Original Title: How to make fucking $$ in the Agentic Economy 2025 Original Author: Foxi_xyz, Crypto KOL Original Translation: zhouzhou, BlockBeats
Editor’s Note: This article explores the future development of the agent economy, especially the evolution of AI agents. It emphasizes the critical role of infrastructure, frameworks, and technology from simple chatbots in Phase 1 to the combination of privacy and DeFi in Phase 2, and collaboration between agents in Phase 3. Despite the current market being flooded with simple social media agents, the real opportunity lies in technologies and platforms that support autonomous economic activities.
Below is the original content (reorganized for readability):
Agents are not just here to steal your Twitter dynamics—they are reshaping the entire digital economy.
In this article, we will delve into how to discover the next AIagentAlpha by thoroughly understanding the methodology behind it. Remember, once everyone sees it, it is no longer Alpha. The key is to apply this methodology and stay two steps ahead to succeed.
Golden Rule: Consensus
I will dump your coins, and you will dump someone else's. We are all here to make money, so you should never really 'marry' your investment bag. Your task is to find the right timing to offload it. To dump these bad coins on others, you need to find a project that has 'consensus'. This means you are likely to find your exit liquidity.
How to make money?
Predict an emerging trend with firm belief (consensus).
Invest in potential stocks, ensuring they have sufficient legitimacy and innovation.
When consensus forms, sell your bags to others.
The upcoming article will focus on the hardest part: forecasting.
If you have nothing in your head or no personal belief in this trend, then you cannot invest in potential stocks on your own. You either rely entirely on luck or wait for someone else to call you, waiting for KOLs to dump you again. Let's get started.
1. Three Waves of Agent Evolution
Although 2024 will be defined by breakthroughs in AI such as OpenAI's o1 and billion-dollar valuations, 2025 will be the year of AI financialization. However, in this fast-evolving environment, the key to uncovering real value is to go beyond the 'AI agent' hype and understand the fundamental changes that are taking place.
Understanding our position in the adoption cycle is crucial for discovering opportunities. The agent economy is unfolding in three distinct phases:
Wave One: Humans to Agents (Current)
We are currently in this phase—imagine the simple chatbot interactions you see in X (aixbt agent) where these agents primarily act as research assistants and the execution layer of human intent. While valuable, they don't require revolutionary infrastructure changes. Now, most agents look like tailored ChatGPTs, assisting you with simple research. These agents lack high autonomy. They cannot independently manage resources, take risks, or pay for other services.
Wave Two: Agents to Humans (Emerging)
This is where it gets really interesting: AI agents begin to independently handle everyday tasks—such as executing trading strategies, optimizing home energy usage, or negotiating and paying bills—without your constant intervention. While tools like Stripe's Agent SDK can cover some scenarios, they also herald a larger shift: you will no longer pay fixed monthly or yearly fees, but rather see more granular on-demand billing.
As agents take on more responsibilities, they need to cover computing power, API costs per query, model inference costs, etc.—anytime, anywhere. These small-scale on-demand transactions quickly expose the limitations of existing payment systems, as these systems were not designed to support real-time micropayments. And this is where cryptocurrencies can play a role, providing faster settlements, lower fees, and more flexible ways to better meet these new demands than traditional systems.
Some on-chain examples may include:
Automated Trading Systems
Yield Optimization
Portfolio Rebalancing
Wave Three: Agent to Agent/Collaboration (Future)
This is where the biggest opportunities lie. We have seen some early experiments, with projects like Terminal of Truth and Zerebro exploring agent-to-agent business models, but the real potential goes far beyond social media tokens:
Resource Market: Computing agents and storage agents negotiate for optimal data locations
Service Optimization: Database agents negotiating query optimization services with computing agents
Financial Services: Risk Assessment Agents transacting insurance with Coverage Agents
This phase requires infrastructure specifically designed for machine-to-machine interactions, as traditional currency systems, which focus on human verification and control, are inadequate in an economy dominated by autonomous entities. In contrast, stablecoins provide a crucial framework that, due to their programmability, cross-border capabilities, rapid transaction settlements, and facilitation of micropayments, are better suited to address these new demands than traditional systems.
2. Analyzing the Web3 AI Stack
Delphi Digital has already made a fairly clear categorization of the 'decentralized AI' stack, highlighting six key directions (which I believe have high potential), each with some 'sub-industries'. You can refer to them as narratives or innovation directions. I can guarantee that each sub-industry will have a leader that reaches at least 500 million in market capitalization within the next few months.
Six key directions and notable examples:
Application aixbt agent
Agent enablement/coordinating virtuals
Privacy PhalaNetwork
AI Training/Inferences ritualnet
Computing ionet
Data Arweave
Each key direction has many sub-industries, so I won't cover everything here. However, I anticipate a 'sequence of capital inflows'. This sequence will heavily depend on the maturity and development phase of the market. Below is a visual chart I created:
Phase 1:
We see a massive number of agents posting daily, most of which are just wrappers for chatbots/ChatGPT with very limited actual use, but they can be an interesting meme. As we know, whether a product is useful is completely unrelated to its valuation, so many interesting agents with imaginative potential will be hyped.
Agent Enablers become the first level of infrastructure for agents at this stage. For example, as agents generate revenue through audience interaction, those funds will be used to buy back and burn tokens in the liquidity pool paired with $Virtual. This creates a direct correlation between agent success and platform value, incentivizing consistency within the ecosystem.
Phase 2:
If a narrative is left with only Twitter bots spamming, it becomes uninteresting. Thus, we begin to see people incorporating the concept of 'privacy' into it (e.g.: aipool tee and sporedotfun).
The good news is that most people do not understand technical terms like TEE, FHE, ZKP. This instantly makes agent applications seem very innovative, even if these agents may not actually implement TEE. However, all this is to enhance the value of agent applications and give them more 'practicality'. Agents will soon venture into the DeFi/wallet sector.
We will see agents able to perform token swaps, cross-chain bridging, optimize trading routes, and minimize transaction costs for you; these agents will be integrated into wallet interfaces.
The key is that these agents now need to compete on 'technology' rather than 'culture', which is different from Phase 1. Therefore, you will see tokens like $BUZZ or $ACOLYT being hyped because they are backed by a legitimate AI team or developer support (even though they may still be far behind AI experts in Web2).
You will soon see: the 'AI agent wealth effect' will attract a large number of top Web2 AI developers to make money in the Web3 space, leading to many powerful AI projects. If I were you, I would check LinkedIn more frequently than Dexscreener.
Phase 3:
These agents will ultimately mature and derive core value from AI reasoning, data, and distributed computing. We will have TEE-based infrastructure for secure key management, a dedicated data availability (DA) layer to store and retrieve the context of large language models (LLMs), on-chain oracles providing trusted data streams, zkVM frameworks for verifiable execution, and chain abstraction solutions.
This also means we will tap into large-scale, trustless computing resources while ensuring interactions, data flows, and outputs remain verifiable and secure. At this point, advanced infrastructures like ritualnet, ionet, and StoryProtocol will transition from mere speculation to becoming essential for driving the next generation of AI innovation.
Part Three: What should I invest in now?
Let's return to the overview we saw earlier:
I believe we are now transitioning from Phase 1 to Phase 2, and I would be more interested if agents could 'actively' provide us with real value, rather than just tweeting or analyzing token price charts (which I can do with GPT). By 'actively', I mean I assume agents can manage resources for me and make autonomous decisions. They can independently complete transaction settlements.
Some more complex applications I personally would be willing to invest in include:
Automated Trading Systems
Portfolio Rebalancing
Virtual Reality
AI-based smart contracts (prediction market arbitration)
These directions may still be too broad for most people, including myself. According to our golden rule of 'consensus', I observe that most consensus is focused on the following directions:
1. shawmakesmagic
He is the ultimate AI cult leader in this AI supercycle, much like MustStopMurad in the memecoin supercycle. Do not overlook any project that ai16z and shaw/core ai16z members are focusing on. Projects that he monitors and promotes are buying opportunities.
Note: 'ai16z partners' are not always core members, and I can also refer to myself as a partner.
2. Solana Hackathon Winners
This chain is pushing some projects to help you filter potential projects. You need to stay on the market front, selecting some high-quality projects. I've done this work for you, and you can check my posts. I'm not an insider, so I can only judge these projects based on personal experience. You should also do some research on your own.
However, to profit from this narrative, you need tools to help you; otherwise, you will not be able to enter the market at the optimal time.
For example: AgentiPy was initially on my high-quality project list, with a token. Once it launched the token, it skyrocketed to 40M, and I personally couldn't keep up in time. You need a tool to monitor the project's Twitter and enter promptly when a CA (contract address) is detected. More tutorials will be released soon.
3.. AI Frameworks
Do you know why there are now over 500 framework layers, and all decentralized applications (dapps) have transformed into app chains? It's simply due to 'higher valuations'. Infrastructure essentially provides you with higher valuation space. However, not every framework is the same.
You either enter as the market leader or study the technology and GitHub to find a 'good technological infrastructure'. If you can't manage that, the best option is still to find a good entry in $ai16z or $virtual. Don't throw your SOL/ETH into random AI scam projects.
4. DeFi x AI
As mentioned above, I am optimistic about the upcoming DEFAI (the combination of DeFi and AI) narrative. This aligns with my hypothesis for Phase 2 (agents to humans). A good starting point is to learn through the following DeFi x AI projects and their subdivisions:
Ultimately, understanding these dynamics is crucial for identifying real opportunities in the agent economy.
While the current market seems to be dominated by simple social media agents, the real value lies in the infrastructures and frameworks that will drive the next generation of autonomous economic activities. I will continue to hold my $ai16z and $Virtual tokens.
Original Link
