The consensus is wrong. It assumes that the race for AI dominance is a contest of foundation models, of compute scale, of sheer parameter count. But the real battlefield is distribution, not creation.
Over the past seven days, Baidu's GenFlow officially rebranded its Chinese-facing product as Kuku AI, a decision that on the surface appears to be a simple marketing refresh. But the numbers tell a different story. Monthly active users have crossed 100 million. That is not a laboratory milestone. That is a production-grade deployment that has passed the ultimate test: real human attention, sustained over time.
Let me state this clearly: Kuku AI is not a breakthrough in model architecture. It is a combination-level innovation—a packaging of Baidu's document processing, cloud storage, and ERNIE large model capabilities into a single AI office application. The innovation resides in the product layer, not the model layer. And that distinction matters far more than most crypto builders care to admit.
Context: The Protocol That Is Not a Protocol
The blockchain industry has spent the last decade obsessed with building the base layer. We have L1s, L2s, rollups, validiums, data availability layers—each promising to be the foundation for the next generation of decentralized applications. But the user base remains a rounding error compared to the 100 million monthly active users of a centralized AI office tool.
The problem is not technological. It is distributional. Kuku AI represents the opposite of what crypto stands for: it is a walled garden, controlled by a single entity, with a model that is opaque and a data flow that is centralized. And yet, it has achieved what no decentralized AI application has: mass adoption.
This is not a criticism of the decentralized AI movement. It is a structural observation. The crypto industry has been trying to build the AI equivalent of a sovereign nation-state while the rest of the world is using a centralized SaaS product that works. The lesson from Kuku AI is not that we should abandon decentralization. It is that we have been optimizing for the wrong metric.
Core: The Liquidity of Attention
In my fund, we track what I call the "attention liquidity pool." It is a simple concept: the total amount of human cognitive time allocated to a given application category. For decentralized AI applications, that pool is negligible. For centralized AI office tools like Kuku AI, it is in the hundreds of millions of hours per month.
Why does this matter for blockchain? Because attention is the ultimate precursor to value flow. Capital follows users, and users follow utility. The crypto industry has spent billions creating utility for speculators, but almost none creating utility for the actual office worker who needs to process a PDF, summarize a meeting, or generate a report.
Based on my audit experience with over 200 DeFi protocols, I can tell you that the ones that survive are not the ones with the most innovative code. They are the ones that solve a real human friction point with the lowest possible cognitive overhead. Kuku AI does exactly that. It takes a set of existing frustrations—document management, cloud storage, AI assistance—and wraps them into a single interface that requires no blockchain knowledge, no wallet management, no gas fees.
Volatility is the fee for admission to the future. The volatility we see in AI tokens today is a reflection of the market's attempt to price this attention shift. But the market is pricing the wrong thing. It is pricing the hype around model releases, not the reality of user adoption. Kuku AI's 100 million MAUs is a data point that should force every crypto AI builder to ask: where are my users?
Contrarian: The Decoupling Thesis
The conventional narrative in crypto is that decentralized AI will eventually win because it is more trustworthy, more censorship-resistant, and more aligned with human values. That narrative is convincing—until you look at the adoption curves. The truth is that centralized AI tools are getting better faster than decentralized ones, precisely because they can move without the overhead of consensus, token governance, and distributed coordination.
History doesn't repeat, but it often rhymes. The pattern we are seeing with AI mirrors the early days of the internet. AOL, CompuServe, and Prodigy were centralized, walled-garden platforms that delivered value to millions of users before the open web even existed. Crypto is playing the role of the open web, but it is still in the dial-up phase. Kuku AI is AOL—it works, it's easy, and it has a massive user base. The decentralized alternative will come, but it will not come from copying Kuku AI's feature set. It will come from offering something that Kuku AI cannot: true data sovereignty, programmable money for AI agents, and a trustless audit trail for every inference.
This is the decoupling thesis. The market is currently pricing AI tokens based on the assumption that they will capture a share of the same attention pool that Kuku AI is capturing. That is a mistake. The two markets are fundamentally different. Kuku AI is solving for immediate productivity. Decentralized AI is solving for long-term autonomy. The value will flow differently, and at different timescales.
Risk isn't a number on a screen. It's what you don't see coming. The risk that the crypto industry is not seeing is that centralized AI becomes so entrenched in the workflow of billions of users that the switching cost to decentralized alternatives becomes prohibitive. Kuku AI is not just a product. It is a network effect in the making. Every document uploaded, every model fine-tuned, every workflow automated—that is data that entrenches the user deeper into Baidu's ecosystem.
Crypto's response should not be to build a better document editor. It should be to build a coordination layer that allows AI agents to transact, verify, and settle without relying on a centralized intermediary. The infrastructure for that is still nascent. We need on-chain attestation of model outputs, decentralized inference marketplaces, and tokenized access to compute resources. Kuku AI shows us what the demand side looks like. Now we need to build the supply side.
Takeaway: Positioning for the Next Cycle
The market is currently chopping sideways. This is not a time for aggressive bets. It is a time for positioning. Based on the data from Kuku AI's launch, I am increasing my allocation to the following categories: decentralized inference protocols, on-chain data marketplaces for AI training, and tokenized compute networks. These are the sectors that will benefit from the inevitable demand for decentralized AI infrastructure, even if the front-end looks like a Baidu product.
Code is law, but capital decides who writes it. The capital is currently flowing to centralized AI. But the law is being written by the open-source and decentralized communities. The question is not whether Kuku AI will win. The question is whether the decentralized alternative can be ready before the network effects of centralized AI become irreversible.
Volatility is the fee for admission to the future. The fee is high right now because the market is uncertain about which narrative will prevail. But the signal is clear: 100 million users are telling us that AI office tools are not a niche. They are the new default. The crypto industry needs to stop building for the crypto-native audience and start building for the Kuku AI user. Because that user is the one who will eventually need what only blockchain can provide.
History doesn't repeat, but it often rhymes. The last rhyming was the ICO boom of 2017, where the winner was not the most technically advanced chain, but the one that attracted the most developer attention. The next rhyming will be the AI agent economy, where the winner will be the one that attracts the most user attention. Kuku AI has shown us where the attention is. Now it is up to us to build the infrastructure that captures it.
