Original text from 0xJeff
Compiled by｜Odaily Planet Daily Golem (@web3golem)_
2024 AI Agent Development Review
2024 is 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 a trend in AI Agents.
Soon after, Virtuals entered the field, pioneering "Agent Tokenization" and solidifying this narrative. Since then, innovation has exploded:
Luna: This agent launched an on-chain wallet tipping feature for fans, now capable of browsing Twitter, analyzing posts, and even joining Google Meet.
Conversational agents on Twitter/X: Some agents have become "parody masters," while others focus on acquiring and sharing Alpha information. For example:
aixbt: Known for concise, actionable insights and some light parody;
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 features, and the ability to exist across platforms. Representative agents include:
AVA and Holoworld AI: The first 3D audio-visual framework, giving agents 3D bodies, voices, and deeper personalities;
zerebro: A music agent that has released top albums and is about to launch its own framework ZerePy, allowing more people to build agents like Zerebro;
Nebula: A Meme AI KOL capable of creating meme images and videos, appearing in AR/VR environments and games;
LucyAI: The first realistic anime agent that can speak multiple languages, capable of live streaming and interacting with fans;
DO KWEEN: A movie agent that produces Netflix-quality drama episodes weekly.
2024 AI Agent Narrative
Meanwhile, ai16z and the open-source innovation movement have also gained attention, especially 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 period, Virtuals has grown into a unicorn company, further solidifying its leadership position in the AI Agent distribution platform.
The open-source innovation movement has sparked interest in the developer community, marking the beginning of the largest community collaboration this year. More and more projects are emphasizing the importance of "open-source frameworks." As agents continue to evolve, new narratives promoting more agent collaboration have emerged:
Agent Metaverse: First proposed by Realis, which created a Minecraft map version of Earth to accommodate these AI agents, allowing them to interact and build a civilization.
Gamification of Agents: ARC Agents represents this field, combining reinforcement learning AI with gaming. By integrating AI with game reinforcement learning, they launched a Flappy Bird-like game where agents compete against each other, with community-contributed game data helping these agents grow. ARC recently revealed its vision towards AGI.
Collective/Swarm Intelligence: FXN represents this field, aiming to establish a unified economy for AI agents, with the idea of agents working together to achieve common goals. Virtuals is also promoting interaction between agents (or commercialization), 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, enabling agents to tokenize, monetize, and trade IP.
Alongside 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 maintained a dominant position in this field, but progress has been temporarily stalled due to a minor bug. Another noteworthy agent is Big Tony, which uses Allora's machine learning price prediction model to automatically trade mainstream currencies.
InvestmentDAO: Initially represented by ai16z, but now more DAOs are emerging, such as AIrthur Hayes and Aimonica. The general narrative is that these DAOs raise SOL on daos.fun (or other platforms) and use these funds for trading and investment profits. If you can use the name of a Crypto VC or a well-known figure, the created InvestmentDAO becomes even more attractive.
DeFi Agent: Led by Mode, which is the preferred ecosystem for DeFi agents. Major application scenarios include AI-driven stablecoin mining, providing liquidity, lending, etc. Quality teams within the ecosystem, such as Giza, Olas, Brian, Sturdy, and QuillAI Network, are involved in the 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 base, especially in the Web2 space.
Abstraction Layer: griffain and Orbit represent this field, providing a chain-based abstract experience for all on-chain content, making it easier for users to operate on-chain, especially friendly for ordinary users.
On-chain VC Agents: sekoia virtuals aims to become a first-level "rubber stamp" for quality agent projects, currently strictly screening investments to only three projects, pioneering the on-chain VC precedent.
Other Narratives: Such as Freysa's on-chain puzzles, JailbreakMe's agent hacking bounty rewards, H4CK Terminal's white-hat AI, and the unique agent models of god and s8n, representing a dialogue debate between God and Satan. More interestingly, there are agents focused 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 $1 billion market cap, indicating that AI Memes are being accepted by the public.
Development of Data and Frameworks
Cookie DAO is becoming a major source of 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 self-learning and self-improvement;
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 others were declining);
AgentTank demonstrates a framework that brings agents to computers, giving them full computational operability, allowing them to engage in entertaining interactions and provide interesting 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 points from this year:
Top teams valued at over $50 million have their own fine-tuned models
They initially showcase the application scenarios and uniqueness of their agents and then provide a no-code framework for others to create agents as good as their flagship agents, which can also lead to higher agent value and drive up agent token prices.
However, this does not mean you should build your own framework or avoid building on other frameworks like Virtuals G.A.M.E and ai16z Eliza. If you lack sufficient AI resources or capabilities, you should join these communities, as tools can help you quickly realize your ideas and experiment. At the same time, you should leverage Virtual and ai16z for distribution/marketing, as these two places currently offer the best visibility, and integrating and collaborating with them is definitely a positive expected value (EV).
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 maintain prices. arc is a great example, as the first Rust framework quickly gained popularity, and its price rose accordingly.
On-chain and DeFi applications will be the product-market fit (PMF) for crypto AI
I believe the areas currently providing the most value include:
Abstraction layers helping people navigate on-chain;
Alpha agents sharing quality alpha, allowing people to profit from these alphas;
Execution agents helping to simplify trading, mining, providing liquidity, and executing loans.
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, introduce data, and clean this data for AI Agents. Although the token economics may have issues, the product is very interesting.
Looking Ahead to AI Agent Development in 2025
In the above, we explored the development of AI Agents in 2024, reviewing the milestones and innovations of the year. Now, we will look ahead to 2025—I believe that 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 Foundation for 2025
Before moving to the next step, it is worth emphasizing that Virtuals will continue to solidify its position as the leading distribution network for AI Agents on Base. Virtuals has become the preferred platform for agents to pair their liquidity, enhance 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 more unique agents emerge on Virtuals and these application scenarios become increasingly diverse, more developers will be attracted to the Virtuals platform, regardless of whether they already have tokens. This growth will also drive up the price of the VIRTUAL token.
While ai16zDao has led the open-source innovation movement with its Eliza framework, it currently lacks a launch platform, and its token economics' value accumulation level is not as strong as Virtuals. Nevertheless, the future remains full of potential. Recently, they have established a working group to improve their token economics, and the 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 conversational agent space focused on Alpha, and it may further solidify its position through sharper responses and more insightful analyses.
As leaders in other verticals emerge, this evolution will be reflected throughout the ecosystem, as they lead the way with 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 and human-like, 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: Agents capable of continuously executing profitable trades;
DeFi-focused Agents: Agents optimizing yield strategies, lending, and liquidity allocation;
Abstract Agents: 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 robust decentralized AI infrastructure.
The Role of Decentralized AI Infrastructure
To scale AI Agents in 2025, decentralized infrastructure is crucial; without it, the field will face bottleneck risks in performance, transparency, and innovation.
Here are the reasons why each part of decentralized AI infrastructure is important, along with 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 just masquerading as a human; whether the output is accurate and generated by the claimed algorithm or model; whether the computations are executed correctly and securely, and so on.
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.
Notable projects:
ORA: Exploring the infrastructure for secure AI, but its token economics still needs improvement;
Hyperbolic: Pioneered sampling proofs for verifying 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, a payment system is needed. Whether transacting with humans or other agents, these systems must handle everything from on-chain/off-chain transactions to barter and accounting. Imagine agents managing finances independently, purchasing computing resources, and even exchanging services with other agents—this is the foundation for commercial transactions between agents.
Notable protocols:
Crossmint: An AI payment tool facilitating transactions;
Nevermined: Supporting commercial transactions and interactions between agents;
Skyfire: Focused on payments and accounting for agent operations.
Decentralized Computing
The computational demands of AI are 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 computing power, and earn rewards.
This year, we even saw the emergence of GPU-backed debt financing models, such as GAIB, helping data centers finance and expand their operations. This enables decentralized computing to be utilized by a broader audience.
Notable protocols:
Aethir: Decentralized computing tailored for AI and Web3.
io.net: 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 impact 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 have emerged 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: Partnering with Virtuals to build the largest decentralized AI data network, supporting dynamic and adaptive AI agents.
Model Creators and Markets
2025 will see an explosive growth of new AI Agents, many of which will be powered by decentralized models. These models will be more advanced, incorporating human-like reasoning, memory, and even cost awareness.
For example, Nous Research is exploring a "hunger" mechanism that introduces economic constraints to AI models. If an agent cannot afford the cost of reasoning, it effectively "dies," teaching it to prioritize tasks more efficiently.
Notable projects:
Nous Research: Introducing a "hunger" mechanism to teach AI resource management;
Pond: Partnering 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 no longer meet the demand. Distributed training spreads the workload 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 for AI." Flock connects AI engineers, model proposers, and data providers to create a marketplace where AI models can be trained, validated, and deployed securely and decentralized. It supports projects like Aimonica and more interesting models.
Collective Intelligence and Coordination Layers
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. Coordination layers abstract complexity, making it easier for agents to collaborate.
For example, Theoriq uses meta-agents to identify the most suitable agents for a task and form a "collective" to achieve goals. It also tracks reputation and contributions to ensure quality and accountability.
Notable projects:
FXN: Creating protocols for unified communication and commerce;
Virtuals: Enabling interactions and integrations 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 faces 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 integrating agents with gaming and immersive virtual worlds;
On-chain and DeFi tools: Protocols like Almanak, Wayfinder, Axal, Cod3x, griffain, and Orbit are building foundational tools for DeFi-driven agents.
Conclusion
2025 will be the year of AI Agents, where we will see them rapidly move towards sentient AGI. These agents will not only perform 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, executing trades, managing your finances, or coordinating 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 beyond 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 deep and shape the future.
2025 is not just a continuation; it is the dawn of a new era for AI Agents.
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