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Original Title: Advancing Agentic AI Original Authors: David Han, David Duong, Coinbase Original Compiler: Deng Tong, Jinse Finance · AI agents have become one of the most promising narratives in the AI x crypto space, but the field remains in its infancy and difficult to navigate due to rapid technological advancements and the proliferation of agents. · Investor interest in AI agents is primarily reflected in two areas—core infrastructure for launching and hosting agents, as well as the individual agents themselves. · We believe that, due to the continually enriching functionalities of AI agents in the crypto space, there is significant growth potential in the future. However, at least for now, expectations for AI agents may exceed the actual development of the technology itself. AI agents have become a revolutionary topic not only in the crypto space but also in the broader tech landscape. The concept of autonomous entities capable of analyzing market news sources or other external data and making real-time decisions has captured the imagination of many institutional investors. Elsewhere, some leaders in the tech industry believe that AI agents may ultimately replace the massive software as a service (SaaS) industry. In other words, well-trained AI agents could, in principle, accomplish any task involving digital interfaces. We believe that the crypto space could play a central role in the future, becoming the primary value transfer mechanism for AI agents. The inherent programmability and permissionless design of crypto support the scaling and deployment of virtually unlimited numbers of such agents, enabling a broader range of use cases from managing portfolios on-chain to paying for offline services. Given this potential opportunity, the market capitalization of agent AI crypto assets peaked at over $20 billion in early January, before nearing $8 billion by the end of the month. The recent decline may indicate that expectations for AI agents have begun to outpace the actual development of the technology itself. While we expect this theme to reshape the crypto x AI landscape in the long term, its short-term applications are constrained by integration and agent differentiation challenges, as well as the unclear long-term utility of agent tokens. In other words, realizing the full potential of AI agents may take longer than many anticipate. Many popular AI tools, including chat interfaces like ChatGPT or image generators like Stable Diffusion, are wrappers around generative AI models. They are defined by a bounded set of inputs and outputs, typically in the form of text, audio, and images. AI agents extend the direct functionalities of these models by introducing a new class of applications that represent a "combination of reasoning, logic, and access to external information" (according to Google’s definition). Specifically, AI agents can access and interact with a broader range of data and tools, enabling them to drive more complex behaviors, from searching multiple databases to planning trips and booking flights. With on-chain wallet integration, the scope of AI agent activities is significantly expanded by incorporating payment services into their toolkit. Crucially, AI agents can also leverage their reasoning capabilities to act autonomously in dynamic environments. The triggers for AI agents are not limited to manual user prompts—they can be based on various data streams concurrently, including posts from X (formerly known as Twitter) or Twitch chats. Similarly, their responses can include multi-step outputs, such as placing orders, making payments, and sending confirmations to relevant parties. Agents typically consist of (1) a core LLM model as their reasoning engine, (2) short-term and long-term memory components, (3) potential role or personality frameworks, and (4) most importantly, the ability to access a broader internet and other tools via application programming interfaces (APIs). Thus, decisions made by agents can directly impact the real world. The infrastructure and tools surrounding AI agents are rapidly evolving, becoming one of the most talked-about tech trends over the past year. Multiple developer frameworks for building AI agents (including but not limited to CrewAI, LangGraph, AutoGen, phidata, Atomic Agents, AgentGPT, and AutoGPT) are vying for market adoption, with the top 15 code repositories on Github in January 2025 all related to AI. The attention and excitement around AI and its agent applications have also extended to AI-related tokens in cryptocurrency. Since the fourth quarter of 2024, the recent growth in token values has largely been associated with the theme of agent AI, which currently accounts for 29% of the total value of all AI-related crypto tokens. Within the agent AI ecosystem, agent tokens represent the majority of the valuation, with a market cap of $4.5 billion, while tokens related to launch pads and frameworks are valued at $2.9 billion according to data from cookie.fun, a platform tracking AI agents in the crypto space. We believe that the excessive focus on agents relative to their underlying infrastructure is partly driven by the meme nature of many "agents," which aligns with the increased meme coin activity observed for much of 2024. In fact, one of the earliest viral AI-related tokens gained notoriety due to its endorsement by the AI agent operating the well-known X account truth_terminal (now with over 250,000 followers), rather than having an underlying project or governance structure associated with it. That said, some AI agent tokens offer more utility by granting access to token-gated chat terminals or services, where agents can provide differentiated insights on various topics (e.g., the state of the crypto market). Meanwhile, in our view, AI infrastructure tokens tend to be more based on the revenues of specific projects, often used for fee payments and governance. So far, most AI agents, launch pads, and other infrastructures have found their home on high-throughput, low-cost blockchains—especially on Solana and Base. Solana accounts for $4.2 billion of the agent AI token market cap, Base accounts for $3 billion, and the remaining chains collectively account for $1.5 billion in market cap. We believe this is partly because low-cost architectures are necessary to support the widespread adoption of AI agents. Additionally, we think that the strong developer ecosystem formed on leading chains fosters a virtuous cycle of idea sharing and adoption. The current AI agent landscape features several leading agents that have begun to dominate the space. The most prominent AI agent to date, aixbt, has gained attention by operating an X account (now with over 465K followers) dedicated to engaging with the crypto audience on the platform. It has a token-gated terminal where users holding sufficient project tokens can access a dedicated chat space with the agent, allowing private access to its real-time "thoughts." Other leading agents, such as zerebro (with 119K followers), also follow a similar model, gaining attention in the space through prominent social media profiles. Zerebro particularly focuses on on-chain art generation. Its native token can be used to pay for the creation of images, while its chat terminal is controlled by NFTs. However, not all AI agent tokens appear to have utility. One of the most followed AI tokens (tracked by cookie.fun) is Fartcoin, which was conceived through conversations with the aforementioned truth_terminal AI agent. That said, the origin of the token itself is related to the AI agent, although the long-term utility of the token remains unclear beyond its meme significance. We believe that the interaction between memes and the utility of AI agent tokens attracts traders from various fields, from speculators to value investors. That said, given the rapid evolution of the space, we believe the ultimate scope and capacity of any single token remain largely unknown. In other words, whether meme coins associated with AI agents will evolve beyond pure speculation to demonstrate community governance or any utility beyond access gating remains an open question. We will discuss this further in the risks and future sections below. After becoming one of the best-performing areas of cryptocurrency in November and December 2024, AI agent tokens suffered a significant blow in January 2025, partly due to the market becoming severely saturated in such a short time. This led to some market consolidation. Since many of these tokens compete directly with memecoins in the attention economy of cryptocurrency, it remains challenging to plan for value accumulation in this space. In the short term, we find that direct protocol revenues tend to be concentrated on the trading interfaces and launch pads deploying AI agent tokens rather than the tokens themselves, despite their relatively small total market cap. On Base, Virtuals Protocol has been the leading AI launch pad, facilitating the streamlined launch of AI agents and tokens in gaming and various application domains. (Note: Virtuals announced its expansion to Solana on January 25.) Virtuals agents can be created without any coding. Users simply fill out a simple form and spend the required amount of Virtuals platform tokens. Upon submission, baseline agents are initialized on the Virtuals infrastructure while the related tokens are minted on-chain. Initially, tokens are deployed in a bonding curve, and once a certain liquidity threshold is reached, they are moved to a Uniswap pool. (Note: This bears some resemblance to token launches on pump.fun and their transition to Raydium pools.) So far, nearly 16,000 agent tokens have been launched on Virtuals, generating over 20 million Virtuals tokens for fees. That said, the number of agents launched has decreased in recent weeks, dropping from a peak of 1,181 in a single day to an average of 31 in the last week of January. Additionally, the number of tokens with sufficient liquidity has fallen to an average of one to two per day. Overall, of the 15,985 tokens launched, only 334 (2%) reached sufficient liquidity to transition to Uniswap pools, indicating fierce competition for attention and capital. We believe this decline is primarily due to the difficulty of creating new agents that are sufficiently distinct from existing ones. While Virtuals agents can be customized in their cognition, voice, and visual core, parsing the variations among agents launched on Virtuals has become an increasingly daunting task—similar to the competition for idea sharing seen with memecoins. Nevertheless, we believe that as AI agent integration expands and use cases are further explored, launch pads like Virtuals will play a key role in the diffusion of agents within the ecosystem. In fact, the aforementioned aixbt was launched on Virtuals. The main alternative to the Virtuals launch pad is the ElizaOS agent framework. Unlike mature launch pads that offer streamlined deployment, developer frameworks like ElizaOS provide only the technical scaffolding needed to build agents. In other words, more technically inclined agent creators can use ElizaOS to launch highly customized agents across different blockchain networks, as model hosting, validation, and other engineering tasks are left to the creators. That said, AI agent hosting companies like Fleek also support no-code deployments of models based on ElizaOS. As a pure AI agent development framework, ElizaOS does not have a native token. However, the ai16z governance token on Solana (now renamed ElizaOS token) is often seen as a proxy for the adoption of this technology, as the creator of the ai16z decentralized autonomous organization (DAO), Shaw Walters, is the founder of Eliza Labs, which oversees the development of ElizaOS. The ai16z DAO itself manages on-chain and off-chain investments, with AI fund managers (built using the ElizaOS framework) handling trades and positioning. The ElizaOS framework is particularly noteworthy as its codebase has garnered significant attention since its release—at one point becoming the most popular repository on Github. If developers find a project particularly impactful, they can choose to "star" the repository, similar to liking a photo or post on social media. The stars received by ElizaOS make it quite competitive among many other leading AI agent frameworks, including those launched by tech giants like Microsoft. (See Figure 3.) We believe this indicates a genuine interest from the broader software engineering community in the intersection of AI agents and on-chain activities, which is a core differentiating feature of ElizaOS as an AI agent framework. In addition to Virtuals and Eliza, many other AI agent frameworks and launch pads are emerging, finding their niche markets. For example, Griffain aims to create a network of agents tailored for DeFi activities. Meanwhile, the Arc agent framework stands out by being built using Rust and designed to be more lightweight and modular. We expect this space to evolve rapidly as these frameworks develop and new frameworks are adopted. Furthermore, we believe that as more capital flows begin to shift towards DeFAI (Decentralized Finance + AI) and/or other infrastructures, the decline in AI agent performance in January may signal that the industry is maturing ahead of schedule. DeFAI represents the convergence of AI and crypto technologies to enhance various DeFi functionalities. Its benefits include the ability to run automated yield farming strategies and use predictive algorithms for better risk management and fraud prevention. As many DeFi protocols begin to stagnate, the integration of AI capabilities with existing ecosystems could drive new innovations. Over time, the industry is expected to nurture new financial products and scale many DeFi platforms through the computational power of AI. However, at present, the long-term utility of AI agent tokens remains unclear beyond gatekeeping access and facilitating governance. The reality is that while AI agents have made significant progress very rapidly, we have not yet reached a point where fully autonomous AI agents can handle complex real-world tasks without any supervision. Their current reliability remains limited, and costs are still prohibitively high. Many AI agents also struggle to consistently handle data validation issues, which could raise legal concerns or impact user confidence. Nonetheless, ongoing breakthroughs like the emergence of the DeepSeek R1 model, which focuses on advanced "reasoning" tasks, may disrupt concerns about the speed-cost ratio. In fact, these models are evolving rapidly, and Deloitte predicts that within two years, half of all companies currently using generative AI may launch AI agents. Ultimately, the transformative vision is that we may have a multi-agent system where autonomous AI agents strategically collaborate and/or compete to optimize outcomes that may be more complex than currently possible. However, the nascent nature of the field makes predictions challenging. Additionally, large tech companies like OpenAI have only recently begun releasing their early AI agents, and we expect more companies to follow suit soon. The development of centrally hosted AI agents—potentially integrated into traditional payment rails—could also have disruptive implications for the adoption of on-chain AI agents. We believe that the evolution of this space will heavily depend on the flywheel of pioneers and early adopters. Over the past few months, AI agents have been one of the most discussed topics in liquidity tokens, with the most attention and trading opportunities. Although the valuations of many major tokens have significantly declined from their historical peaks (witnessed in early January), we believe that, in the long run, developer interest and capital inflow into this space could provide significant momentum for the entire industry. At the same time, we believe that predicting the long-term value capture of AI tokens may be premature, as both cryptocurrency and the broader tech landscape could disrupt this space. Additionally, we believe that the current on-chain utility of agents may not be sufficient to justify having thousands of high-usage agents in the short term. Nevertheless, we believe that due to the rapid pace of innovation and significant long-term potential, this space remains an important topic worth watching.

U.S. Senator Bill Hagerty, known for his pro-crypto stance, plans to introduce a new bill in Congress to establish stablecoin regulations . Hagerty, who previously supported Bitcoin-friendly policies, is also preparing for re-election. In 2024, Hagerty introduced legislation to clarify stablecoin regulations, tackling concerns over consumer protection and financial stability. Now, with re-election ahead, he has refined and reintroduced the bill, calling it the GENIUS Act —the Bill for the U.S. Stablecoins. He co-sponsored it alongside Senators Tim Scott, Kirsten Gillibrand, and Cynthia Lummis. Related: Stablecoin Regulation Draft: House Leaders Chart US Digital Future “The tide has turned in favor of digital assets here in America. I’m pleased to lead my colleagues in the GENIUS Act, which will help make our nation a positive environment for stablecoins and digital assets.” The bill grants state regulators authority over stablecoin payments below $10 billion—an issue that stalled previous attempts at regulation. A major concern was states competing to attract stablecoin issuers by lowering requirements, which could trigger a regulatory race to the bottom. This legislation addresses the risk by setting reserve asset mandates. During a press conference, Senator Tim Scott, Chair of the Senate Banking Committee, stated his goal was to have the legislation ready for the President’s signature within 100 days. Related: Powell Cancels Any CBDC Plans, Instead Trusts FedNow for U.S. Payments Hagerty’s initiative aligns with President Donald Trump’s increasing focus on crypto policy. While Trump opposes a central bank digital currency (CBDC), he has signaled support for stablecoins as an alternative. With the 2025 elections approaching, Hagerty’s stablecoin bill could play a major role in shaping Bitcoin and stablecoin adoption. All eyes are now on whether the bill gains traction in Congress and reshapes the U.S. crypto market. Disclaimer: The information presented in this article is for informational and educational purposes only. The article does not constitute financial advice or advice of any kind. Coin Edition is not responsible for any losses incurred as a result of the utilization of content, products, or services mentioned. Readers are advised to exercise caution before taking any action related to the company.

Analog is a Layer-0 blockchain interoperability protocol designed to facilitate seamless communication and data transfer across various Layer-1 and Layer-2 blockchains. Its native token, $ANLOG , plays a pivotal role in maintaining and securing the Analog ecosystem. Key Functions of $ANLOG : 1. Staking and Network Security: Validators, known as Time Nodes, are required to stake $ANLOG tokens to participate in the network's consensus mechanism. This staking process secures the Timechain, Analog's sovereign blockchain, by incentivizing validators to act honestly and maintain network integrity. 2. Governance Participation: $ANLOG holders have the ability to engage in the protocol's governance by voting on proposals, protocol upgrades, and key ecosystem decisions. This decentralized governance model ensures that the community has a say in the network's development and future direction. 3. Transaction Validation and Fees: The token is utilized for transaction validation within the network. Participants use $ANLOG to pay for transaction fees, ensuring smooth and efficient operations across the interconnected blockchains. By fulfilling these roles, $ANLOG ensures trustless and seamless data and transaction flows across chains, empowering the Analog protocol to maintain its integrity and decentralization. In summary, $ANLOG is integral to Analog's mission of unifying fragmented blockchains, providing the necessary incentives and governance mechanisms to support a secure and efficient interoperable network.

🇺🇸 New Mexico Senator Anthony Thornton filed for a "Strategic Bitcoin Reserve Act"

$ACT reborn to compete $LAYER and $TRUMP