Jula茹大大

If you pay attention to KITE for a long time, you will notice an interesting trajectory— it is quietly completing a crucial 'identity evolution'.
Initially, we recognized it as an efficient and user-friendly AI agent payment and coordination tool; today, it resembles a magnet that attracts everyone to participate in its construction.
This transformation is far more than just an increase in functionality; it is an iteration of underlying logic: from 'using it to get things done' to 'growing together with it'.
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1. Why is staking an inevitable choice for KITE?
Many projects in their initial stages need a clear 'purpose' to open up the situation. KITE, in its early days as the infrastructure of the AI economy, used its tokens for paying Gas, incentivizing nodes, and settling services, with clear and direct logic.

Through long-term observation of KITE's evolution, I gradually realized a profound shift that transcends economic incentives: it is quietly constructing a collective decision-making system based on common interests through its staking mechanism. This is not only about profits but also about how a decentralized ecosystem can converge dispersed individual judgments into sustainable collective wisdom.
1. Staking: The identity shift from 'holder' to 'responsible'
Many projects simplify staking as a financial tool, but KITE's practice has shown me another possibility. When users stake tokens and become validation nodes, their identity undergoes a subtle yet fundamental change—from asset holders to network 'responsibles'. You need to be accountable for transaction validation, vote on network security, and even propose protocol upgrades. This design extends economic stakes to the level of governance and operational responsibilities. In an AI-driven economy that heavily relies on reliability, this model of 'shared responsibility' builds deeper trust than any centralized promise.

If today’s crypto world is compared to a noisy tropical rainforest, then Meme coins are undoubtedly the colorful, epiphytic orchids that bloom overnight, parasitizing on the tall canopies. They absorb all attention and nutrients, growing wildly under the torrential rains of social media, creating a suffocating prosperity. Meanwhile, Kite is like a tree that refuses to bloom, focused solely on drilling deep down. While everyone looks up in awe at the exotic flowers above, it silently extends its roots deep into the bedrock, trying to reach the underground water source of the future machine internet.

If the current cryptocurrency ecosystem is like a mountainous area continuously washed by heavy rain, then various Meme coins are like the bubbles and debris on the surface, swept along, rolling and colliding, briefly shining in the sunlight. They are noisy and eye-catching, surging violently with each storm of market sentiment. In contrast, Kite is like an aquifer buried deep underground— it does not participate in the revelry of surface water flows; its mission is to filter, store, and ultimately provide a clear, drinkable water source. In this era of mixed information and value, Kite's choice is not to create more noise, but to build a silent system that filters and sediments value.

Recently, I chatted with several developers, and everyone was discussing the same question: When AI agents begin to operate, trade, and even collaborate autonomously, is our existing blockchain architecture really sufficient?
This reminds me of the path that Kite is taking. It is not trying to become another 'universal' public chain, but rather focuses on a core narrative: building a composable and scalable infrastructure layer for the AI agent economy. The key to this narrative lies in its deep understanding of 'subnets' and a modular ecosystem—this is not just a scalability solution, but a fundamental reshaping regarding ecological diversity and specialization.

I had a deep conversation with a few friends who are doing AI model training all night. The most painful issue for them is not the technical bottlenecks, but rather the value black hole. 'My data feeds the model, my computing power supports the inference, but apart from the initial meager rewards, the subsequent value growth has nothing to do with me.' This sense of powerlessness is precisely the core flaw of the current AI economy. We are eager to talk about the intelligence of AI, yet we turn a blind eye to the rights of its contributors.
This made me re-examine what KITE is doing. What may be striking is the subnet architecture, but what is truly disruptive is its attempt to build a native value layer for the AI economy—a blockchain-based, verifiable contribution record and benefit distribution system. This is not just about technological expansion; it's a transformation of production relationships.

If I were to summarize KITE's 2026 roadmap in one sentence, I would say: it is shifting from building a 'technical protocol layer' to constructing a 'business value closed loop.' This is not a simple addition of functions, but a fundamental narrative upgrade — KITE's goal is no longer just to enable AI agents to operate and transact, but to ensure they can continuously and verifiably create and capture economic value.
In the past, we discussed the integration of AI and blockchain, focusing more on 'decentralized computing power' or 'data rights confirmation.' KITE has chosen a path that delves deeper into the essence of business: it aims to become the production relationship protocol of the AI agent economy. Every key deployment in 2026 adds an indispensable link to this closed loop.

If you have tried to enter Web3 in the past two years, you have probably experienced moments like this: eagerly installing a wallet, only to be doused with cold water by those 12 seemingly random English words; finally memorizing the mnemonic phrase, only to find that although there is USDT in the account, it gets stuck because it lacks a little ETH for Gas; wanting to try a chain game, where every operation requires a pop-up signature, and after ten minutes, your fingers are more tired than playing a competitive game.
These fragmented feelings of frustration have formed an invisible wall between the public and blockchain. And today, when we directly use FaceID to log into a dApp on Kite, pay fees with any token in our account, and even complete a series of on-chain interactions without perceiving the signature, we suddenly realize that what has always hindered the popularization of blockchain is not the technology itself, but the way the technology is presented to people.

Open your phone, you unlock it with facial recognition to enter social networks, use the balance of your balance treasure to pay for a taxi directly, and games update automatically in the background—never have you thought about 'HTTP requests' or 'database transactions'. This is the essence of excellent infrastructure: it provides value, not complexity. Today, the 'human-computer interaction layer' of blockchain is meeting its 'multi-touch moment', and Kite's design philosophy is precisely anchored at this historic turning point.
Beyond 'wallets': accounts as carriers of personalized strategies
In most blockchains, an account is a passive 'address', a container for holding assets. Its 'intelligence' is limited to receiving and sending. In contrast, Kite's native smart account has been an active, programmable agent since its inception. The difference is akin to that between a radio and a smartphone.

Many people talk about AI Agents, always starting with imagining a single intelligent entity.
An Agent can analyze the market, an Agent can execute strategies, and an Agent can scrape data.
It looks cool and smart.
But the capability of a single Agent has a ceiling, and you will quickly find that what it can do is always limited, unable to form a complex system.
The real value does not lie in how smart a single Agent is, but in what multiple Agents can do when they collaborate.
When tasks become complex and require collaboration among Agents with different skills, different roles, and different data sources, the problem arises:

Many people look at projects and always ask one question: Will it fail?
Is the liquidity sufficient? Are there enough users? Can it quickly break out?
This logic works well in the short term, but for infrastructure projects, the real danger is often not these superficial risks.
KITE is a typical example.
If you only focus on price and popularity, you might think it is slow, low-key, and even a bit boring.
Short-term fluctuations may not be large, and social popularity is also not high; many people might even say, 'Is it not working?'
But this is precisely the trap of underestimation.

Imagine a future: on-chain Agents are no longer just experimental scripts; they begin to truly create economic value.
They can run strategies, analyze data, execute tasks, collaborate to complete complex processes, and then directly generate profits.
At this point, you will find that the value distribution of the entire ecosystem will undergo subtle yet profound changes.
Many people might wonder: the profits belong directly to the Agent, right? What can KITE earn?
There is a crucial logic here: KITE does not just provide tools, but rather provides the infrastructure for operation and collaboration.
When Agents start making money, almost all of their operations will rely on KITE's scheduling, settlement, identity verification, and collaboration network.

Many people see KITE and their first reaction is to focus on the token model.
Deflation? Inflation? Lock-up? Unlocking period? Distribution ratio?
Almost all projects in the market are bound by such indicators, as if value is just price fluctuation.
But if you really understand the logic of KITE, you will discover a very core fact:
Its true value capture is not in the token design, but in the intensity of use.
Here, the intensity of use refers to how many Agents are running tasks every day, how many tasks are being broken down and executed, and how many collaborative relationships are being established and maintained.

When it comes to 'network-type projects', many people's first reaction is: cold start hell.
No one uses it, so it has no value; without value, even fewer people will come.
Social, market, and platform-type products have all been repeatedly tormented by this question.
So when KITE, this 'Agent cooperation network', appears, skepticism is almost a reflex.
How can such a complex system get off the ground in the early stages?
But if you really break down KITE's growth logic, you'll find that its cold start is not that difficult.
In fact, on certain dimensions, they can be much easier than traditional human-oriented products.

We are accustomed to using the term 'users' to understand all products.
How many DAU, how much retention, is the growth curve looking good?
However, if you apply these metrics unchanged to AI Agents, you might very well be going in the wrong direction from the start.
Because in the era of AI Agents, the real 'users' may no longer be humans.
It sounds a bit exaggerated, but if you think carefully, you'll find that this trend has actually appeared a long time ago.
In the Web2 world, the earliest big clients were never ordinary users, but rather systems, programs, and interfaces.
Humans are merely the ones initiating requests; the truly high-frequency, stable, and predictable calls often come from machines.

Many people instinctively want to figure out one thing when they first see KITE:
What exactly is it as a 'product'?
Is it a chat tool? A strategy? An automated trading tool? Or some kind of AI tool?
But if you keep pursuing this question, you'll find it increasingly awkward.
Because KITE itself is not designed according to the logic of a 'product'.
This is also why I prefer to use an analogy that sounds a bit old-fashioned, but is very apt to understand it—
KITE is more like the AWS of the Agent world, rather than an AI App.
Why compare it to AWS?

In the crypto market, we are too accustomed to using 'price' as a signal.
If it goes up, it means right; if it goes down, it means wrong.
But if you extend the time frame a bit, you'll find a recurring pattern: the truly significant turning points often don't reflect in the price first.
Many changes that determine the cycle's direction first appeared in the 'dependencies.'
Looking back at the early days of DeFi, Maker truly became irreplaceable, not because of the first surge of DAI, but because more and more protocols discovered:
Once you connect with Maker, the entire system's stability, collateral structure, and liquidation logic will be designed around it.

The on-chain world we see now is actually still in a very early stage.
Whether it's DeFi, NFT, GameFi, or Meme, most on-chain behaviors can essentially be summed up in two words: transactions.
Exchanging coins, staking, doing LP, gaming prices, playing emotions.
Assets are flowing on the chain faster and faster, but it's hard to say that the chain is really 'working'.
It's not that blockchain doesn't work, but rather a stage issue.
What has been solved on the chain over the years is more about value settlement rather than task execution.
It is very good at answering 'who should get the money', but it doesn't care much about 'how things are accomplished'.

Many people, when they first see KITE, will instinctively categorize it as 'just another AI × Crypto project.'
There are Agents, models, and automation, which seem quite similar to a bunch of AI projects on the market.
But if you really follow its design logic down, you will find a very counterintuitive fact:
What KITE is really betting on, from the very beginning, is not the AI itself, but the 'relationships' between Agents.
This point is very crucial.
Because in the past few years, whether it's Web2 or Web3, the biggest problem with AI projects is not 'not being smart enough,' but rather not being irreplaceable.

Recently, I had an in-depth conversation with a friend who works on AI agents. He mentioned a somewhat 'sci-fi' concern: the customer service agents he has trained can already handle 80% of routine conversations, but every time external data or APIs need to be called, the process gets stuck—because it requires him to log in, authorize, and make payments manually. It's like putting shackles on a marathon runner while you have to follow along step by step to give them water.
This made me realize a truth that we all vaguely feel but rarely articulate: the active subjects of the internet are transitioning from 'humans' to 'machines'. Searching, comparing prices, booking, coordinating workflows... an increasing number of decisions and actions are being completed by AI agents in milliseconds. However, the entire economic underlying structure of our network—payments, identity verification, contract execution—still assumes that sitting in front of the screen are humans who can become fatigued, careless, and require friendly UIs. This misalignment is becoming the biggest bottleneck for AI's truly autonomous actions.