From Hype to Practicality: The Value Transformation of Web3 AI Agents

Original Title: Post-AI Agent Bubble: Where's the Real Value in Web3 AI?

Original Author: 0x Jeff

Original Compilation: Ethan, Odaily Planet Daily

Brief Overview:

The total market capitalization of AI agents has grown from zero to over $20 billion in just a few months, only to crash rapidly. However, this field is gradually maturing. Infrastructure, decentralized AI, and real utility are starting to dominate. How will the next wave of development shape the future, and why is it worth paying attention to?

In the fourth quarter of last year, we witnessed one of the fastest-growing sectors, "AI agents," skyrocketing from zero to over $20 billion in just a few months—ranging from some interesting, charismatic, and entertaining "agents" to financial agents promising to change the world and make you rich overnight through trading and investment. Moreover… it's not just those agents that can make you wealthy; investments in DAOs are also emerging… human (or agent) DAOs (3, 3) investing in other agents.

From Hype to Infrastructure: The Evolution of Web3 AI Agents

We all understand that in an emerging field (and against the backdrop of Web2 AI, Trump's election, and new catalysts supporting cryptocurrency and AI), people are not concerned about fundamentals. Anything that can create noise, appears full of hype, and has a flashy presentation can almost quickly reach a market cap of over $100 million.

@virtuals_io has captured the market by seizing attention, telling compelling stories, and crafting the best narratives. This attracted a large number of creators to publish content and launch projects on Virtuals, while also drawing the attention of retail investors, capitalizing on the hype.

@elizaOS then emerged, taking a different approach—open-source AI, allowing any developer to use "shovels" to mine for gold. A massive dissemination effect formed around this idea, with rapid adoption, and the number of stars and forks on GitHub skyrocketing (these numbers continue to grow).

The valuation of Virtuals has grown to over $5 billion, while Eliza accounted for about half of that at its peak market cap, with other interesting agents reaching valuations in the 8-9 figure range, such as AIXBT reaching $1 billion. Of course, the situation is very different now, with newly launched, well-performing agents averaging valuations between $3 million and $10 million. The valuations of older, well-performing agents average between $10 million and $50 million. The valuation ceiling has compressed, and the overall market cap has shrunk from $20 billion to a range of $4 billion to $6 billion.

Infrastructure Acceleration and Rapid Advancement of Web2

The market is now beginning to focus on "pure fundamentals," with greater concern for infrastructure, decentralized AI, especially as AI models in Web2 continue to accelerate at an astonishing pace—Meta's Llama, OpenAI's GPT, Grok, DeepSeek, Alibaba's Qwen, etc., are releasing new improvements and optimized models monthly. The image generation model of ChatGPT quickly sparked a "Ghibli-ization" trend after its release.

On top of all this, the consumer layer of Web2 is developing at a pace far faster than ever due to the enhanced capabilities of AI models—things that were previously impossible are now becoming feasible. Tools like Lovable, Bolt, Cursor, and Windsurf enable developers to launch more products more quickly. Agent workflows and AI agents are everywhere. The entry barrier has lowered, and the switching costs for users are almost zero—if you dislike an application, you can easily find a more competitive service or product with a better interface and user experience.

Awakening of Data Ownership: The Call for Decentralized AI

Meanwhile, many people are starting to think: "Since so many agent applications are using centralized technology, who owns my data? Where does my data go? If I discuss something private with AI, will it keep it confidential? Or will it leak out?" This question is particularly important, especially since OpenAI's recent updates mentioned that ChatGPT can now reference your past chat history to provide more personalized responses.

Ah… all of this sounds cool, and it is likely to trigger a wave of personalized AI agents, such as co-pilots, personal assistants, therapists, companions, etc. But you can imagine the consequences when others own or control your data.

Decentralized AI (DeAI): The Power Leading the Future

I made some predictions last year, one of which is that decentralized AI will emerge in the second quarter of 2025, with infrastructure enhancing confidentiality, transparency, verifiability, and data ownership, thus gaining more adoption and attention.

This trend can be divided into three main parts, with many trends intersecting or intertwining:

• Web2 AI venture capital trends (YC companies launching vertical agents, a16z positioning for future consumer trends, Perplexity launching AI funds)

• Web3 AI venture capital trends (DeAI infrastructure investment, distributed training, inference networks, etc.)

• Web3 AI retail trends (AI agent ecosystem, consumer agents, AI consumer applications)

Web2 and Web3 AI: The Collision of Two Worlds

For Web2, the total addressable market (TAM) is much larger than Web3, meaning that many businesses are seeking to transform and optimize their operations through AI, improving workflows to generate more leads, more conversions, higher sales, retaining more customers, and reducing administrative costs to operate more efficiently. Thus, many businesses are looking for solutions that can address their specific pain points.

This demand for optimization has attracted many young entrepreneurs to seek better ways to integrate AI agents into workflows. Compared to traditional SaaS, the solutions provided by AI agents can save substantial amounts of money or generate more leads. This allows agent startups to charge higher subscription fees for their usage (which is also why we see many startups reaching 7-8 figure annual revenues within months).

For Web3 venture capital, the trends here are entirely different, as blockchain provides the perfect infrastructure layer for DeAI, such as verifiable/immutable transaction records, trustless environments, decentralized computing, and minimal trust AI reasoning and training (sorry for the jargon, but you should get the gist of what I'm trying to convey).

In short, the future direction is for people to understand how their data is processed, comprehend the thought processes of AI, own their data, possess their models and use cases, and be motivated to share (without censorship), etc. Web3 venture capital has already invested in these future trends.

The AI Agent Craze in the Retail Market: More Than Just Entertainment

For the Web3 retail market, DeAI is very difficult to grasp, as it requires you to learn a lot of terminology and understand the key points (sometimes it feels like an alien language). This is why retail market users prefer the most easily understandable things—like "Web3 AI agents" that start with chatbots, which are humorous and can create entertaining content.

As the retail market continues to delve into this industry, they gradually realize that these basic skills of chatting and analyzing are not enough to create sustainable value for users. This realization (combined with a poor market environment) has prompted market consolidation, with useless agents gradually disappearing while useful agents continue to survive (even though their valuations have significantly decreased).

People are beginning to understand that AI products must have a core practical use case. This awareness has prompted teams to either develop genuine AI products or collaborate with truly technical AI companies, such as @AlloraNetwork and @opentensor (Bittensor).

The benefits of this shift are twofold:

(i) It has given people a better understanding of infrastructure.

(ii) It has provided AI agents with real use cases, enabling them to demonstrate their value to the community.

• Before the shift: Agents with basic skills/use cases (chatting, analyzing, etc.)

• After the shift: Agents with advanced practical skills (such as AI-driven betting, trading, liquidity provision, farming, etc.)

Agents like @AskBillyBets and @thedkingdao have become ideal agents, showcasing the Bittensor subnet and bringing cool technology into the mainstream.

The Bittensor Ecosystem: New Investment Opportunities in Decentralized AI

I find one interesting aspect of the Bittensor ecosystem is that it is a decentralized AI ecosystem where anyone can invest. Nowadays, most decentralized AI projects are limited to VC or strategic investors working behind closed doors, as they are still in the early stages, and many projects have yet to issue tokens.

However, Bittensor allows anyone to stake their $TAO into the subnet they wish to support, converting it into the subnet's alpha token (directly participating in DeAI projects).

Although I have previously expressed disappointment with bridging and trading experiences, Bittensor's technology, products, and atmosphere are outstanding, especially the team at @rayon_labs.

I love Rayon Labs because they have done a lot of consumer-friendly work in optimizing UI/UX. Given the characteristics of dTAO—the market determines the emission of each subnet and the pricing of the subnet—it becomes particularly important to build products that are easy to understand and comprehend for each subnet.

Rayon has many cool subnets (the coolest of which might be Gradients, an AutoML platform that allows easy training of models on the platform), and even cooler is their latest flagship product, the Squad AI agent platform, which allows users to create agents through a drag-and-drop interface (similar to Figma's AI agent creation method).

Conclusion

I am still in the early stages of deeply understanding Bittensor and will publish a dedicated article later to share interesting findings and demonstrate how to seize opportunities from it.