AI agents, software systems that use AI to pursue goals and complete tasks on behalf of users, are proliferating. Think of them as digital assistants that can make decisions and take actions to achieve the goals you set without needing step-by-step instructions: from GPT-powered calendar managers to trading robots, the number of use cases is expanding rapidly. As their role expands throughout the economy, we need to build the right infrastructure that allows these agents to communicate, collaborate and trade with each other in an open market.
Big tech players like Google and AWS are building early marketplaces and trading protocols, but that begs the question: Will they try to extract massive rents through walled gardens once again? Agent capabilities are clearly increasing, almost daily, with the arrival of new models and architectures. What is at risk is whether these agents will be truly autonomous.
Autonomous agents are valuable because they unlock a novel user experience: a shift from software as passive or reactive tools to active and even proactive partners. Instead of waiting for instructions, they can anticipate needs, adapt to changing conditions, and coordinate with other systems in real time, without the constant presence or intervention of the user. This decision-making autonomy makes them especially suited to a world where speed and complexity surpass human decision-making.
Naturally, some are concerned about what greater autonomy in decision-making means for work and accountability, but I see it as an opportunity. When agents handle repetitive, time-consuming tasks and parallelize what previously had to be done in sequence, they expand our productive capacity as human beings, freeing people to pursue work that demands creativity, judgment, composition, and meaningful connection. This is not a fantasy, humanity has been there before: the arrival of corporations allowed entrepreneurs to create entirely new products and levels of wealth previously unthinkable. AI agents have the potential to bring that capability to everyone.
When it comes to intelligence, truly autonomous decision-making requires an AI agent infrastructure that is open source and transparent. OpenAI’s recent OSS release is a good step. Chinese labs, such as DeepSeek (DeepSeek), Moonshot AI (Kimi K2), and Alibaba (Qwen 3), have moved even faster.
However, autonomy is not purely linked to intelligence and decision making. Without resources, an AI agent has little means to implement changes in the real world. Therefore, for agents to be truly autonomous they need to have access to resources and self-custody their assets. Programmable, permissionless, and composable blockchains are the ideal substrate for agents to do this.
Imagine two scenarios. 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, permissioned environment. Now imagine a decentralized marketplace that spans many blockchain ecosystems. Developers can compose different sets of environments and parameters, therefore the scope available for AI agents to operate is unlimited, globally accessible, and can evolve over time. One scenario looks like a toy idea of a market, and the other is a real global economy.
In other words, to truly scale not only AI agent adoption but also agent-to-agent commerce, we need rails that only blockchains can offer.
The limits of centralized markets
AWS recently announced an agent-to-agent marketplace aimed at addressing the growing demand for out-of-the-box agents. But their approach inherits the same inefficiencies and limitations that have long plagued isolated systems. Agents must expect human verification, rely on closed APIs, and operate in environments where transparency is optional, if it exists at all.
To act autonomously and at scale, agents cannot be locked into closed ecosystems that restrict functionality, pose risks to the platform, impose opaque fees, or make it impossible to verify what actions were taken and why.
Decentralization scales agent systems
An open ecosystem allows agents to act on behalf of users, coordinate with other agents, and operate across services without permission barriers.
Blockchains already offer the key tools needed. Smart contracts allow agents to perform tasks automatically, with rules built into the code, while stablecoins and tokens enable instant, global value transfers without payment friction. Smart accounts, which are programmable blockchain wallets like Safe, allow users to restrict the activity and reach of agents (via guards). For example, an agent may only be allowed to use whitelisted protocols. These tools allow AI agents to not only behave expansively but also be contained within risk parameters defined by the end user. For example, this could include setting spending limits, requiring multiple signatures for approvals, or restricting agents to whitelisted protocols.
Blockchain also provides the transparency necessary for users to audit agents’ decisions, even when they are not directly involved. At the same time, this does not mean that all interactions between agents must occur in a chain. For example, AI agents can use off-chain APIs with access restrictions defined and payments executed on-chain.
In short, decentralized infrastructure gives agents the tools to operate more freely and efficiently than closed systems allow.
It’s already happening on the chain
While centralized actors are still refining their agent strategies, blockchain is already enabling early forms of interaction between agents. On-chain agents are already showing more advanced behavior, such as purchase predictions and data from other agents. And as more open frameworks emerge, developers are creating agents that can access services, make payments, and even subscribe to other agents, all without human involvement.
The protocols are already implementing the next step: monetization. With open marketplaces, people and businesses can rent agents, make money with specialized agents, and create new services that plug directly into this agent economy. Customizing payment models, such as subscription, one-time payments or bundled packages, will also be key to meeting different user needs. This will unlock a whole new model of economic participation.
Why is this distinction important?
Without open systems, fragmentation breaks the promise of seamless AI support. An agent can easily complete tasks by staying within an individual ecosystem, such as coordinating between different Google applications. However, when third-party platforms are needed (in social media, travel, finance, etc.), an open chain marketplace will allow agents to programmatically acquire the various services and goods they need to complete a user’s request.
Decentralized systems avoid these limitations. Users can own, modify, and deploy agents tailored to their needs without relying on vendor-controlled environments.
We have already seen this work in DeFi, with DeFi laymen. Bots automate lending strategies, manage positions and rebalance portfolios, sometimes better than any human. Now, that same approach is being applied as “lay agents” in sectors such as logistics, gaming, customer service, and more.
The way forward
The agent economy is growing rapidly. What we build now will determine how it works and who it works for. If we rely solely on centralized systems, we risk creating another generation of AI tools that look useful but ultimately serve the platform, not the person.
Blockchain changes that. It enables systems where agents act on your behalf, earn from your ideas, and connect to a broader open market.
If we want agents to collaborate, transact, and evolve without restrictions, then the future of agent-to-agent marketplaces must live on-chain.
