Why has research on Web3 projects become increasingly meaningless?

Author: Liu Ye Jing Hong

Introduction

Recently, most of my energy has shifted towards 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.

Readers who have followed me for a while may remember that my writing career began with project and track investment research and analysis. However, I don't know when it started, but I have rarely written such articles since then. Behind this are 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 continually 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 some time of thinking and sorting things out, I would like to systematically discuss why my investment research and analysis of specific projects has gradually shifted from enthusiasm to giving up.

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

It is undeniable that a core profit model in the Web3 industry stems from information asymmetry. In terms of “investment research,” whoever can discover the potential value of a project earlier and position themselves in advance can reap excess returns. However, it is precisely for this reason that I ultimately gave up this path.

Looking back to 2018 and 2019, I was still doing project ratings. Thanks to my computer science background, 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 projects truly have technical substance.

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 development of blockchain technology has exceeded my understanding, but rather that project teams have become incredibly adept at using the latest AI large models to “package” themselves. Projects that could easily be seen through in the past can now, with the support of AI, create seamless narratives, technical white papers, and even GitHub code repositories that appear authentic and well-crafted.

I might as well be honest: over the past two years, I have helped some exchanges and project teams write a lot of promotional materials that appear to be “technically professional” to the outside world, but their real authors are actually AI. In fact, much of the seemingly active project interaction data and on-chain transaction records were also generated in bulk through scripts written by AI.

This means that in the era of AI proliferation, the cost of traditional investment research is increasing exponentially. To discern the authenticity of a project, the effort and time you need to invest far exceed the past. Public information channels have been severely polluted by AI-generated “noise,” and it feels like we are watching a “magic showdown” between AIs, while real and effective information is buried layer upon layer. 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 Two: Decoupling of Value - The Discrepancy Between Project Quality and Token Price

For many who have yet to deeply engage in Web3 investment research, this seems like a high-return path. Indeed, during the first two cycles, I earned considerable profits through investment research. But that was a relatively “pure” era for the industry—good projects really did appreciate.

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 “on the outside,” the possibility of conducting research and profiting from publicly available information has become extremely slim.

The deeper issue lies in the fact that in the vast majority of Web3 projects, the technical team is separated from the trading team. In other words, there may indeed be a group of tech geeks diligently building excellent technology, but the price movement of the tokens is not determined by them. During the fundraising phase of the project, the market-making rights of the tokens are often handed over to professional trading teams.

Therefore, when a project announces significant positive news, such as a technological breakthrough, it may actually be an excellent opportunity for the operation team to distribute their assets. This also explains the common phenomenon: why does the price drop sharply when a technological breakthrough occurs?

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

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

This point may be the most heartbreaking: in today's era of rampant meme culture, the quality of the project itself has become unimportant. The project parties don't care, and most participants don't care either. Traffic and emotions have instead become the only metrics for measuring whether a project is successful.

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 come to Web3 to make money, my goal is profit, not to build a quality project.” When the entire market's consensus is based on this, in-depth research on project fundamentals becomes insignificant, and even somewhat “out of place.”

On the other hand, as I engage with higher levels of the industry, I gradually realize that the quality of the project itself is not the key issue when many project parties negotiate with investors or trading institutions. As long as they choose a track that sounds good and has heat, and weave a narrative that is compelling enough with AI, the rest is merely a game of human relationships and chip distribution. As for the project's development progress, that is merely a time point they use to decide when to distribute 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 has an immeasurable and significant role in broadening personal perspectives, enhancing cognitive depth, and building a knowledge system. It has at least allowed me to grow from a naive “retail investor” into a participant who can avoid the majority of traps.

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

Nowadays, the publicly available investment research content has increasingly evolved into a “traffic diversion tool.” For example, I once spent a month operating an investment research account, and the articles easily achieved readerships 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 in various ways, with the ultimate profit point still resting on “selling coins.” Because I believe this model is not honorable and has not yielded profits for me, I later gave it up.

My years of investment research experience have given me an unprecedented understanding of Buffett's famous saying:

" 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 the models. Now I realize that in Web3, “understanding” must also include grasping the underlying capital structure, the games of interest, and human nature. And these are precisely the things that public information can never tell you.