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

Author:0xJeff

Translated by: DeepChain TechFlow

Overview

AI agents have rapidly grown to over $2 billion in value within a few months, but also collapsed just as quickly. However, this field is moving towards maturity. Infrastructure, decentralized AI, and practical applications are taking over. How is the next wave forming, and why should we pay attention?

In the fourth quarter of last year, we witnessed the "AI agent" industry, which grew from zero to over $2 billion in value within a few months—ranging from interesting, charming, entertaining, and almost absurd "agents" to financial agents that promised to change the world and make you very wealthy through trading and investing. Moreover, it's not just agents that make you rich, but also many investment DAOs... those DAOs that invest in other agents (or agents) DAOs (3,3).

From Hype to Infrastructure

We all know that in a new industry (with new catalysts such as Web2 AI, Trump's election and support for crypto and AI), people don't care about fundamentals. Anything that creates a lot of discussion, looks like hype, and has a cool demo can easily have a market cap exceeding $100 million.

@virtuals_io became the leader of this ecosystem, controlled the marketing, attracted builders' attention, told the best stories, and created the best narratives. This attracted builders to launch projects on Virtuals and also attracted retail traders to hype them.

Subsequently, @elizaOS emerged, taking a different approach—open-source AI, providing tools for any developer who wants to create "mining" agents. A large movement formed around this idea, with adoption growing at an astonishing rate, with GitHub stars and forks increasing rapidly (and still growing).

The valuation of major Virtuals grew to over $5 billion, with Eliza reaching about half of that at its peak, and many other interesting agents reached eight or nine-digit peaks, such as AIXBT reaching $1 billion. Of course, now things are completely different, with new agents averaging between $3 million and $10 million. The average transaction price of well-performing old agents is between $10 million and $50 million. Valuation caps have compressed, and the total market cap has shrunk from $20 billion to a range of $4-6 billion.

Infrastructure Momentum and Web2 Acceleration

The market is now focusing on "pure fundamentals," with more emphasis on infrastructure and decentralized AI, especially as AI models in Web2 continue to accelerate rapidly—Meta's Llama, OpenAI's GPT, Grok, DeepSeek, Alibaba's Qwen release new improved and optimized models every month. You can see that ChatGPT's image generation model immediately created a viral "Hayao Miyazaki-style" trend.

In addition, due to the improvement of AI model capabilities, the consumer side of Web2 is progressing at a faster pace, making previously impossible things possible—Lovable, Bolt, Cursor, Windsurf allow developers to release more products faster. Agent workflows and AI agents are everywhere. The entry barrier has lowered, and the user switching cost is almost zero. If you don't like an application, you can easily find a competitor service or product with a lower price and better UI/UX.

Awakening of Data Ownership

At the same time, many people began to think: "With so many agent applications that use centralized technologies, who owns my data? Where will my data go? If I discuss some private matters with AI, will it be kept confidential or flow elsewhere?" This is especially important because @OpenAI recently updated ChatGPT to include a memory function that can reference all your past chat records to provide more personalized responses.

Bro… this sounds cool and may trigger a wave of personalized AI agents, co-driving, personal assistants, therapists, partners, etc. You can imagine the impact when your data is owned or controlled by others.

Rise of Decentralized AI (DeAI)

Last year, I made some predictions, one of which was that decentralized AI would emerge in Q2 of 2025, with its infrastructure enhancing confidentiality, transparency, verifiability, and ownership, thus gaining more adoption and attention because the demand for these features is stronger.

There are three independent trend segments, many trends intersecting or converging between them:

• Web2 AI Venture Capital Trends (YC companies launching vertical agents, a16z positioning future consumer trends with their arguments, Perplexity launching its AI fund)

  

• Web3 AI Venture Capital Trends (DeAI infrastructure investments, distributed training, inference networks, etc.)

  

• Web3 AI Retail Trends (AI agent ecosystems, consumer agents, AI consumer applications)

  

Web2 vs Web3 AI: Completely Different Energies

For Web2, since the total addressable market (TAM) is significantly larger than Web3, there are many enterprises that want to transform or optimize their business with AI, improve their workflows to generate more potential customers, more conversions, more sales, retain more customers, reduce management costs, and operate at a higher level. Many enterprises are looking for solutions that can solve highly specific pain points in their particular fields.

This optimization demand has attracted many young startup founders seeking better ways to introduce AI agents to improve workflows. Compared to traditional SaaS, AI agents can significantly save capital or generate more leads. This allows agent startups to charge higher subscription fees (which is why we see many startups reach seven or eight-digit annual recurring revenue within a few months).

For Web3 venture capital, the trends here are very different, as blockchain provides the perfect layer for decentralized AI (DeAI), such as verifiable/immutable transaction trails, trustless environments, decentralized computing, trust-minimized AI inference and training. In short, the future direction is to let people know how their data is processed, understand the AI's thinking process, own their data, own the model, own the use cases, and be incentivized to share (without censorship), etc. Web3 venture capital has been investing in these futures.

Why Retailers Love Agents (Even if They Don’t Fully Understand Decentralized AI)

For Web3 retailers, decentralized AI (DeAI) is very difficult to understand, as it requires learning a lot of terminology and understanding significant content (sometimes it feels like alien language). That's why retailers tend to choose the easiest to understand things—the "Web3 AI agents" that can chat, be funny, and do some entertainment activities.

As retailers continue to stay in this industry, they gradually realize that this is insufficient to create sustainable value for users (yes, many AI agents are useless and lack creativity). This realization (along with market instability) has led to market consolidation, with useless agents gradually dying out, while useful ones remain (although valuations have dropped significantly).

People begin to realize the need for a core AI product with real use cases. This realization has prompted teams to either develop genuine AI products or collaborate with AI companies that have real technology, such as @AlloraNetwork and @opentensor (Bittensor).

This shift has two benefits:

1. It increases people's understanding of less understood infrastructure.

2. It provides actual use cases that AI agents can showcase to the community.

Before this shift: agents had basic skills/use cases (chatting, post analysis)

After this shift: agents have advanced useful skills (AI-driven betting, trading, liquidity provision, mining, etc.

Agents such as @AskBillyBets and @thedkingdao have become ideal agents to showcase Bittensor subnets, bringing cool technology into the mainstream.

Bittensor Ecosystem

What I find interesting about the Bittensor ecosystem is that it's an ecosystem filled with decentralized AI where you can invest. Today, most decentralized AI (DeAI) can only be invested in by VCs or behind-the-scenes strategic investors, as many projects are still in the early stages and have not yet issued tokens.

But Bittensor allows anyone to hold their $TAO and stake it into the subnets they want to support, thereby converting it into alpha tokens of the subnets (investing in decentralized AI projects).

I've publicly shared my fatigue with cross-chain and trading experiences, but the technology, products, and atmosphere there, especially @rayon_labs, are impressive.

The reason I like Rayon Labs is that they are building products with optimized user interfaces and user experiences for consumers. Considering the nature of dTAO, the market determines the emission and pricing of each subnet, so it becomes increasingly important for each subnet to build products that are easy to understand and master.

Rayon has many cool subnets (the coolest might be Gradients, an automated machine learning platform where you can easily train models on the platform), and even cooler is their latest flagship product, Squad AI agent platform, where you can create agents by dragging and dropping block boxes (node builder style, similar to @figma's AI agent creation).

Final Remarks

I'm still in the early stages of exploring Bittensor, and I'll publish a dedicated article later, sharing what I found and how to take advantage of the opportunities. If you want to learn about other trends and changes in the market, please check this article.

Personal Note: Thank you for reading! If you are a subnet owner or researcher on Bittensor, building or researching cool things in the Bittensor ecosystem, I would be happy to connect with you and learn more.