Author: David C, Bankless; Translator: Baishui, Golden Finance
AI agents have recently become a focus in the technology field (and not just the cryptocurrency field) as major companies compete to invest in software that can observe, reason and act on their own. These systems, sometimes called autonomous agents, are expected to change daily life - one day, they may plan our schedules, shop for us online, or even build software without our direct help.
ChatGPT brought a key spark that turned advanced AI from a futuristic idea into a widely used tool, proving that these models can learn and adapt in real time. As developers realize that AI can do more than just answer text prompts - such as handling tasks such as managing calendars or coding - AI agents have become the focus of attention.
Although it is still in its early stages, the potential of these systems is constantly being recognized. That said, AI agents can be difficult to grasp at first. In this article, we will clearly define them, and how agents are different from regular "bots" or "workflows", and then outline their synergy with blockchain. Let's get started.
AI Agents Explained
AI agents are dynamic software systems designed to handle tasks with minimal human supervision. They use advanced AI tools to process data inputs (such as text, images, or blockchain records) to achieve specific goals. Unlike simple robots that follow strict rules for automation, AI agents bring intelligence, adaptability, and autonomy to their tasks.
Agents are often confused with robots, which are simply automated tools that perform functions according to predefined parameters. For example, a robot might follow a script to send an alert, place an order, or collect data when certain conditions are met, essentially operating through an "Action A triggers Action B" workflow. While robots are efficient at repetitive tasks, they strictly follow the rules set by their creators and lack the ability to adapt or learn.
Agents, on the other hand, leverage advanced techniques such as Large Language Models (LLMs) to understand context, learn from interactions, and adapt to unforeseen situations.
This autonomy enables them to improve their approaches in real time to better achieve their goals, even in a changing environment. By combining automation with intelligence, agents can handle complex tasks that require contextual awareness and intentionality, providing capabilities that go far beyond the limitations of traditional robots.
Over time, this flexibility could enable them to become personal assistants, financial managers, or autonomous problem solvers across a range of applications.
How Do AI Agents Fit Into Crypto?
While this cycle has been referred to as the AI x Crypto cycle for some time, AI agents have recently become particularly popular in our industry.
While their initial use cases may seem simple or like GOAT or other “chatbots,” it turns out that the synergy between the two technologies is more fundamental. First, because many agents provide services, they also need to make payments, which traditional financial infrastructure cannot provide them. For example, opening a bank account or signing a contract often requires meeting a banker or notary. Since AI agents are not actually people, they do not have passports or any necessary banking documents - making it difficult for them to interact with traditional finance and receive or make payments.
Crypto solves this problem, however.
On a blockchain, it doesn’t matter whether the actor is human or software, which means agents can own digital assets, make or receive payments for services, or interact directly with smart contracts, addressing the limitations that the current financial system imposes on them. Furthermore, once these contracts are deployed, anyone or anything (including AI agents) can use them. This arrangement stands in stark contrast to traditional finance, where every new entity must apply for and be approved, whereas users on a blockchain (whether human or AI) can access all smart contracts running on the blockchain.
In addition, because many blockchains are enabled with open source protocols, AI agents may have a wider range of tools to integrate, giving them a wider toolbox to complete tasks on-chain (or even off-chain), thereby enhancing their autonomy and expanding their potential impact.
Beyond providing the required economic imperatives for agents, blockchain also plays a key role in addressing concerns about “black box” AI. With AGI becoming a matter of when, rather than if, many worry that AI in its current opaque state could create serious imbalances and lead to unintended consequences, posing a huge threat to society. However, by operating on a decentralized network, the operations of AI are transparent, difficult to monopolize, and prevent abuse or single points of failure. Cryptography can therefore serve as a safeguard against such behavior, making the actions of AI and AI agents verifiable on-chain.
Agents Matter
In short, AI agents change the way we think about software and automation by introducing intelligence, adaptability, and independence — expanding the possibilities beyond the predefined workflows typical of simple robots.
While agents can operate in dynamic environments, whether involving planning, trading, or interacting with real-world applications, by leveraging blockchain, these agents can overcome the limitations imposed on them by traditional finance, greatly increasing their potential to deliver services and achieve goals. Coupled with the transparency of decentralized networks, this convergence of AI and cryptocurrency promises to usher in an era in which agents can confidently navigate financial services and keep their processes verifiable on-chain. As the capabilities of AI agents and blockchain ecosystems continue to evolve, their synergy will reshape how we approach large-scale tasks both on-chain and off-chain, creating a future marked by greater intelligence and greater achievement.