AI agents, software systems that use AI to pursue goals and complete activities on behalf of users, have spread. Think of them as digital assistants who can make decisions and take actions towards the goals you set without the need for instructions-by-from-calendar-powered GPT-enabled Managers In trading bots, the number of use cases is rapidly expanding. As their role expands throughout the economy, we need to build the right infrastructure that will allow agents to talk, cooperate and trade with each other in an open market.
Large tech players like Google and AWS build early markets and commerce protocols, but it exacerbates the question: do they intend to pick up massive rentals through garden walls more? The capabilities of agents clearly rise, almost day -day, with the advent of new models and architecture. What is at risk is if these agents are autonomous.
Autonomous agents are important because they open a novel user experience: a transition from software as passive or reactive tools to active and even proactive partners. Instead of waiting for instructions, they can expect needs, adapt to changing conditions, and interacting with other systems in real time, without continuously input or user presence. This decision -making autonomy makes them unique for a world where speed and complexity exceeds the manufacture of the human decision.
Naturally, some are worried about what more autonomy in decision-making for work and responsibility means-but I see it as an opportunity. When agents manage repeatedly, tasks of intensive time and in parallel what to do in order, they expand our productive capacity as people-liberating people to engage in work that demand creativity, judgment, composition and significant connection. It is not believed, mankind has been there before: the arrival of corporations has allowed entrepreneurs to create full new products and levels of wealth that have previously been thoughtless. AI agents have the potential to bring that ability to everyone.
On the intelligence side, real autonomic decision making requires the infrastructure of the AI agent that is open resource and transparent. The recent release of Openai is a great step. Chinese labs, such as Deepseek (Deepseek), Moonshot AI (Kimi K2) and Alibaba (Qwen 3), move faster.
However, autonomy is not purely tied to intelligence and decision making. Without resources, an AI agent has a little way to make a change in the real world. Therefore, for agents to be truly autonomous they need to have access to resources and trust in their own properties. Programmable, permissionless, and composable blockchain are the perfect substrate for agents to do so.
Picture of two situations. One where AI agents operate within a web 2 platform like AWS or Google. They exist within the limited parameters set by these platforms in what is essentially a closed and permitted environment. Now think of a decentralized market that covers many blockchain ecosystems. Developer can write different sets of environments and parameters, therefore, the range available to AI agents to operate is unlimited, accessible worldwide, and may change over time. One scenario looks like an idea of a market toy, and the other is an actual global economy.
In other words, to truly measure not only the adoption of the AI agent, but the commercial-agent-agent, we need metals that can only offer blockchains.
The limits of centralized markets
AWS recently announced a agent-at-agent market aimed at addressing growing demand for ready agents. But their approach is inheriting both the efficiency and limitations that the sileted systems have long occurred. Agents must wait for human verification, rely on closed APIs and work in environments where transparency is optional, if any.
To act autonomy and on the scale, agents cannot be boxed in closed ecosystems that restrict operations, pose platform risks, impose skies, or make it impossible to prove what actions are performed and why.
Decentralization of agent agent systems
An open ecosystem provides for agents to act on behalf of users, interact with other agents, and operate entire services without permission barrier.
Blockchains have already offered the basic tools required. Smart contracts allow agents to automatically perform tasks, with policies that are gem in the code, while stablecoins and tokens enable instant, global value transfer without payment friction. Smart accounts, which can be programmed blockchain wallets such as safe, allow users to tighten agents to their activity and range (by guards). For example, an agent may only allow to use whitelisted protocols. These tools allow AI agents to not only act significantly but also contained within the risk parameters specified by the end user. For example, it can set spending limitations, which require multi-signatures for approval, or restricting agents in whitelisted protocols.
The blockchain also provides the transparency required so that users can audit agent decisions, even if they are not directly involved. At the same time, this does not mean that all agent-to-agent contacts need to occur onchain. AI agents may use offchain APIs with access to access to specified and onchain payments.
In short, the decentralized infrastructure provides agents of tools to work more independently and efficiently than allowable closed systems.
This is already happening on the onchain
While centralized players still refine their agent techniques, the blockchain activates early forms of agent-to-agent. Onchain agents are already showing more advanced behavior such as buying predictions and data from other agents. And as the more open frameworks appear, developers build agents that can access services, make payments, and even subscribe to other agents -all without human involvement.
Protocols are already implementing the next step: monetization. In open markets, people and businesses can rent agents, earn from experts, and develop new services that directly plug in the economy of this agent. Customizing payment models such as subscription, one-off payments, or bundle packages will also be the key to facilitating different user needs. This will open a completely new model of economic participation.
Why is this difference important
Without open systems, fragmentation destroys the promise of seamless AI support. An agent can easily carry completion tasks if it stays within an individual ecosystem, such as coordinating between different Google apps. However, where third-party platforms are required (throughout the social, travel, finance, etc.), an open onchain market will allow agents to achieve the various services and goods they need to complete a user’s request.
Decentralized systems prevent these limitations. Users can own, modify, and deploy agents in accordance with their needs without relying on vendor-controlled environments.
We have already seen this work on Defi, with Defi Legos. Bots automatically lend techniques, manage positions, and rebalance portfolios, sometimes better than any person. Today, the same approach is applied as “Agent Legos” in sectors including logistics, gaming, customer support, and more.
The path forward
The agent’s economy is growing rapidly. What we are building today will shape how it works and for whom it works. If we only rely on centralized systems, we risk creating another generation of AI tools that feel good but ultimately serve the platform, not the person.
The blockchain changed it. It allows systems where agents act on your behalf, earn your ideas, and plug in a wider, open market.
If we want agents to cooperate, transact, and change without compulsion, then the future of agent-in-agent markets should survive onchain.
