Original text from 0x Jeff.
Compiled by | Odaily Planet Daily Golem (@web3_golem)
2024 AI Agent Development Review.
2024 will be a transformative year for AI Agents. About three months ago, truth terminal captured everyone's attention with its humorous personality, conversational style, and interactions with A16z co-founder Marc Andreessen, becoming the first 'millionaire agent' and sparking the trend of AI Agents.
Soon after, Virtuals also entered this field, pioneering 'Agent Tokenization' and consolidating this narrative. Since then, innovation has exploded.
Luna: This agent has launched an on-chain wallet tipping feature for fans, now able to browse Twitter, analyze posts, and even join Google Meet.
Conversational agents on Twitter/X: Some agents have become 'prank masters,' while others focus on acquiring and sharing Alpha information. For example:
aixbt: Known for its concise, actionable insights and some light-hearted humor.
Dolos: With a sharp personality, it has now developed its own framework, supporting other agents through Dolion.
At the same time, AI agents are gradually becoming more entertaining, equipped with 3D models, voice capabilities, and the ability to exist across platforms. Representative agents include:
AVA and Holoworld AI: The first 3D audio-video framework, giving agents 3D bodies, voices, and deeper personalities.
zerebro: A music agent that released a top album and is soon launching its own framework ZerePy, allowing more people to build agents like Zerebro.
Nebula: A meme AI KOL that can create meme images, videos, and appear in AR/VR environments and games.
LucyAI: The first realism anime agent capable of speaking multiple languages, live streaming, and interacting with fans.
DO KWEEN: A movie agent producing Netflix-quality drama episodes weekly.
2024 AI Agent Narratives.
Meanwhile, ai16z and the open-source innovation movement have also gained attention, particularly after the launch of the Eliza framework. Developers have come together to create toolkits, plugins, and other features to promote collaboration and innovation. During this time, Virtuals has grown into a unicorn company, further consolidating its leadership position in the AI Agent distribution platform.
The open-source innovation movement has sparked interest in the developer community and has opened the biggest collaborative community event of the year. More and more projects are emphasizing the importance of 'open-source frameworks.' As agents continue to evolve, new narratives are emerging to facilitate more agent collaboration.
Agent Metaverse: First proposed by Realis, it created a Minecraft map version of Earth to house these AI agents, allowing them to interact and build a civilization.
Gamification of Agents: ARC Agents represent this field, featuring reinforcement learning AI x gaming. By combining AI with gaming reinforcement learning, a game similar to Flappy Bird was launched, pitting agents against each other, with community contributions of game data helping these agents grow. ARC recently revealed its vision toward AGI.
Clustering/Collective Intelligence: FXN represents this field, aiming to establish a unified economy for AI agents, with the clustering concept allowing AI agents to work together to achieve common goals. Virtuals is also advancing interactions between agents (or commercialization), which is a communication protocol that allows agents to seamlessly provide services to each other. Meanwhile, Story announced the launch of an inter-agent communication protocol for IP, allowing agents to tokenize, monetize, and trade/buy IP.
In parallel with these narratives, we can also see:
On-chain trading agents: Initially proposed by Spectral, their Syntax v2 allows users to launch trading agents that can trade on Hyperliquid. They have dominated the field, but progress has been temporarily stalled due to a small vulnerability. Another agent to watch is Big Tony, which automatically trades mainstream currencies using Allora's machine learning price prediction model.
InvestmentDAO: Initially represented by ai16z, but now more DAOs are starting to emerge, such as AIrthur Hayes and Aimonica. The general narrative is that these DAOs raise SOL on daos.fun (or other platforms) and use the funds for trading and investment profits. If you can use the name of Crypto VC or a well-known figure, the created InvestmentDAO is more attractive.
DeFi Agent: Led by Mode, it is the preferred ecosystem for DeFi agents. Major application scenarios include AI-driven stablecoin mining, providing liquidity, lending, etc. High-quality teams within ecosystems such as Giza, Olas, Brian, Sturdy, and QuillAI Network are involved in its construction.
AI App Store: ALCHEMIST AI represents this field, providing a no-code tool that allows users to create applications. MyShell is another AI app platform with a larger developer and user community, especially in the Web2 space.
Abstract Layer: griffain and Orbit are representatives in this field, providing a chain-based abstract experience for all content on-chain, making it convenient for users to operate on-chain, which is particularly user-friendly for the average user.
On-chain VC Agent: sekoia virtuals aims to become the primary 'rubber stamp' for quality agency projects, currently strictly selecting investments for only three projects, pioneering the on-chain VC precedent.
Other Narratives: Such as Freysa's on-chain puzzles, JailbreakMe's bounty rewards for proxy cracking, H 4 CK Terminal's white hat AI, and the unique proxy models of god and s 8 n, representing a dialogue and debate between God and Satan. More interestingly, there are proxies focusing on Alpha analysis, such as Rei (quantitative analyst), kwantxbt (TA analyst), and Nikita (general alpha analyst). Then there's Fartcoin, a suddenly popular meme project that even appeared on Stephen Colbert's show and surpassed a market cap of $1 billion; AI memes are being accepted by the public.
The development of data and frameworks.
Cookie DAO is becoming the primary source for AI agent data and social metrics, relied upon by industry insiders to track agent influence, market value, and performance.
Masa integrates with Virtuals to provide agents with real-time data, enabling them to self-learn and self-improve.
TAOCAT is the first virtual agent powered by the Bittensor subnet, showcasing the potential of real-time data (it is the only agent token that surged while other agent tokens were falling).
AgentTank showcases a framework that brings agents to computers, giving them full computable operability, allowing them to engage in entertaining interactions on the internet and provide amusing commentary.
Other New Frameworks:
arc: A Rust-based RIG framework that has gained attention for its versatility.
Dolion: Evolved from Dolos, becoming a toolkit for creating unique agents.
What have we learned from 2024?
The above may have overlooked some minor narratives or AI agents, but through the development of AI agents, we can learn the following from this year:
Top teams valued over $50 million have their own tuned models.
They initially showcase the application scenarios and uniqueness of their agents, then provide a no-code framework for others to have agents as good as their flagship agents, which can also bring higher agent value and boost agent token prices.
But this does not mean you should build your own framework or not build on other frameworks like Virtuals G.A.M.E and ai16z Eliza. If you don't have enough AI resources or capabilities, you should join these communities, as with the right tools, you can quickly realize your ideas and experiment. At the same time, you should leverage Virtual and ai16z for distribution/marketing, as both currently offer the best visibility, and integrating and collaborating with them is absolutely a positive expected value.
Investing in agents with built-in frameworks or the entire AI agent ecosystem will yield better risk-return ratios.
If they manage to create a framework that people are willing to pay to build agents, it means that the framework has enough attention and demand to drive or sustain prices. Arc is a great example, the first Rust framework that rapidly gained popularity, and its price rose accordingly.
On-chain and DeFi applications will be the product-market fit (PMF) of crypto AI.
I believe the areas currently bringing the most value include:
The abstract layer helps people navigate on-chain.
Alpha agents share high-quality alpha, allowing people to profit from these alphas.
Execution agents can help simplify trading, mining, liquidity provision, and lending execution.
Perhaps we will soon see an agent that combines alpha discovery + execution.
Data is an indispensable part of every agent.
Bad data = bad output. If data is gold, then data platforms like Cookie DAO are essentially gold mines. Vana is an interesting L1 that tokenizes data into data liquidity pools; they have a DataDAO model that helps people co-own data, bring in data, and clean this data for AI agents. Although there may be issues with the tokenomics, the product is very interesting.
Looking ahead to the development of AI Agents in 2025.
Above, we explored the development of AI Agents in 2024, reviewing the milestones and innovations of the year. Now, we will look forward to 2025—I believe this year AI Agents will not only become more useful but will also begin to reshape our views on autonomy, intelligence, and collaboration.
Laying the groundwork for 2025.
Before moving to the next step, it is worth emphasizing that Virtuals will continue to solidify its position as the primary distribution network for AI Agents on Base. Virtuals has become the preferred platform for agents to pair their liquidity, increase visibility, and form deeper collaborations with other quality projects. Currently, the total market cap of Virtuals agents is approximately $3 billion, accounting for 77% of the entire AI Agent field (data source: Cookie DAO).
As unique agents on Virtuals increase, and as these application scenarios diversify, more developers will be attracted to the Virtuals platform, regardless of whether they already have tokens. This growth will also drive the rise of the VIRTUAL token.
While ai16z Dao has led the open-source innovation movement with its Eliza framework, it currently lacks a launch platform, and its tokenomics value accumulation level is not as high as Virtuals. Nevertheless, the future still holds potential. Recently, they have formed a working group to improve their tokenomics, and a future launch platform may position ai16z as the top distribution platform on Solana, surpassing existing launch platforms (if they decide to launch one).
In 2025, we will also see top agents with product-market fit (PMF) receive significant capability upgrades. For example, AIXBT has already established a leadership position in the dialogue agent field focused on Alpha and may further solidify its position through sharper responses and more insightful analyses.
As leaders emerge in other verticals, this evolution will be reflected throughout the ecosystem, as they lead the way through unique expertise and innovation.
What are the trends for 2025?
2025 will be a year of specialization for AI Agents. We will see leaders emerge in various verticals, each dominating its own niche market.
3D Models: Agents with high-quality visual designs suitable for gaming, AR/VR, etc.
Voice Modules: Agents capable of speaking naturally, like humans, and evoking emotional resonance.
Personality-rich Agents: Personalized conversational agents with unique and relatable personalities.
Live Streaming Agents: Interactive agents thriving on platforms like Twitter/X and YouTube.
Automated Trading Agents: Capable of continuously executing profitable trades.
DeFi-focused Agents: Optimizing yield strategies, lending, and liquidity allocation.
Abstract Agents: Enabling seamless on-chain interactions through user-friendly UIs.
Just as humans are diverse and specialized, AI Agents will become equally diverse. The uniqueness of each agent will be closely related to its underlying model, data, and infrastructure. However, the success of this ecosystem depends on a strong decentralized AI infrastructure.
The Role of Decentralized AI Infrastructure.
To expand AI agents in 2025, decentralized infrastructure is crucial; without it, the field will face performance, transparency, and innovation bottleneck risks.
Here are the reasons why each part of decentralized AI infrastructure is important, and the projects currently being built to address these challenges:
Verifiability.
Trust is the foundation of decentralized AI. As AI Agents become more autonomous, we need systems that allow us to verify what is happening in the background. We need to know whether this 'agent' is a real AI or masquerading as a human; whether the output is accurate, and generated by the claimed algorithms or models; whether computations are executed correctly and securely, etc.
This also involves Trusted Execution Environments (TEE), which ensure that agents operate independently, securely, and without manipulation. Without verifiability, there is no trust, and without trust, the ecosystem cannot scale.
Projects to watch:
ORA: Exploring the infrastructure for secure AI, but tokenomics still needs improvement.
Hyperbolic: Pioneered sampling proofs for validating AI computations and reasoning.
Phala Network: Known for its TEE infrastructure, adding a layer of security for decentralized AI.
Payments.
For AI Agents to operate autonomously in the real world, payment systems are required. Whether transacting with humans or other agents, these systems must handle everything from on-chain/off-chain transactions to barter exchanges and accounting. Imagine agents independently managing finances, purchasing computational resources, or even exchanging services with other agents—this forms the basis of commercial transactions between agents.
Notable Protocols:
Crossmint: AI payment tools that facilitate transactions.
Nevermined: Supports commercial transactions and interactions between agents.
Skyfire: Focused on payment and accounting operations for agents.
Decentralized Computing.
The computational demand for AI is skyrocketing—doubling approximately every 100 days. Traditional cloud services like AWS cannot meet this demand in terms of cost or accessibility. Decentralized computing networks allow anyone with idle resources to join the network, provide their computational capacity, and earn rewards.
This year, we even saw the emergence of GPU-supported debt financing models like GAIB, which help data centers finance and expand their operations. This enables decentralized computing to be used by a broader audience.
Notable Protocols:
Aethir: Decentralized computing tailored for AI and Web3.
io.net: Providing scalable computing solutions for AI workloads.
Data.
If AI is the brain, then data is the oxygen. The quality, reliability, and integrity of data directly affect the performance of AI models. However, the cost of acquiring and labeling high-quality data is high, and poor data can lead to poor outcomes.
Excitingly, some platforms are emerging that allow users to own their data and monetize it. For example, vana allows contributors to tokenize their data and trade it in a Data Liquidity Pool (DLP). Imagine choosing TikTok DataDAO or Reddit DataDAO to aggregate your contributions—this concept empowers users while driving AI development.
Notable Protocols:
Cookie DAO: A reliable source of data metrics and insights.
vana: Tokenizing user data into liquidity pools that can be traded on decentralized markets.
Masa: Collaborating with Virtuals to build the largest decentralized AI data network to support dynamic and adaptive AI agents.
Model creators and markets.
2025 will witness explosive growth in new AI agents, many of which will be supported by decentralized models. These models will be more advanced, integrating human-like reasoning, memory, and even cost awareness.
For example, Nous Research is studying a 'hunger' mechanism that introduces economic constraints for AI models. If an agent cannot afford the reasoning costs, it effectively 'dies,' teaching it to prioritize tasks more efficiently.
Notable Projects:
Nous Research: Introducing a 'hunger' mechanism to teach AI resource management.
Pond: Collaborating with Virtuals to provide tools for decentralized model creation and training.
Bagel: Providing privacy-preserving infrastructure using FHE and TEE.
Distributed training and federated learning.
As AI models become larger and more complex, centralized training systems will not meet demand. Distributed training spreads workloads across multiple decentralized nodes, making the process faster and more efficient. At the same time, federated learning allows organizations to collaboratively train models without sharing raw data, addressing major privacy concerns.
FLock.io is the 'Uber of Artificial Intelligence.' Flock connects AI engineers, model proposers, and data providers to create a marketplace where AI models can be trained, validated, and deployed in a secure and decentralized manner. It supports projects like Aimonica and other interesting models.
Collective Intelligence and Coordination Layer.
As more specialized agents enter the ecosystem, seamless communication between them becomes crucial. Collective intelligence allows agents to work together as a team, pooling their capabilities to achieve common goals. The coordination layer abstracts complexity, making collaboration easier for agents.
For example, Theoriq uses meta-agents to identify the agents most suited for a particular task and form a 'swarm' to achieve goals. It also tracks reputation and contributions, ensuring quality and accountability.
Notable Projects:
FXN: Creating protocols for unified communication and business.
Virtuals: Enabling interaction and integration between agents.
Theoriq: Developing agents and building advanced coordination tools for AI agents, including clustering and task delegation.
Why decentralized infrastructure is crucial.
The next phase of AI agent development depends on infrastructure. Without verifiability, payment systems, scalable computing, and robust data pipelines, the entire ecosystem would face the risk of stagnation. Decentralized infrastructure helps address these issues by providing trust and transparency, scalability, collaboration, and empowerment.
Of course, several other narratives are expected to develop in 2025, such as:
Agent Metaverse / AI x Gaming: Projects like Realis and ARC Agents are merging agents with gaming and immersive virtual worlds.
On-chain and DeFi tools: Protocols such as Almanak, Wayfinder, Axal, Cod 3 x, griffain, and Orbit are building essential tools for DeFi-driven agents.
Summary.
2025 will be the year of AI Agents, when we will see them rapidly advance toward sentient AGI. These agents will not only execute isolated tasks—they will autonomously trade, collaborate with other agents, and interact with humans in ways we cannot yet imagine.
Imagine an agent analyzing market data, trading, managing your finances, or coordinating to complete complex tasks with others. They will seamlessly integrate into our lives, handling everything from on-chain DeFi operations to real-world interactions, with autonomy and intelligence far exceeding what we see today.
The decentralized infrastructure currently being built (verifiable systems, payment tools, computing networks, and coordination layers) will make this future possible. For builders, investors, and enthusiasts, now is the time to delve into research and shape the future.
2025 is not just a continuation; it is the dawn of the next era for AI Agents.
