Viewpoint: Why I Gradually Gave Up Researching Web3 Projects?

Author: Liu Ye Jing Hong

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Introduction

Recently, I have mostly shifted my focus to the AI field, and the output related to Web3 has also decreased. However, after more than a year of reflection, I have accumulated many new insights and experiences about this industry that are worth sharing with everyone.

My earlier readers may remember that my writing career began with research analysis on projects and tracks. But I don't know when it started, I rarely write such articles anymore. Behind this is both my personal vision enhancement - allowing me to glimpse the higher-level and more fundamental operational logic of the Web3 world; as well as a series of changes in personal resources and wealth concepts.

During this period, I have been repeatedly asked by friends: “How is a certain project?” “Is that track still worth investing in?” I often find myself at a loss for words, because in the current environment, it is difficult to have definitive answers to these questions.

After a period of reflection and organization, I would like to systematically discuss why my investment research and analysis on specific projects has gradually shifted from enthusiasm to abandonment.

Core One: The Reversal of Information Barriers - When AI Becomes a Tool for Creating Mists

It is undeniable that a core profit model in the Web3 industry originates from information asymmetry. For “investment research,” whoever can discover the potential value of a project earlier and position themselves in advance can obtain excess returns. However, it is precisely this reason that led me to ultimately give up this path.

Looking back at 2018 and 2019, I was still doing project ratings. Thanks to my background in computer science, many blockchain concepts that seem obscure to outsiders are quite familiar to me. This allows me to relatively easily distinguish which projects are hollow and which ones truly possess technical value.

However, by the time we reach 2025 (note: this refers to the current and near-future industry environment), this methodology has almost become ineffective. It is not that the blockchain technology itself has developed beyond my understanding, but rather that project teams have become incredibly adept at using the latest AI large models to “package” themselves. Poor-quality projects, which could be easily seen through in the past, can now, with the aid of AI, create seamless narratives, technical white papers, and even GitHub code repositories that appear impressive and credible.

I might as well be honest: over the past two years, I have helped some exchanges and project teams write quite a few promotional texts that appear “technically professional” to the outside world, while their actual authors are, in fact, AI. Even those seemingly active project interaction data and on-chain transaction records are often generated in bulk through scripts written by AI.

This means that in the era of AI proliferation, the costs of traditional investment research are increasing exponentially. To verify the authenticity of a project, the effort and time required far exceed what was needed in the past. Public information channels have been severely polluted by “noise” generated by AI, and it feels like we are watching a “magic showdown” between AIs, while real and effective information is buried beneath layers. I personally have also tried to use AI to analyze Web3 projects, but progress has been minimal, and I feel trapped in a deadlock of mutual verification of AI-generated content.

Core II: Decoupling of Value - The Illusory Separation of Project Quality and Token Price

For many who have not yet deeply engaged in Web3 investment research, this seems to be a path of high returns. Indeed, in the first two cycles, I earned substantial profits through investment research. But that was in a relatively “pure” era of the industry—good projects really would rise.

As of today, Web3 has developed into a highly mature and well-defined industry chain. From project preparation, fundraising, issuance, promotion to market value management, each link has professional institutions or incubators operating behind the scenes. Even many KOLs you see have the support of exchanges behind them.

As an independent researcher who is “outside the loop,” the possibility of conducting research and profiting solely based on publicly available information has become extremely slim.

The deeper issue is that in the vast majority of Web3 projects, the technical team and the operation team are separate. In other words, there may indeed be a group of tech geeks dedicated to building excellent technology, but the price trend of the tokens is not determined by them. During the project's fundraising phase, the market-making rights of the tokens are often handed over to professional operation teams.

Therefore, when a project releases significant good news, such as a technological breakthrough, it may actually be an excellent time for the trading team to distribute their chips. This also explains the common phenomenon: why does the price drop instead when the technology has made a breakthrough?

Ultimately, the industry has evolved into its current state: the quality of the project itself and the performance of its token price are completely unrelated matters. This is also the fundamental reason why I find myself in a dilemma when facing questions from friends like “Is the project good? Can the token be bought?”.

Core Three: The Disappearance of Fundamentals - An Era Where Traffic and Sentiment Reign Supreme

This might be the most heart-wrenching point: in today's world where meme culture is rampant, the quality of the project itself has become unimportant. The project parties don't care, and most participants don't care either. Traffic and sentiment have instead become the only indicators of a project's success.

I am also keeping an eye on some projects, such as the highly anticipated Monad ecosystem that is about to airdrop, but its overall popularity and community engagement may be far less than that of a suddenly trending Meme project.

This precisely reveals a cruel characteristic of Web3 at present: “I came to Web3 to make money; my goal is profit, not to build a quality project.” When the consensus of the entire market is based on this, in-depth research on the fundamentals of projects becomes trivial, and even somewhat “out of place.”

On the other hand, as I come into contact with higher levels of the industry, I gradually realize that the quality of the project itself is not a key issue when many project parties negotiate with investors or operating institutions. As long as they choose a track that sounds good and has a lot of hype, and weave the narrative with AI to make it compelling enough, the rest is all about the games of human relationships and chip distribution. As for the development progress of the project, that is merely a time node they use to decide when to distribute the chips.

Conclusion: The True Value of Investment Research

In writing this article, my intention is not to completely deny the value of “investment research.” On the contrary, investment research itself plays an invaluable role in broadening personal horizons, enhancing cognitive depth, and building knowledge systems. It has at least allowed me to grow from a naive “retail investor” into a participant who can avoid the vast majority of traps.

However, if your sole purpose is to make short-term profits, then I believe that in the current era, relying solely on public information for investment research to make money has become an extremely narrow path.

Nowadays, the publicly available investment research content has increasingly evolved into a kind of “traffic diversion tool.” For example, I once spent a month operating an investment research account, and the articles easily reached a readership of tens of thousands. However, the endpoint of this path is often to divert traffic to third-party paid communities, which then guide you to purchase certain tokens through various means, with the ultimate profit point still resting on “selling tokens.” I believe this model is not honorable and did not yield any profit, so I eventually gave up.

The investment research experience over the years has allowed me to understand Buffett's famous saying like never before:

" Never invest in a business you cannot understand. "

“Never invest in a company you don't understand.”

In the past, I thought that “understanding” meant comprehending the technology and models. But now I realize that in Web3, “understanding” must also include understanding the underlying capital structure, the game of interests, and human nature. And these are precisely what public information can never tell you.