After the AI Agent bubble bursts: What is the real value of Web3 AI?

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In the fourth quarter of last year, the AI agent track soared like a rocket, from almost zero to a market value of more than 20 billion US dollars . Various intelligent agents became popular at the same time – funny and even weird. Then everyone began to look forward to those financial agents that can automatically trade kriptocurrencies and help you make money, and various InvestmentDAOs that claim to invest in other agents, and even DAO organizations that humans and agents co-govern. There are many ways to play, as if getting rich overnight is not a dream.

But the trend comes and goes quickly. Once the bubble burst, many projects died one after another. However, there are still some infrastructure/practical AI projects taking over the market. The real value is beginning to emerge, and the next wave of Web3 AI is brewing , which may not just be hype this time – it deserves everyones serious attention.

We all know that once there is a new track or a new hot spot (such as Web2 AI, Trumps support for a combination of cryptocurrency and AI), the market does not care about the fundamentals at all. As long as it looks lively, has gimmicks, and has a beautiful demo, regardless of its actual usefulness, the market value can easily reach hundreds of millions of dollars.

@virtuals_io is the best storyteller in this wave. They have accurately hit the market, occupied the minds of users, and done a great job of narrative. So developers want to launch projects on it, and retail investors also follow the hype.

Later, @elizaOS appeared and took a completely different route – it open-sourced AI, allowing any developer to easily get started and mine gold by themselves . This concept immediately resonated widely, the community grew rapidly, and the number of stars and forks on GitHub rose like a rocket (and is still rising now).

The total valuation of the Virtuals ecosystem once reached over $5 billion, and Eliza was nearly half of that at its peak. Some other interesting AI agents, such as AIXBT, also once reached a market value of $1 billion.

Of course, the current situation is completely different. The market value of newly launched proxy projects with good performance is mostly between 3 million and 10 million; the market value of old projects has also been compressed to the range of 10 million to 50 million. The valuation ceiling of the entire sector has been compressed, and the total market value has dropped from the peak of 20 billion US dollars to the current range of 4 billion to 6 billion.

Bölüm 1 The rise of infrastructure and the acceleration of Web2 AI

The current market no longer believes in those cool-looking bubble projects, but begins to focus on real fundamentals. Especially in the context of the increasingly rapid development of Web2 AI models, everyone is more concerned about the long-term value of infrastructure and decentralized AI .

Metas Llama, OpenAIs GPT, Grok on X, DeepSeek, and Alibabas Qwen – they are updated almost every month, and the models are stronger, faster, and smarter. For example, the image generation function of ChatGPT was recently launched, and it immediately brought the Jixilifeng picture to the screen, which was directly screened.

The consumer product side of Web2 is also evolving rapidly. Because the underlying AI capabilities have become stronger, many product experiences that were not possible before can now be realized. New tools like Lovable, Bolt, Cursor, and Windsurf have improved developers development efficiency by several levels, and their functions are updated quickly and frequently. AI agents and intelligent workflows have now penetrated into every corner, and the entry threshold is getting lower and lower. For users, changing tools is almost free of cost – if a tool is not easy to use or expensive, you can immediately find a replacement with a better UI and a smoother experience. The entire market is becoming more and more competitive, but it has also accelerated the landing of truly valuable things .

Part.2 Data sovereignty awakening: Who is the real data owner?

As all this is developing rapidly, more and more people are beginning to realize a problem: there are all kinds of AI agent applications everywhere, but most of them use centralized technology – who owns my data? Where will my chat history go? If I talk to AI about something private, will it really be kept confidential? Or will it be uploaded, analyzed, and used to train other peoples models?

This question has become even more critical after @OpenAIs recent update – ChatGPTs memory function can now reference all your past conversations to generate more personalized responses. This feature is really cool. Imagine that in the future everyone has their own AI personal assistant, chat partner, emotional support… But this also means that your data will be long-term held by a certain platform, and you are no longer the owner of the data .

Once someone controls your conversations, preferences, emotions, and even lifestyle habits, the consequences may go beyond just “a better experience.”

This is why the topic of data sovereignty is becoming the next focus of AI + Web3. Data that truly belongs to users is the most valuable future .

Part.3 The rise of decentralized AI (DeAI)

I made several predictions last year, one of which was that decentralized AI would truly enter the public eye by the second quarter of 2025. Especially as people are increasingly concerned about privacy, security, and data ownership, the underlying infrastructure that can provide confidentiality, verifiability, and transparency of user data ownership will receive more attention and use.

We are currently seeing trends emerging in three main directions:

1. VC Trends in Web2 AI

▶ Some Y Combinator-backed startups are launching vertical AI agents (specialized in solving problems in a certain field);

▶ a16z began to lay out the next stage of consumer AI product trends and put forward its own investment logic;

▶ Perplexity has launched a fund dedicated to investing in AI.

2. VC Trends in Web3 AI

▶ Start betting on decentralized AI infrastructure;

▶ The fields of distributed training networks and computing power sharing are gradually heating up.

3. Retail investor trends in Web3 AI

▶ AI Agent ecology is still one of the hot topics;

▶ Consumer-grade AI applications are gradually becoming more diverse, ranging from productivity tools to emotional companionship;

▶ Users are increasingly concerned about whether the AI products they use are truly serving them, rather than harvesting their data. These trends are intertwined, pushing DeAI from a conceptual stage to a practical one. 2025 will be a critical moment to verify the value of decentralized AI.

Part.4 Web2 vs Web3 AI: Completely different rhythms and gameplay

On the Web2 side, the market size is much larger than that of Web3. This is because too many traditional companies are trying to use AI to transform and optimize their business processes – for example, to acquire more customers, improve conversion rates, increase sales, etc. These companies usually have very clear needs, and many of them are concentrated in a certain niche, so they hope to find AI tools that can accurately solve their specific pain points. This has also attracted many young entrepreneurs to target these niche needs and become vertical AI agents.

Compared with traditional SaaS, AI agents can bring more direct benefits – either saving a lot of money or directly attracting more customers to make money. Therefore, the subscription price of such AI tools can also be sold at a higher price. It is not without reason that many startups have achieved annual revenues of millions or tens of millions of US dollars within a few months of going online.

But Web3 plays a completely different game. The blockchain itself is a foundation layer tailor-made for decentralized AI (DeAI). All behaviors can be verified on the chain and cannot be tampered with; it naturally provides a trustless environment; it supports decentralized computing; and users can truly own their own data, models, and usage scenarios. In human terms, Web3 AI will allow users to know how their data is used, understand the decision-making process of AI, control models and use cases, and make money from it.

“Web3 VCs are already betting on this future”

Part.5 Why do retail investors love AI agents?

For Web3 retail investors, DeAI (decentralized AI) is indeed difficult to understand: a bunch of new words and concepts, which sound almost like alien language. So at the beginning, they are most likely to be attracted by those AI agents that are understandable, interesting and fun – such as talking chatbots, the kind that can tell jokes and make fun of others. This kind of entertainment AI agent is indeed very popular, but over time, retail investors have begun to find that these things seem to have no real use? In addition, the market conditions have been bad during this period, and a lot of useless projects have been slowly eliminated, while those useful agents that can provide functions have their valuations reduced, but they are still alive.

This wave of cleansing has made more and more people realize that only AI projects with practical use cases and core product capabilities have a future . Therefore, the project parties began to turn to two directions. Either develop real AI products to solve practical problems; or cooperate with truly technical and valuable DeAI projects, such as @AlloraNetwork, @opentensor (Bittensor)

This change has two positive meanings: it makes people start to pay attention to the underlying infrastructure that was originally incomprehensible; it makes AI agents no longer just performance tools, but products that can do real things. Projects like @AskBillyBets and @thedkingdao have become typical cases – not only are they powerful, but they also bring cool DeAI technologies like Bittensor to the public. This shows a trend: although retail investors do not understand technology, they will gradually be educated by really useful products.

I think the most interesting thing about the project Bittensor just mentioned is that it is a decentralized AI ecosystem that ordinary people can also participate in investing in. Most DeAI projects are still too early, and only VCs or strategic partners in the circle can invest, and there are many that have not even issued tokens. But Bittensor is different. Users can directly use $TAO to vote for the subnets you like, which is equivalent to swapping into the subtokens of these DeAI projects and getting on board in advance.

Although I have complained before: the cross-chain bridge and trading experience are a bit annoying…but their underlying technology, product logic, and overall atmosphere are really strong. Especially the existence of @rayon_labs, which makes the UX/UI design of the entire ecosystem more user-friendly. Because in the Bittensor mechanism, if each subnet wants to get more rewards (mining incentives), it must rely on market recognition – whoever is useful and powerful can get more distribution .

Therefore, for these subnets, it is extremely important to let users understand what you are doing . Rayon Labs is doing this. Their product direction is very clear: optimize UI/UX for ordinary users. They not only have multiple practical subnets (such as Gradients: a super convenient AutoML platform, users can directly train models on it and run them with the click of a button. And their latest flagship product is also very cool: Squad AI Agent platform: you can drag and drop modules like dragging tiles to create AI Agents, truly building AI agents with zero code . This experience is a bit like the Web3 version of the idiot AI factory, which is very suitable for users who dont understand technology to get started).

In general , the Bittensor ecosystem is not only one of the most technologically advanced DeAI projects, but also at the forefront in terms of user-friendly participation. This kind of team with clear product logic and user-friendly is the key role that makes this ecosystem popular.

We are in an era of great change led by Web3 AI. The bubble of the past that relied on hype to increase market value has been replaced by actual infrastructure, decentralized AI, and real application scenarios. Whether it is enterprises using AI to optimize their business in Web2 or retail investors experiencing the convenience of new agents in Web3, data sovereignty and user participation will be key in the future. Web3 AI is far from reaching its climax. The real drama has just begun.

*All content on the Coinspire platform is for reference only and does not constitute an offer or recommendation of any investment strategy. Any personal decision made based on the content of this article is the responsibility of the investor, and Coinspire is not responsible for any gains or losses arising therefrom. Investment is risky and decisions should be made with caution

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