When a technological paradigm truly shifts, we often see the frenzy before the system.

The same is true for the AI wave we are experiencing.

As a primary investor, I firmly believe that betting on the deepest forces of change in an industry is far more valuable than chasing superficial narratives.

Over the past year, I’ve reviewed countless projects—RWA, Consumer, InfoFi, and more—all exploring the intersection between the real world and on-chain systems.

But the trend is becoming increasingly clear: No matter the path, every project must eventually embrace AI’s collaborative logic to boost competitiveness and efficiency.

Take RWA, for example. The future lies in using AI for risk control optimization, off-chain data validation, and dynamic pricing.

Or consider Consumer or DeFi, where superior user experience is critical. AI is needed for user behavior prediction, strategy generation, incentive distribution, and more. Other sectors follow similar trajectories, so I won’t elaborate further.

Thus, whether it’s asset digitization or experience optimization, these seemingly independent narratives will converge into a single technological logic: If infrastructure lacks the capacity to integrate and support AI, it cannot sustain the complex collaboration required for next-gen applications.

In my view, AI’s future isn’t just about "getting stronger" or "being used more." The real paradigm shift lies in the reconstruction of collaborative logic.

Just as the early internet revolution wasn’t about inventing DNS or browsers, but about enabling everyone to create content and turn ideas into products—birthing an open ecosystem.

AI is on the same path: Agents will become everyone’s intelligent co-creators, transforming expertise, creativity, and tasks into automated productivity tools—even monetization.

This is a question the Web2 world struggles to answer today, and it’s the foundational logic behind my interest in AI+Web3: Making AI collaborative, tradable, and profit-sharing is the system truly worth building.

Today, I want to discuss the only project so far that attempts to systematically build an AI-operational foundation from the chain level: Sahara.

AI × Web3: Who Will Build the Chain for This Era?

The Essence of Investment Is Worldview—Choosing a Value System
My investment logic isn’t about combining a public chain narrative with AI, picking the team with the best background, and placing a bet.

Investment, at its core, is a choice of worldview. And I keep returning to one question: Can the future of AI be collectively owned by more people?

Can blockchain redefine how AI’s value is attributed and distributed, allowing ordinary users, developers, and other roles to participate, contribute, and benefit sustainably? Simply put, only if this logic emerges do I believe such projects can become disruptors—not just "another abandoned public chain."

To find the answer, I scoured every AI project I could access—until I encountered Sahara. Tyler, Sahara’s co-founder, told me: "We’re building an open, participatory ecosystem where everyone can own and benefit."

This simple statement exposes the weakness of traditional public chains: They often serve developers unidirectionally, with tokenomics limited to gas fees or governance, rarely fostering true ecological flywheels—let alone sustaining emerging sectors.

I know this path is fraught with challenges, but that’s precisely why it’s an unavoidable revolution—and why I’m investing firmly.

As I’ve emphasized in my earlier writings on the "Web2 to Web3 evolution": True paradigm shifts aren’t about single products, but about building supportive systems. (Readers interested in this logic are welcome to revisit that article.)

And Sahara is one of the most promising cases I foresaw.

AI × Web3: Who Will Build the Chain for This Era?

From Investment to 8x Valuation Follow-On
My initial investment in Sahara was because it aligned with my vision of AI’s true mission—building an AI economy and infrastructure system. But what made me aggressively follow on at 8x the previous round’s valuation within six months was the rare energy I sensed in this team.

Two co-founders:

• Ren, the youngest tenured professor at USC, an AI expert. The fact that a '90s-born academic achieved this speaks not just to his scholarship but to his drive—a dreamer with the energy and audacity to realize it. Over a year of knowing him, I’ve witnessed a genius who works 10+ hours daily, remains emotionally steady, and stays humble.

• Tyler, former Investment Director at BN Lab, overseeing North American investments and incubators—his Web3 expertise goes without saying. His discipline is staggering: sleeping only in 1.5-hour multiples, gym sessions no matter how busy, zero sugar for mental clarity, 13+ work hours daily. I joked he’s a robot; he calmly replied, "I’m lucky to be this busy." His dopamine comes from daily progress—building dreams is his fuel.

Meeting them changed me. I’ve since adopted stricter sleep routines, stabilized my emotions, and started gyming...

So when people say Sahara "got lucky" with capital, I counter: "The capital frenzy was inevitable." I vividly recall this round’s tough primary market—yet Sahara was chased by investors.

Polychain, Binance, and Pentera invested, yes. But Sahara also kicked off Samsung’s foray into Web3 AI (its AI award catalyzed the deal). Beyond that, AI-heavy funds, national banks—all are Sahara’s guests. What you see are traditional tech and industrial players quietly betting on AI × Web3 via Sahara.

Capital only backs certainty and execution—this is Sahara’s reward for technical depth, team pedigree, system design, and delivery.

That’s why it’s posting real metrics:

• 3.2M+ activated testnet accounts

• 200K+ data annotators (millions queued)

• Clients like Microsoft, Amazon, Character.AI, and Motherson

• $10M+ revenue already

On infrastructure chains, from "who builds" to "can it be built?", Sahara is already deeper and steadier than 99% of "AI narrative projects."

AI × Web3: Who Will Build the Chain for This Era?

Public Chains’ Ultimate Challenge: Sustaining Contributor Benefits & Driving Economic Flywheels
Back to our initial thesis: In an AI-blockchain system, can a mechanism truly recognize, record, and reward every contributor?

Model training and data optimization rely on mass annotation and interaction. Without user contributions, projects must spend heavily on data procurement and outsourcing—increasing costs and undermining community-driven value.

Sahara is among the few Web3 AI projects letting users "participate in data building from day one." Its annotation task system runs daily, with communities actively labeling and creating prompts—not just improving the system but investing in data’s future.

Sahara’s mechanism doesn’t just enhance models—it educates and engages users in decentralized AI, linking data contributions to earnings, creating a true flywheel.

A case in point: BNB Chain’s MyShell, leveraging Sahara’s decentralized data collection and human-AI labeling, rapidly built a multilingual, multi-accent dataset, supercharging its TTS and voice-cloning models. This propelled its open-source projects (VoiceClone, MeloTTS) to thousands of GitHub stars and 2M+ Hugging Face downloads.

Annotators earned MyShell tokens—a bidirectional incentive loop between developers and data contributors.

Sahara’s "permissionless copyright" ensures participant rights while enabling open circulation and reuse of AI assets—the bedrock of explosive ecosystem growth.

Why is this a long-term value scenario?

Imagine building an AI app: You’d want your model more accurate and user-aligned than others’.

Sahara’s edge? It connects you to a vast, active data network—hundreds of thousands (soon millions) of annotators providing tailored, high-quality data, accelerating your iterations.

Critically, this isn’t a one-off transaction. Via Sahara, you tap a potential early-user community; these contributors may become your actual users.

And it’s not a buyout. Sahara’s smart contracts and rights-management enable long-term, traceable, sustainable incentives—contributors earn dynamically with usage, no matter how often data is called.

This isn’t just about annotation or training. Sahara’s economy spans AI’s full lifecycle: post-deployment calls, combinations, cross-chain reuse—all with built-in profit-sharing, capturing value over extended periods.

Model developers, optimizers, validators, and compute nodes all benefit continuously—no more one-time deals.

This system compounds value through model reuse. A trained model becomes like a block, recombinable across apps—each call generating new revenue for original contributors.

Hence, I share Sahara’s creed: A healthy AI economy can’t be about data plunder or model buyouts, nor letting a few monopolize gains. It must be open, collaborative, win-win—where everyone participates, every contribution is recorded, and rewards flow perpetually.

AI × Web3: Who Will Build the Chain for This Era?

But Closer to Reality, More Challenges Arise
While bullish, I won’t mask Sahara’s hurdles.

A key strength is its chain-agnostic design: open, omnichain, standardized—deployable on any EVM-compatible chain, with APIs letting Web2 systems (e-commerce backends, enterprise SaaS, mobile apps) directly call Sahara’s models and settle on-chain.

Yet this rare architecture carries a core risk: Infrastructure’s value lies not in "what it can do," but in "what others build atop it."

To become a trusted, adopted, composable AI protocol layer, Sahara hinges on how ecosystem players assess its technical maturity, stability, and future predictability. The system is built—but will projects adopt its standards?

Undeniably, Sahara has critical validation: serving Microsoft, Snapchat, MIT, Motherson, and Amazon, tackling industry-hard data problems—early signals of feasibility.

But these are Web2 partnerships. Sahara’s long-term fate ties to Web3 AI’s maturation and adoption. While it benefits from the macro trend, unlocking its infrastructure value requires more native Web3 AI products and solutions.

Still, Sahara is "the only one."

Among chains designed natively for AI, many mimic concepts—but only Sahara delivers end-to-end: on-chain rights, off-chain execution, cross-chain calls, technical closure, real revenue, and client validation.

This grants Sahara a "first-mover advantage"—but also structural risk: Success would define Web3 × AI infra standards; failure could brand AI Layer1 as premature.

As the sole option in this space, market judgment will be harsher—it must withstand time and ecosystem tests.

AI × Web3: Who Will Build the Chain for This Era?

Final Words to Builders & Observers: Seize the Window—Don’t Regret Waiting
For me, primary investing boils down to three things: depth of world understanding, dimensionality of trend judgment, and a team’s cyclical perseverance. Products matter, but they’re manifestations of these fundamentals.

Web3 lacks neither ideas nor stories—it lacks hands that turn logic into order, people who know what to hold and what to drop.

I can’t guarantee Sahara becomes the next paradigm-defining chain.

But it’s the only attempt today worth serious attention, observation, and betting.

If you wait until everything’s proven, ecosystems matured, and consensus formed—the opportunity will be gone.

So maybe you should panic. Not because you missed something, but because you’re witnessing a system’s genesis.

While others watch for market signals, you already know: This system exists, its direction is clear, its structure is up—just not yet understood.

Most will swarm once it’s proven. But you—you’re here as the flywheel sits motionless, standards unset.

This isn’t certainty—but it’s a real beginning.

Not everyone gets it. But you’re seeing "what precedes consensus."

When a technological paradigm truly shifts, we often see the frenzy before the system.

The same is true for the AI wave we are experiencing.

As a primary investor, I firmly believe that betting on the deepest forces of change in an industry is far more valuable than chasing superficial narratives.

Over the past year, I’ve reviewed countless projects—RWA, Consumer, InfoFi, and more—all exploring the intersection between the real world and on-chain systems.

But the trend is becoming increasingly clear: No matter the path, every project must eventually embrace AI’s collaborative logic to boost competitiveness and efficiency.

Take RWA, for example. The future lies in using AI for risk control optimization, off-chain data validation, and dynamic pricing.

Or consider Consumer or DeFi, where superior user experience is critical. AI is needed for user behavior prediction, strategy generation, incentive distribution, and more. Other sectors follow similar trajectories, so I won’t elaborate further.

Thus, whether it’s asset digitization or experience optimization, these seemingly independent narratives will converge into a single technological logic: If infrastructure lacks the capacity to integrate and support AI, it cannot sustain the complex collaboration required for next-gen applications.

In my view, AI’s future isn’t just about "getting stronger" or "being used more." The real paradigm shift lies in the reconstruction of collaborative logic.

Just as the early internet revolution wasn’t about inventing DNS or browsers, but about enabling everyone to create content and turn ideas into products—birthing an open ecosystem.

AI is on the same path: Agents will become everyone’s intelligent co-creators, transforming expertise, creativity, and tasks into automated productivity tools—even monetization.

This is a question the Web2 world struggles to answer today, and it’s the foundational logic behind my interest in AI+Web3: Making AI collaborative, tradable, and profit-sharing is the system truly worth building.

Today, I want to discuss the only project so far that attempts to systematically build an AI-operational foundation from the chain level: Sahara.

AI × Web3: Who Will Build the Chain for This Era?

The Essence of Investment Is Worldview—Choosing a Value System
My investment logic isn’t about combining a public chain narrative with AI, picking the team with the best background, and placing a bet.

Investment, at its core, is a choice of worldview. And I keep returning to one question: Can the future of AI be collectively owned by more people?

Can blockchain redefine how AI’s value is attributed and distributed, allowing ordinary users, developers, and other roles to participate, contribute, and benefit sustainably? Simply put, only if this logic emerges do I believe such projects can become disruptors—not just "another abandoned public chain."

To find the answer, I scoured every AI project I could access—until I encountered Sahara. Tyler, Sahara’s co-founder, told me: "We’re building an open, participatory ecosystem where everyone can own and benefit."

This simple statement exposes the weakness of traditional public chains: They often serve developers unidirectionally, with tokenomics limited to gas fees or governance, rarely fostering true ecological flywheels—let alone sustaining emerging sectors.

I know this path is fraught with challenges, but that’s precisely why it’s an unavoidable revolution—and why I’m investing firmly.

As I’ve emphasized in my earlier writings on the "Web2 to Web3 evolution": True paradigm shifts aren’t about single products, but about building supportive systems. (Readers interested in this logic are welcome to revisit that article.)

And Sahara is one of the most promising cases I foresaw.

AI × Web3: Who Will Build the Chain for This Era?

From Investment to 8x Valuation Follow-On
My initial investment in Sahara was because it aligned with my vision of AI’s true mission—building an AI economy and infrastructure system. But what made me aggressively follow on at 8x the previous round’s valuation within six months was the rare energy I sensed in this team.

Two co-founders:

• Ren, the youngest tenured professor at USC, an AI expert. The fact that a '90s-born academic achieved this speaks not just to his scholarship but to his drive—a dreamer with the energy and audacity to realize it. Over a year of knowing him, I’ve witnessed a genius who works 10+ hours daily, remains emotionally steady, and stays humble.

• Tyler, former Investment Director at BN Lab, overseeing North American investments and incubators—his Web3 expertise goes without saying. His discipline is staggering: sleeping only in 1.5-hour multiples, gym sessions no matter how busy, zero sugar for mental clarity, 13+ work hours daily. I joked he’s a robot; he calmly replied, "I’m lucky to be this busy." His dopamine comes from daily progress—building dreams is his fuel.

Meeting them changed me. I’ve since adopted stricter sleep routines, stabilized my emotions, and started gyming...

So when people say Sahara "got lucky" with capital, I counter: "The capital frenzy was inevitable." I vividly recall this round’s tough primary market—yet Sahara was chased by investors.

Polychain, Binance, and Pentera invested, yes. But Sahara also kicked off Samsung’s foray into Web3 AI (its AI award catalyzed the deal). Beyond that, AI-heavy funds, national banks—all are Sahara’s guests. What you see are traditional tech and industrial players quietly betting on AI × Web3 via Sahara.

Capital only backs certainty and execution—this is Sahara’s reward for technical depth, team pedigree, system design, and delivery.

That’s why it’s posting real metrics:

• 3.2M+ activated testnet accounts

• 200K+ data annotators (millions queued)

• Clients like Microsoft, Amazon, Character.AI, and Motherson

• $10M+ revenue already

On infrastructure chains, from "who builds" to "can it be built?", Sahara is already deeper and steadier than 99% of "AI narrative projects."

AI × Web3: Who Will Build the Chain for This Era?

Public Chains’ Ultimate Challenge: Sustaining Contributor Benefits & Driving Economic Flywheels
Back to our initial thesis: In an AI-blockchain system, can a mechanism truly recognize, record, and reward every contributor?

Model training and data optimization rely on mass annotation and interaction. Without user contributions, projects must spend heavily on data procurement and outsourcing—increasing costs and undermining community-driven value.

Sahara is among the few Web3 AI projects letting users "participate in data building from day one." Its annotation task system runs daily, with communities actively labeling and creating prompts—not just improving the system but investing in data’s future.

Sahara’s mechanism doesn’t just enhance models—it educates and engages users in decentralized AI, linking data contributions to earnings, creating a true flywheel.

A case in point: BNB Chain’s MyShell, leveraging Sahara’s decentralized data collection and human-AI labeling, rapidly built a multilingual, multi-accent dataset, supercharging its TTS and voice-cloning models. This propelled its open-source projects (VoiceClone, MeloTTS) to thousands of GitHub stars and 2M+ Hugging Face downloads.

Annotators earned MyShell tokens—a bidirectional incentive loop between developers and data contributors.

Sahara’s "permissionless copyright" ensures participant rights while enabling open circulation and reuse of AI assets—the bedrock of explosive ecosystem growth.

Why is this a long-term value scenario?

Imagine building an AI app: You’d want your model more accurate and user-aligned than others’.

Sahara’s edge? It connects you to a vast, active data network—hundreds of thousands (soon millions) of annotators providing tailored, high-quality data, accelerating your iterations.

Critically, this isn’t a one-off transaction. Via Sahara, you tap a potential early-user community; these contributors may become your actual users.

And it’s not a buyout. Sahara’s smart contracts and rights-management enable long-term, traceable, sustainable incentives—contributors earn dynamically with usage, no matter how often data is called.

This isn’t just about annotation or training. Sahara’s economy spans AI’s full lifecycle: post-deployment calls, combinations, cross-chain reuse—all with built-in profit-sharing, capturing value over extended periods.

Model developers, optimizers, validators, and compute nodes all benefit continuously—no more one-time deals.

This system compounds value through model reuse. A trained model becomes like a block, recombinable across apps—each call generating new revenue for original contributors.

Hence, I share Sahara’s creed: A healthy AI economy can’t be about data plunder or model buyouts, nor letting a few monopolize gains. It must be open, collaborative, win-win—where everyone participates, every contribution is recorded, and rewards flow perpetually.

AI × Web3: Who Will Build the Chain for This Era?

But Closer to Reality, More Challenges Arise
While bullish, I won’t mask Sahara’s hurdles.

A key strength is its chain-agnostic design: open, omnichain, standardized—deployable on any EVM-compatible chain, with APIs letting Web2 systems (e-commerce backends, enterprise SaaS, mobile apps) directly call Sahara’s models and settle on-chain.

Yet this rare architecture carries a core risk: Infrastructure’s value lies not in "what it can do," but in "what others build atop it."

To become a trusted, adopted, composable AI protocol layer, Sahara hinges on how ecosystem players assess its technical maturity, stability, and future predictability. The system is built—but will projects adopt its standards?

Undeniably, Sahara has critical validation: serving Microsoft, Snapchat, MIT, Motherson, and Amazon, tackling industry-hard data problems—early signals of feasibility.

But these are Web2 partnerships. Sahara’s long-term fate ties to Web3 AI’s maturation and adoption. While it benefits from the macro trend, unlocking its infrastructure value requires more native Web3 AI products and solutions.

Still, Sahara is "the only one."

Among chains designed natively for AI, many mimic concepts—but only Sahara delivers end-to-end: on-chain rights, off-chain execution, cross-chain calls, technical closure, real revenue, and client validation.

This grants Sahara a "first-mover advantage"—but also structural risk: Success would define Web3 × AI infra standards; failure could brand AI Layer1 as premature.

As the sole option in this space, market judgment will be harsher—it must withstand time and ecosystem tests.

AI × Web3: Who Will Build the Chain for This Era?

Final Words to Builders & Observers: Seize the Window—Don’t Regret Waiting
For me, primary investing boils down to three things: depth of world understanding, dimensionality of trend judgment, and a team’s cyclical perseverance. Products matter, but they’re manifestations of these fundamentals.

Web3 lacks neither ideas nor stories—it lacks hands that turn logic into order, people who know what to hold and what to drop.

I can’t guarantee Sahara becomes the next paradigm-defining chain.

But it’s the only attempt today worth serious attention, observation, and betting.

If you wait until everything’s proven, ecosystems matured, and consensus formed—the opportunity will be gone.

So maybe you should panic. Not because you missed something, but because you’re witnessing a system’s genesis.

While others watch for market signals, you already know: This system exists, its direction is clear, its structure is up—just not yet understood.

Most will swarm once it’s proven. But you—you’re here as the flywheel sits motionless, standards unset.

This isn’t certainty—but it’s a real beginning.

Not everyone gets it. But you’re seeing "what precedes consensus."