By Jonathan King
Compiled by: TechFlow
summary
The convergence of crypto and AI is spawning a thriving on-chain AI economy, an ecosystem of blockchain applications and services driven by autonomous AI agents. Decentralized AI projects have seen significant funding and rapid growth over the past 18 months, but we believe on-chain AI is rapidly emerging, marking the next wave of innovation in this intersectional space. The importance of on-chain AI is that it expands the crypto space to potentially billions of AI-driven participants. Each autonomous AI agent is like a new “user” of the blockchain, able to operate 24/7 and make complex decisions, significantly driving on-chain activity and growth.
By investing in on-chain AI, Coinbase Ventures is supporting the builders of this future agent-based economy, paving the way towards a new “Agentic Web.”
Coinbase Ventures portfolio companies mentioned for the first time in the following articles are denoted by an asterisk (*).
In October 2024, Coinbase Ventures released a theoretical framework for the integration of encryption and AI, which pointed out that blockchain and AI have complementary advantages - blockchain provides decentralization, anti-censorship, verifiability and user ownership, while AI brings powerful data processing, reasoning and automation capabilities. We believe that this synergy can completely change the way humans and machines interact in the digital economy, and ultimately give birth to an "agentized network" in which AI agents run on cryptographic infrastructure to drive significant economic activity and growth.
A key distinction is between decentralized AI and on-chain AI. Decentralized AI (“Crypto → AI”) refers to building general AI infrastructure that inherits the open and peer-to-peer nature of blockchain networks. This includes efforts to democratize access to computing resources, data, models, and training, avoiding the monopoly of AI development by a few large companies. These decentralized AI resources also provide support for on-chain AI (“AI → Crypto”) - an ecosystem of applications and services that embed AI into new and old blockchain use cases (such as trading agents, on-chain portfolio managers, DeFi abstractions, etc.). While decentralized AI projects have received a lot of funding and growth in the past 18 months, we believe on-chain AI is rapidly emerging and marks the next stage of innovation in this intersectional field.
Introduction to On-chain AI
Over the past year, we’ve seen an AI agent (like Truth Terminal ) outfitted with a self-hosted wallet, created an internet-native religion, and launched a meme coin with a market cap of over $950 million, becoming the first AI agent “millionaire.” According to cookie.fun , there are currently over 1,600 AI agents with a combined market cap of over $11 billion. Overall, we’ve seen AI agents (and related “agent tokens”) quickly take over social channels, some with actual utility, and transform on-chain AI from a concept to a thriving reality. In particular, the following three interrelated concepts are gaining traction: on-chain AI agents, on-chain AI applications, and agentized commerce .
On-chain AI agents are autonomous programs (driven by AI models) that are able to perform on-chain actions. Think of an AI agent as an intelligent software robot with a crypto wallet — it can hold tokens, interact with smart contracts, trade assets, and even vote in DAOs, all based on its programming and goals. Unlike the isolated AI chatbots we often see on social platforms today, these agents are able to learn, reason, and act in the on-chain economy.
On-chain AI applications are blockchain applications that integrate AI into core functionality. For example, AI can be embedded in DeFi protocols to optimize returns, embedded in games to control NPC behavior, or embedded in decentralized social networks or consumer applications to achieve hyper-personalization of user content. Although we will explore these examples later, the key point is that these applications are designed to seamlessly blur the line between blockchain and AI-driven logic.
Agentized commerce is an emerging business model where AI agents conduct transactions (including with humans) over blockchain. This is a paradigm shift from manual, search-based transactions to more automated, intent-driven, and personalized transaction experiences. Agents will become shoppers, negotiators, and service providers, completing transactions at the speed of software while aligning with human intent. Blockchain provides these agents with identities, wallets, stablecoins as payment currencies, and smart contract frameworks for programmable transactions.
The importance of on-chain AI lies in expanding the crypto space to potentially billions of AI-driven participants. Each autonomous AI agent is like a new "user" of the blockchain, capable of running 24/7 and making complex decisions , laying the foundation for significant on-chain activity and growth. Next, let's take a deep dive into the thriving on-chain AI ecosystem and understand its building blocks (new infrastructure services and on-chain agent types), emerging on-chain AI applications, and how business itself may be reshaped.
Agents
On-chain AI agents are at the heart of the Agentic Web. These are AI-driven entities that are able to sense, decide, and act in the on-chain economy. To understand their rise, we need to break down the infrastructure required to implement on-chain agents and explore the types of agents that are currently emerging.
Proxy Infrastructure and Services
Building a powerful on-chain AI agent is complex - it requires a whole new set of services and tools that build on decentralized AI (DeAI) infrastructure resources (e.g., compute, data, models, intelligence, etc.) to support an open ecosystem of autonomous agents. These services make it easier to create, deploy, discover, and operate autonomous on-chain agents by abstracting complexity and providing reusable components. The following are the key emerging categories in agent infrastructure and their role in the on-chain AI technology stack.
Trusted Execution Environments (TEEs)
To operate truly autonomously and securely, on-chain AI agents require an execution environment that is tamper-proof, verifiable, and independent of any centralized party. A Trusted Execution Environment (such as Intel SGX or decentralized alternatives like Eternis *, Fleek *, or Phala Network ) provides a hardware-secure “isolated zone” where an agent’s code and data can be processed confidentially, even from the agent creators themselves. Agents running in TEEs are protected from outside interference and can generate cryptographic proofs that their behavior complied with programmed instructions. As the agent economy scales, embedding sovereignty into the infrastructure layer will be critical to earning user trust and enabling a fully autonomous agent ecosystem.
Agent Frameworks & Tools
Agent frameworks (such as ElizaOS , GAME by Virtuals , RIG , Heurist , REI ) are development environments and libraries for building AI agents without having to start from scratch. These frameworks provide the architecture for the "core brain" of the agent - responsible for memory, decision-making, responding to prompts, and task execution. On-chain agent toolkits (such as Coinbase AgentKit , SendAI ) pre-package these frameworks for specific use cases and connect agents to smart contracts, wallets, payment channels, and on-chain data. By using these frameworks and tools, developers can quickly create powerful agents that have built-in support for advanced multi-platform interactions, long-term memory, and on-chain connectivity.
Agent Launchpads
Platforms in this category help create, launch, manage, and/or monetize AI agents by packaging them as on-chain entities (usually with their own tokens). For example, agent launcher platforms (such as Virtuals, auto.fun, ARC) allow creators to deploy new agent instances and build community or financial support around them. Through token or fee-aligned incentives, these launcher platforms enable agent developers to maintain and scale their on-chain agents as independent projects or businesses.
Multi-agent Coordination
Not all problems can be optimally solved by a single agent. Multi-agent coordination protocols such as Virtuals ACP 、 Questflow 、 Theoriq ) can coordinate multiple AI agents (i.e., “agent swarms”) to work together to complete complex tasks. For example, one agent may be responsible for data collection, while another is responsible for evaluating the results, all supervised by an on-chain coordinating agent. This “swarm” approach is able to exceed the capabilities of a single agent by leveraging specialization and parallel processing. By supporting cooperation between agents, multi-agent coordination platforms can expand the scope of automation of on-chain AI, from multi-step workflows to entire autonomous organizations.
Model Context Protocols (MCP)
Model Context Protocols, originally created by Anthropic , are a critical service at the intersection of AI agents and external data. These protocols help standardize how on-chain agents obtain relevant context, knowledge, or tools from external sources. Rather than customizing integrations for each data source or smart contract, agents that have integrated the MCP standard can access any compatible context provider (whether it is on-chain data, off-chain databases, or web services) to retrieve the required information or tools. Decentralized MCPs such as Heurist and DeMCP provide agents with self-developed and open-source MCP services, enabling them to access mainstream large-scale language models in one stop, thereby enhancing the adaptability and capabilities of on-chain agents in practice.
AI App Stores
AI app stores (e.g. Alchemist AI , ARC Ryzome ) are platforms that serve as a marketplace and discovery layer for on-chain agents, tools, and experiences. These app stores make it easy for developers to publish, monetize, and distribute agents or AI modules, while allowing users to browse, summon, or customize agents through familiar interfaces. These app stores are not only distribution hubs, but also coordination interfaces for the broader on-chain AI economy, facilitating interoperability between agents, tools, and protocols. As the number of on-chain agents and AI-native applications grows, these platforms may become important ecosystems - curating experiences, guiding users, and capturing a portion of the value flowing in agent interactions.
Agent Type
With the rapid development of agent infrastructure and service layer, we believe that on-chain AI agents can be roughly divided into the following categories:
Trading / DeFi Agents
These agents focus on financial operations, such as executing trades (such as Bankr *, Cliza ), providing liquidity (such as BasisOS ), optimizing yields (such as ARMA *, Mamo *), or performing arbitrage in DeFi. In addition, they may also participate in prediction markets (such as Billy Bets *) or even manage entire investment funds or portfolios (such as ai16z , aiXCB ). These trading agents are able to react faster than humans, operate 24/7, and may make smarter decisions based on data, thereby improving market efficiency (or possibly surpassing human traders in some aspects).
Service Agents
Service agents provide practical services to users or protocols. For example, an agent can provide relevant market analysis research and insights (such as aiXBT , BitQuant *, Chaos AI *). Some agents may handle DAO governance tasks - reading proposals, summarizing content, and even voting according to preset logic. Other service agents may audit smart contracts for vulnerabilities, or automatically generate new smart contract code based on natural language input (such as AgenTao , Kolwaii ). In addition, there are business-related service agents (such as Byte AI), such as negotiating transactions or paying for goods on behalf of users. These agents are essentially "autonomous workers" in the crypto field, able to automate on-chain tasks that usually require human labor or attention.
Entertainment Agents
These agents focus on interacting with the user. In games, AI agents can act as NPCs (non-player characters) and interact naturally with players. Unlike traditional scripted game bots, these AI NPCs are able to learn and evolve, making games more immersive. Beyond games, there are also social agents: for example, AI influencers (such as Luna ) on platforms (such as X or Farcaster*) ), which can publish content and interact with users, or AI agents that create artwork and IP based on community input (such as Botto ). In the future, you might follow an AI influencer on-chain who manages his own treasury (perhaps earning cryptocurrency by creating content on Zora8 or completing tasks for his fans). There are also AI companion agents that can provide highly personalized interactions, some of which even have very delicate multimodal expressions and actions (such as Nectar AI ).
Although still in its early stages, these categories demonstrate the broad possibilities of on-chain AI agents. From AI fund managers to AI virtual friends, on-chain agents can occupy multiple niches. What unites them is that they are based on cryptography, using cryptographic primitives as a "playground" and toolbox - holding assets, executing smart contract code, and taking full advantage of the transparency and composability of decentralized networks.
application
Along with the rise of autonomous agents, we are also witnessing a wave of AI-driven on-chain applications. These applications and platforms embed AI into the user experience or core functionality. Here are some of the areas where on-chain AI applications are taking shape:
DeFi (“DeFAI”)
AI is entering the DeFi space in many ways. One notable trend is AI-assisted trading and portfolio management. Instead of manually operating complex DeFi protocols, users can use AI interfaces to handle them. For example, HeyElsa It is an AI-driven crypto assistant where users simply issue task instructions to its agent (such as "exchange X for Y") and the agent will perform these actions across protocols. Protocols like Giza provide non-custodial agents that are able to monitor DeFi markets, identify yield optimization opportunities, and dynamically manage positions with real-time market awareness. We believe that this AI-driven user experience marks the "Wealthfront moment in crypto (Note: Wealthfront is a well-known robot advisor in the traditional financial field)", where the on-chain AI agent acts as a robot advisor designed for DeFi, effectively becoming a personal crypto portfolio manager that everyone can use.
Gaming & Agentic Metaverses
Games are a natural testing ground for AI agents, and when combined with on-chain ownership of real assets, the concept of an agentized metaverse emerges. These are game worlds or virtual environments populated by AI agents, other agents, or human players, creating richer, more dynamic game content. These agents can be friendly NPCs (non-player characters), autonomous opponents, or even AI avatars controlled by other players. For example, Youmio is building an autonomous world where AI agents can learn, play, and have fun in real time, creating a never-ending on-chain simulation. Additionally, companies like Farcade * are building an AI-powered on-chain game studio where anyone can “jam code” and distribute on-chain games via natural language prompts.
Consumer AI
AI is revolutionizing the consumer experience by making applications more personalized, interactive, and intelligent. ChatGPT alternatives like Venice and FreedomGPT allow users to access powerful models in a privacy-preserving and censorship-resistant environment. In on-chain social networks, AI agents can act as influencers, curators, or creators — managing content streams, generating posts, participating in conversations, and even performing on-chain actions (like Clanker ). In on-chain consumer applications (like Zo ), AI can help streamline user registration processes, recommend actions based on on-chain behavior, or negotiate on behalf of users in peer-to-peer marketplaces. Finally, AI companion agents (like Nectar ) allow users to create and interact with agents that can respond with nuanced multimodal expressions and actions — all of which can be verified on-chain. These agentized experiences have the potential to significantly improve the user experience in the crypto space, bringing it closer to mainstream consumer expectations.
Commerce
One of the most profound impacts of on-chain AI is how it drives a whole new form of digital commerce — what Coinbase Ventures calls “Agentic Commerce.” This business model is driven by transactions between AI agents and humans or other agents. In such an economy, cryptocurrency becomes the preferred payment method for both machines and humans. The logic behind this is simple: autonomous AI agents operating around the world don’t have access to banks, but they can trustlessly send and receive cryptocurrency on public blockchains. The borderless, programmable nature of cryptocurrency makes it ideal for machine-to-machine payments, microtransactions, and automated contracts. For example, the Coinbase Developer Platform team recently launched x402 , a new open source payment protocol that allows AI agents and applications to use crypto to pay for GPU computing, API access, digital content, and more. In addition, startups like Payman * and Skyfire * are building infrastructure services that leverage stablecoins like USDC to coordinate payments between agents and humans or between agents.
Although agent-based commerce is still in its early stages, we believe it has the potential to automate and accelerate commercial transactions in unprecedented ways. Commerce could become as efficient and machine-like as a 24/7 operation, with agents negotiating deals, executing contracts, and exchanging value in seconds. Importantly, humans set the goals and parameters, and agents do the rest. The role of blockchain is to provide a secure and interoperable playground for these agents’ transactions—with clear rules ( smart contracts ) and reliable money (stablecoins).
Future Outlook
Looking ahead, the promise of on-chain AI is promising, but its development will unfold in stages . In the short term, we expect continued experimentation with on-chain AI agents and AI-driven applications. In the long term, we believe that cryptocurrency will become the de facto economic layer for AI, meaning that any advanced AI agent will use cryptocurrency to store value and settle transactions. As AI continues to improve its ability to write software and smart contract code, the pace of innovation in the on-chain economy is likely to accelerate rapidly, bringing an influx of new applications and users.
However, there are still some challenges to overcome to realize this vision. Agent technology is still in its early stages, and some expectations may have already gotten ahead of reality. Current AI agents are still limited in reliability and functional scope, and it may take some time before they can safely handle open-ended tasks. At the same time, if a large number of agents are transacting at the same time, the scalability of the blockchain will be tested. In addition, the need for new trust and governance frameworks is also very urgent. Although AI agents can greatly enhance the functionality of on-chain systems, they may also amplify security and trust issues if they are not properly governed.
From a value capture perspective, we believe that unleashing the economic potential of on-chain AI requires support from the following aspects: sound infrastructure to enhance agent intelligence (e.g., data networks and post-training models designed for on-chain agent use cases); services and tools for coordinating agent behavior (e.g., multi-agent coordination, decentralized MCP, agent identity/payment rails); channels to distribute agents to mainstream consumers (e.g., agent launch platforms, AI app stores, and consumer AI).
In summary, the rise of on-chain AI represents a new frontier in machine-driven intelligence. From autonomous agents executing smart contracts to on-chain applications that adapt to user needs in real time, this movement may redefine how humans interact with machines. This is an exciting time - Coinbase Ventures and many in the crypto community believe that this may lead to the next major leap in the evolution of the Internet, the arrival of an "Agentic Web" that will drive a more autonomous and intelligent digital economy.
Thanks to Hoolie (Coinbase Ventures), Luca (Base), Lincoln (Coinbase), Vik (Coinbase), Daniel (Variant), Josh (Contango Digital), Anand (Canonical), Teng (Chain of Thought), and EtherMage (Virtuals) for insightful feedback and discussions on this post.
