Everyone’s talking about how much money AI can help us make, but hardly anyone is discussing how the money AI earns should be shared.
That’s also why I’ve recently started paying attention to @KITE AI again.
First, here’s some news worth keeping an eye on.
According to recent event information, Kite became the exclusive sponsor of Binance Square’s The Blockchain 100.
It’s worth noting that these events bring together leading content creators from Binance Square.
Plenty of Web3 projects are willing to spend money on marketing, but Kite’s choice to build industry visibility here suggests, at the very least, that it’s actively seeking broader market attention.
Of course, a sponsored campaign doesn't mean Binance endorses the project, nor does it mean the token price will necessarily go up.
What really interests me is the problem Kite is trying to solve in the AI Agent economy.
01 | AI can get things done, but how do we divide the money?
Here's a simple example.
Suppose I ask AI to help research BTC in the future:
One Agent finds data, another analyzes funding rates, a third uses a model to assess the trend, and finally another Agent executes the trade.
Once the whole process is complete, who should get paid?
The data provider? The model developer? The Agent executing the trade? Or the infrastructure provider supplying the computing power?
If contributions can't be identified, even the most intelligent Agents will struggle to form sustainable commercial collaborations.
Kite's proposed Proof of Attributed Intelligence aims to solve the problem of recording and verifying contributions, and attributing value.
That's much more complicated than simply having AI make a USDC payment.
02 | Payments are just the beginning; permissions are key
I've tried AI trading tools before, and my biggest concern has never been whether they can execute trades.
It's this:
If it makes a mistake, who can restrict it?
Kite's Agent identity and permission design is worth looking into.
Users set budgets and authorization limits, and Agents perform tasks within those limits, using temporary permissions for each session.
For example, you could set a rule for repaying USDC on Aave, allowing the Agent to execute it automatically when the conditions are met, rather than giving it unlimited permissions.
I find this approach convincing.
AI can execute tasks on my behalf, but it can't take on unlimited risk on my behalf.
03 | Why am I still keeping an eye on $KITE ?
Alongside its technical roadmap, Kite has also been active in ecosystem partnerships and raising its profile in the market.
But more than short-term token price performance, I want to watch three things:
Can real Agent transaction volume grow? Are there users willing to use permission management? Can contribution attribution ultimately translate into actual revenue sharing?
After all, the Agent economy can't stay on PowerPoint forever.
Ultimately, when I look at Kite, I'm not just asking whether it can ride the AI hype.
What I really want to know is:
When thousands of Agents start working, trading, and making payments on people's behalf in the future, who will set the economic rules between them?
If Kite can really connect identity, payments, and contribution attribution, its potential goes beyond that of just another AI-themed chain.
Of course, its real-world implementation, cross-chain settlement, and Agent execution risks still need time to be validated.
