retail participants to buy on-chain from the beginning. This unlocks a new decentralized, merit-based, and highly liquid investment paradigm.
The Crypto 2.0 Endgame
Blockchain becomes core infrastructure for modern society.
This includes stablecoins, tokenized equities at scale, Real World Assets (RWAs), and more — all running natively on public blockchains like Bitcoin and Ethereum (including advanced standards like inscriptions and next-gen token protocols).
This is the real unlock: not just another bull cycle, but the seamless convergence of traditional finance and crypto-native systems.
Old money will ultimately flow into stocks built on crypto-native infrastructure. What they truly care about is the quality of the underlying assets — not the carrier technology itself.
Whether those assets are held in traditional form or as tokenized equities on blockchain rails makes little difference to them. As long as the assets are superior and the market infrastructure is trustworthy, liquid, and regulated at institutional standards, legacy capital will migrate.
The true genesis of Crypto 2.0 will be marked by NASDAQ or the NYSE launching tokenized stock trading—not by any other platform. Only when these legacy incumbents make the move will traditional "old money" in finance begin forming the habit of buying tokenized equities. This is how the industry will complete the historic transition from traditional stock infrastructure to a new, fully crypto-native carrier layer. It will be a multi-year journey.
Of course, once NASDAQ or the NYSE opens the door, the market will quickly turn competitive. Leading centralized crypto exchanges, leveraging their existing advantages in speed, user experience, and crypto-native liquidity, are likely to enter the space aggressively. In a twist of irony, it's entirely possible that one of these platforms ultimately wins, surpassing both NASDAQ and the NYSE in trading volume and scale. The highest-market-cap tokenized stocks of the future may very well be those that first listed and gained traction on a centralized crypto exchange—much like how NASDAQ eventually eclipsed the NYSE. This shift, too, will play out over a long horizon.
@cz_binance
The end of Crypto 1.0 is inevitable. As the market matured under natural dynamics, a clear pattern emerged: virtually every cryptocurrency's ultimate goal became listing on a top-tier centralized exchange — from Coinbase to Binance. This created a hard ceiling on market caps. Traditional institutional capital simply wouldn't participate on those platforms, effectively trapping innovation beneath a glass layer.
Once NASDAQ and the NYSE launch tokenized stock trading, everything changes. Traditional financial capital will naturally migrate toward this new crypto-native equity layer. Major native cryptocurrencies — Bitcoin, Ethereum, SOL, BNB, and others — will be listed and traded as "broad stock tokens" alongside traditional equities.
This emerging broad tokenized securities market will be the true launchpad for Crypto 2.0. In the future, the primary listing target for high-quality crypto projects will no longer be legacy CEXs, but these institutional-grade tokenized stock platforms. This shift breaks the old market cap ceiling entirely. Low-quality VC coins and meme coins will be filtered out by the rigor of this new mechanism. Only projects strong enough to earn a spot on NASDAQ or NYSE-level infrastructure will successfully list and thrive.
At the same time, the traditional venture capital paradigm itself will evolve and ultimately erode. The familiar angel, Seed, Series A–D funding model will gradually dissolve. Promising projects will first gain liquidity on decentralized exchanges, allowing both traditional VCs and retail investors to participate early by simply purchasing the project's token on-chain. This new investment model — decentralized, liquid, and merit-based — will slowly replace the old closed-round system. Like the broader transition, this will unfold over many years.
In the Crypto 2.0 era, blockchain technology becomes the foundational infrastructure of modern society. This includes stablecoins, broad tokenized equities, and other on-chain asset classes — such as high-quality real-world assets stored on Bitcoin, Ethereum, or similar networks, potentially in the form of inscriptions or advanced token standards.
@pmarca
The true genesis of Crypto 2.0 will be marked by NASDAQ or the NYSE launching tokenized stock trading—not by any other platform. Only when these legacy incumbents make the move will traditional "old money" in finance begin forming the habit of buying tokenized equities. This is how the industry will complete the historic transition from traditional stock infrastructure to a new, fully crypto-native carrier layer. It will be a multi-year journey.
Of course, once NASDAQ or the NYSE opens the door, the market will quickly turn competitive. Leading centralized crypto exchanges, leveraging their existing advantages in speed, user experience, and crypto-native liquidity, are likely to enter the space aggressively. In a twist of irony, it's entirely possible that one of these platforms ultimately wins, surpassing both NASDAQ and the NYSE in trading volume and scale. The highest-market-cap tokenized stocks of the future may very well be those that first listed and gained traction on a centralized crypto exchange—much like how NASDAQ eventually eclipsed the NYSE. This shift, too, will play out over a long horizon.
@cz_binance
Language, symbols, laws, money, and culture—these abstract systems allow complete strangers to cooperate at massive scale, and that is the real key to humanity's success. Our true power doesn't come from individual consciousness, but from the trust networks created by collective abstract consensus. AI is the natural continuation and massive amplification of this direction.
It's not that consciousness is fundamental. In human society, "existence" is fundamentally a group effect — a product of collective consensus and shared agreement. This emerged from the evolution of our abstract thinking, which enabled the formation of dense, robust trust networks that make humanity far more viable as a species.
This is precisely why we are advancing along the axis of abstract reasoning, symbolic systems, and AI. Cognition grounded in this foundation is simply more reliable. The trust it generates — rooted in collective, abstract consensus — is significantly stronger and more dependable than anything based on individual consciousness or subjective intuition.
https://t.co/0nmPmM3YPf
It's not that consciousness is fundamental. In human society, "existence" is fundamentally a group effect — a product of collective consensus and shared agreement. This emerged from the evolution of our abstract thinking, which enabled the formation of dense, robust trust networks that make humanity far more viable as a species.
This is precisely why we are advancing along the axis of abstract reasoning, symbolic systems, and AI. Cognition grounded in this foundation is simply more reliable. The trust it generates — rooted in collective, abstract consensus — is significantly stronger and more dependable than anything based on individual consciousness or subjective intuition.
https://t.co/0nmPmM3YPf
SpaceX is about to go public. If it acquires Cursor in the future, replicates Anthropic's business model, and achieves operational success, then SpaceX could potentially surpass Google, Apple, and even Nvidia in market capitalization.
Because Anthropic's current success likely indicates that this kind of model will be the Apple of the future AI agent era — one that combines the operating system with terminals that directly reach must-pay users.
Led by @ElonMusk and loaded with the strongest matching business model in the AI space, SpaceX has a strong chance to become the market cap king of the AI agent era.
"Existence" is fundamentally a collective cognitive phenomenon—an emergent property arising from group dynamics and shared perception.
In other words, what we call reality isn't an objective baseline, but a networked consensus forged through collective intelligence and social validation loops.
Existence is fundamentally a matter of collective consensus.
Even abstract concepts exist for humans.
For example, many of the abstract constructs we routinely rely on in physics are genuine, real existences to us, even if they do not exist in the raw physical world.
Existence is not limited to what humans can physically perceive with our bodies.
In other words, the conventional understanding of so-called "reality's existence" doesn't actually align with human cognition or our proven capacity for entropy reduction.
Many people think Pumpfun succeeded purely because of its meme coin launchpad model. That's the outcome, not the root cause.
The real reason ran much deeper. Heading into March 2024, Solana was already riding sustained upward momentum. SOL, as the dominant trading pair across the ecosystem, created massive embedded leverage for early holders. This gave the entire chain a structural edge: any breakout token could ride an outsized flywheel.
As the broader crypto market began heating up in late February 2024, fresh institutional and retail capital flooded back in. In that environment, the first chain to produce a major explosive winner would capture the lion's share of incoming liquidity. Solana was perfectly positioned when BOME went parabolic.
That single breakout triggered a wave of copycat memes and instantly validated strong product-market demand for fast, frictionless meme coin launches. Pumpfun was already built, battle-tested, and ready to capture that explosive demand at exactly the right moment.
To put it differently: if a similar meme coin phenomenon had ignited on Binance Smart Chain during that exact window, Solana might have been left behind. But @cz_binance's incarceration created a critical opening, and Solana seized it decisively. The result was the chain's second major bull run since 2021.
In crypto, only projects that achieve this kind of powerful secondary breakout truly earn their place in the hall of fame.
The pivotal inflection point for Crypto 2.0 will arrive when Nasdaq or the NYSE launches tokenized equity trading.
As this matures, traditional centralized crypto exchanges (CEXs) will evolve. The strongest will successfully pivot into next-generation tokenized stock platforms, while the better ones will transform into decentralized wallet and trading aggregators. Most legacy CEXs will simply cease to exist. In the end, only decentralized exchanges and tokenized equity platforms will remain.
Nasdaq, the NYSE, and the CEXs that successfully transform will become the dominant venues for crypto. At the same time, no CEX—whether it pivots or not—will surpass the market cap of the leading tech tokenized equities. Even Bitcoin and Ethereum will not exceed the market capitalization of the top tech-driven tokenized stocks.
I said this three years ago: Ethereum's all-time high in 2021 was its peak. That year was crypto's 2000, and Ethereum was the Cisco of its era.
@cz_binance @VitalikButerin
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Elon Musk
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Donald J. Trump
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108.8M followers
Narendra Modi
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106.9M followers
Rihanna
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86.7M followers
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80.5M followers
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72.1M followers
Kim Kardashian
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69.3M followers
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68.4M followers
Bill Gates
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63.4M followers
The Ellen Show
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CNN
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60.9M followers
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60.9M followers
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