The longer you trade crypto, the more you realise that “user” is a very messy concept. Half the order flow on your screen comes from bots. Your own “activity” might be a mix of manual clicks, Python scripts, Telegram signal bots, copy trading and some AI assistant you asked to rebalance a portfolio. On chain it all collapses into a single wallet that supposedly represents “you”. That mismatch between how we actually operate and how blockchains model identity is exactly where Kite is trying to flip the table.
Kite is a new EVM compatible Layer 1 designed not for human users in the traditional sense, but for autonomous AI agents that act on behalf of humans and businesses. It leans into the idea of an “agentic internet” where software agents transact, negotiate and coordinate without constant human babysitting. In that world you do not want to give a large language model your seed phrase and hope for the best. You want an identity layer that knows who the human is, who the agent is, and what a specific action or session is allowed to do. Kite hard codes that into the protocol with a three layer identity model that separates users, agents and sessions. Users are real people or organisations, agents are the autonomous systems acting on their behalf, and sessions are time boxed instances of an agent performing a particular task.
Why does that separation matter so much in practice? Think about how most trading bots work today. You generate an API key or connect a wallet, set some limits and hope the bot respects them. Technically the bot is operating as you. If it goes rogue, gets exploited or misconfigured, the entire wallet is at risk. There is no way at the protocol level to say “this bot can only manage liquidity on these pairs, within this size, during these hours”. On Kite, the agent itself has a cryptographic identity, separate from the user. You can grant that agent scoped permissions and capital, while every concrete trading run is a temporary session with its own constraints. If something breaks, you can cut the session without nuking the user account or every other agent tied to it. That is a very different security posture from handing bots a master key and hoping they behave.
The other piece is payments. Kite has integrated the x402 payment standard, which is essentially a common language for AI agents to express and settle payment intents. In plain terms, x402 lets agents pay each other, pay services and receive funds without custom glue code for every single integration. That is important because agents are not just trading. They are paying for data feeds, inference, APIs, gas, cloud compute and all the small services that keep automated strategies alive. Kite is positioning itself as the native execution layer for those machine to machine transactions, with stablecoin settlement built in so agents can transact in low volatility units while still tying system level economics back to the KITE token.
From a market perspective the numbers are starting to get interesting. Kite has reportedly raised about 33 million dollars from investors like PayPal Ventures, Coinbase Ventures and General Catalyst, and its testnets have already processed over 1.7 billion AI inference calls while it gears up for a planned mainnet launch in Q4 2025. The KITE token has a total supply around 10 billion, with a design that routes stablecoin revenues from agent activity back into KITE, creating structural buy pressure as network usage grows. A big chunk of supply is earmarked for community and ecosystem incentives, and builders are expected to lock KITE to spin up agent modules and earn rewards. That is the standard “usage drives token value” story, but this time the usage is not retail degens trading memecoins. It is an emerging class of AI workers doing on chain tasks.
So what does “separating users and agents” change for traders specifically? Imagine a DeFi protocol where your “account” is really a fleet of agents. One handles market making on a handful of spot pairs, another arbitrages perp funding, another manages your stablecoin ladder for on chain bills and subscriptions. Each agent has its own limits and its own performance history, and each trade they do is scoped to a session that can be audited, paused or revoked independently. You can let an LP agent run fully autonomously inside a narrow strategy band while keeping a discretionary trading agent under tighter manual approval. In institutional terms this looks a lot like the separation of firm, desk, trader and algorithm, but expressed natively at the chain level instead of via off chain policy documents. Kite’s own messaging talks about DeFi protocols using agents for automated liquidity balancing, real time volatility responses and continuous yield optimisation without giving those agents blanket access to the treasury. That is the kind of structure that risk teams and regulators understand.
For developers, the user agent separation unlocks a different way of thinking about product design. You are not building an “app” that a wallet connects to. You are building modules that agents call as part of larger workflows. Kite’s architecture leans into this modularity, with an Agent Passport identity system that lets you verify what an agent is allowed to do, and an app store style marketplace where agents discover data feeds, models and commerce tools they can pay for automatically. Instead of shipping a bot that your users have to host, secure and permission themselves you can deploy an agent template on Kite and let users attach their own capital and policy. For quantitative devs used to wrestling with exchange APIs and semi trusted VPS providers, that is a very different distribution and trust model.
Investors should look at all of this with both curiosity and caution. On the one hand, the macro narrative is strong. The agentic economy is a hot theme, and there is a plausible path from today’s clunky “GPT plus API keys” setups to a world where agents routinely handle payments, subscriptions, trading and operations for millions of users. If that happens, the execution layer that those agents prefer can accrue real value. On the other hand, the usual early chain risks are all here. Execution risk if mainnet performance or developer experience disappoints. Competitive risk from larger chains that can copy similar identity models or payment standards. Regulatory risk around who is responsible when an autonomous agent causes harm, loses funds or violates sanctions. There is also the simple question of usage. Do agents really need their own chain, or will they live mostly on Ethereum, Solana and whatever your favourite general purpose L1 is?
The design itself is not risk free either. Giving agents explicit identities and scoped permissions reduces blast radius, but it also creates new attack surfaces. Misconfigured policies, bugs in the Agent Passport logic, hostile modules in the agent app store or exploits in x402 implementations could all lead to loss of funds or privilege escalation. If you are a trader deploying capital through agents on Kite, you will still need to think like a security engineer. Who wrote this agent template. How is it updated. What contracts does it talk to. Where are the limits actually enforced. Chains do not magically remove operational risk, they just rearrange it.
Still, it feels like something important is shifting here. For years we pretended that a wallet address was a person. In reality that address is increasingly a swarm of scripts, tools and agents acting in loose coordination. Kite’s core move is to admit that truth at the protocol layer and give those software actors proper first class status, while keeping the human at the top of the stack as the ultimate principal. If you are a trader, that might mean your future PnL comes as much from designing the right agents and permissions as from picking the right tokens. If you are an investor, it means weighing the bet that agent native rails will matter as much as user native ones did in the last cycle. And if you are a builder, it is an invitation to stop thinking of “the user” as someone who clicks buttons, and start thinking of them as someone who hires and supervises machines. In the end, separating users and agents is not just a technical tweak. It is a philosophical claim about who is really acting on chain, and where responsibility and control should live when the markets are mostly moved by code.
