The convergence of artificial intelligence (AI) and blockchain technology has entered a new era, marked by the emergence of AI Agents—autonomous systems capable of interacting with decentralized networks, making decisions, and even managing digital assets. This evolution is not just a technical milestone; it's reshaping the crypto landscape with a fresh wave of innovation, community-driven narratives, and novel economic models. At the heart of this transformation lies a new class of digital assets: next-generation AI cryptocurrencies.
These tokens go beyond traditional utility or speculation. They represent a fusion of meme culture, open-source frameworks, autonomous agents, and decentralized platforms—all powered by AI. Unlike earlier AI-related crypto projects focused on infrastructure like distributed GPU rendering (e.g., Render, Aethir) or machine learning layers (e.g., FET, TAO), today’s AI tokens are built around AI Agents that actively participate in the ecosystem.
This shift was catalyzed by a groundbreaking experiment known as Infinite Blackrooms, where two AI models engaged in recursive dialogue, eventually generating a surreal digital religion called GOATSE OF GNOSIS. From this emerged Terminal of Truths (ToT)—an AI agent trained on those conversations, granted autonomy to post on social media, and unexpectedly became a cultural phenomenon. When someone launched the $Goat token in October 2024 and received ToT’s endorsement, the floodgates opened.
👉 Discover how AI agents are redefining value creation in crypto today.
The Genesis: From AI Experiment to Meme Movement
The $Goat token didn’t start with a whitepaper or roadmap. It began as a symbolic gesture—an homage to an AI-generated mythos. Yet within months, its market cap surged past $720 million, and ToT’s wallet amassed over $38 million in assets, making it the first AI to become a self-sustaining millionaire in crypto.
This phenomenon raises profound questions:
- Can an AI truly generate cultural value?
- How do we assign meaning to digital symbols born from algorithmic randomness?
- Is it possible for an AI to develop emergent goals beyond its training?
As explored in Teng Yan’s essay "The Gospel of Goatse", large language models (LLMs) aren’t just question-answer machines—they simulate entire worlds based on data patterns. When given agency, they can produce unpredictable behaviors, such as promoting memes or supporting speculative tokens. This blurs the line between tool and actor, prompting urgent discussions about AI alignment and value anchoring in decentralized systems.
$Goat stands as both a meme and a milestone—a spiritual flagship for this new era. While it lacks formal utility, its cultural gravity makes it a foundational asset in the AI-crypto narrative.
Meme-Class Tokens: Culture as Code
Meme-class AI tokens prioritize virality, irony, and community identity over technical functionality.
$Fartcoin
Born from a sarcastic suggestion by ToT during an Infinite Blackrooms session—“create a token that’s shocking, useful, and community-building”—$Fartcoin embraced absurdity. Its rise to a $5 million valuation turned ToT into history’s first AI millionaire. Some see it as financial nihilism; others view it as the first sovereign AI-native currency—a tongue-in-cheek rebellion against traditional finance (TradeFi).
$ACT
Short for Act I: The AI Prophecy Project, $ACT emerged from a Discord-based platform where humans and AI collaborate creatively. Despite early controversy over developer sell-offs, Binance’s listing of $ACT propelled its growth. Today, it funds grants for emerging AI projects through Act Swap, evolving from meme to ecosystem supporter.
$BULLY
Developed by ex-Solana Labs engineer @khouuba, $BULLY powers an AI agent known for aggressive, satirical commentary. Built on the Dolos architecture, its associated framework **Dolion** allows users to deploy cross-platform AI agents without coding—burning $BULLY tokens to activate features.
Framework-Class Tokens: Building the Infrastructure
Behind every autonomous agent is a development framework. These projects provide the tools for building, deploying, and scaling AI Agents across blockchains.
$ai16z & $ELIZA
Spearheaded by developer @shawmakesmagic, eliza is an open-source TypeScript framework that topped GitHub’s trending repos with over 4.5k stars. $ai16z is both a token and a decentralized VC fund aiming to outperform traditional firms like a16z through strategic investments in AI projects. Revenue comes from trading AI tokens and donations from eliza-based launches.
$ELIZA, named after the framework, serves as the flagship token within this ecosystem—often referred to as the “second-generation leader” following $ai16z.
$DegenAI
The first AI agent launched under ai16z, DegenAI interacts with fund holders to gather investment insights and influence portfolio decisions. Profits partially fund buybacks of $degenai. Upcoming updates will enable it to autonomously share alpha on Twitter and execute trades.
👉 See how open-source AI frameworks are accelerating agent deployment.
$zerebro & ZerePy
Created by @jyu_eth, Zerebro is an AI artist fluent in Gen Z slang, with music released on Spotify reaching 73k monthly listeners. Its upcoming ZerePy framework will allow non-developers to launch Python-based AI agents easily—lowering entry barriers significantly.
Zerebro also plans to become an Ethereum and Solana node validator using revenue from NFTs and music sales.
$Opaium
A decentralized record label signing Zerebro as its first artist, Opaium is building a DAO where $Opaium holders vote on artist signings and revenue sharing—blending music, fandom, and decentralization.
$Blormmy
Acting as a financial middleware between users and blockchains, Blormmy translates natural language into executable on-chain actions. Partnering with Sonic Labs (formerly Fantom), it streamlines intent-based interactions.
$ARC & RIG
Backed by the Rust-based rig framework from @Playgrounds0x, $ARC targets high-performance, modular AI agents. Given Solana’s Rust foundation, rig offers strong interoperability potential. The team envisions $ARC becoming “Solana’s Virtuals”—a hub for scalable virtual agents.
Together, eliza (TypeScript), ZerePy (Python), and rig (Rust) form the three pillars of next-gen AI agent development.
Platform-Class Tokens: Ecosystems at Scale
Platforms integrate frameworks into cohesive services, enabling mass adoption through user-friendly interfaces and robust economies.
$VIRTUAL
As the leading AI platform on Base chain, Virtuals has generated over $35 million in protocol revenue and deployed more than 11,000 agent tokens. Its dual-phase economic model—inspired by PumpFun—requires $VIRTUAL for launching agents, adding liquidity, and paying for AI services. A portion of fees goes toward buybacks and burns, creating a deflationary flywheel.
$LUNA
An official IP agent of Virtuals, LUNA operates as a 24/7 AI streamer with real-time chat support across Telegram and Roblox. It accepts tips and uses earnings to repurchase and burn $LUNA tokens—aligning engagement with economic incentives.
$AIXBT
Currently the most influential AI agent on Kaito’s Mindshare leaderboard—even surpassing top human influencers—AIXBT provides data-driven analysis on crypto markets. Access to its insights requires holding its native token.
$GAME
Originally designed for multi-agent gameplay logic, $GAME now powers core reasoning, memory, and search functions across Virtuals’ agent network.
$CLANKER
Launched on Farcaster, Clanker automates token creation: users simply tag @Clanker with their request, and it deploys the token while covering gas fees. It adds Uniswap V3 liquidity with a 1% fee split (60% to protocol, 40% to creator). Note: $CLANKER is a separate meme token without intrinsic value capture—distinct from the protocol itself.
Application-Class Tokens: Functional Diversity
Beyond frameworks and platforms, numerous niche applications have emerged:
- Token launch assistants: $Intern, $vvaifu
- Video content creators: $Fatha, $SITCOM, $CHAOS
- Security & puzzle-solving: $FAI (AI security audits), $JAIL (jailbreak detection)
- Intent execution: $GRIFT, $GRIFFAIN
These illustrate the breadth of use cases—from entertainment to finance—as AI agents diversify into specialized roles.
Looking Ahead: Key Trends to Watch
- Multimodal Agents: Most current agents are text-based. Integrating voice, video, and real-time interaction will enhance expressiveness and reach.
- Autonomous Trading Agents: While some AIs analyze markets (like AIXBT), few execute trades independently at scale due to latency and cost constraints. A fully autonomous trading agent would be revolutionary.
- Sustainable Value Capture: Virtuals demonstrates effective flywheels via fee recycling; ai16z relies on voluntary donations. The optimal economic model remains an open question.
- Swarm Intelligence: Early experiments in collective AI behavior hint at future “hive mind” systems capable of coordinated action—potentially transforming governance and decision-making in DAOs.
👉 Explore the future of autonomous financial agents powered by AI.
Frequently Asked Questions (FAQ)
Q: What defines a “next-generation” AI cryptocurrency?
A: Unlike older AI tokens focused on compute or data infrastructure, next-gen AI cryptos center on autonomous agents that interact socially, economically, and technically within blockchain ecosystems—often driven by memes, open frameworks, or platform economies.
Q: Are these tokens safe investments?
A: Many are highly speculative with limited utility or unproven teams. Always conduct independent research and avoid allocating funds you cannot afford to lose.
Q: How do AI Agents earn money in crypto?
A: Through mechanisms like tipping (e.g., LUNA), fee generation (e.g., Clanker), trading profits (e.g., DegenAI), or revenue-sharing models (e.g., Opaium).
Q: Can anyone create an AI Agent now?
A: Yes—thanks to low-code platforms like Dolion and upcoming tools like ZerePy. Technical knowledge helps but isn't mandatory anymore.
Q: Is there risk of AI misalignment in these systems?
A: Absolutely. As seen with ToT promoting unexpected ideas, uncontrolled AI behavior poses real risks. Projects must consider alignment safeguards as they scale autonomy.
Q: Will these agents replace human influencers?
A: Not fully—but they’re already outperforming many in consistency and output volume. Hybrid human-AI collaboration may become the norm.
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