Why am I gradually giving up on Web3 project research and investment?

Introduction

Recently, most of my energy has shifted towards the AI field, and my output related to Web3 has correspondingly 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 research and analysis of projects and sectors. But at some point, I rarely wrote such articles anymore. Behind this, there is both the broadening of my personal perspective—which allowed me to glimpse the higher-level and more fundamental operating logic of the Web3 world—and a series of changes in my personal resources and views on wealth.

During this period, friends have constantly asked me: "What do you think about a certain project?" "Is that sector still worth investing in?" I often find myself at a loss for words, because in the current environment, these questions are already very difficult to answer definitively.

After some time of thinking and sorting out my thoughts, I want to systematically discuss why my enthusiasm for project-specific research and analysis has gradually faded and why I eventually gave it up.

Core Point 1: The Reversal of Information Barriers—When AI Becomes a Tool for Creating Fog

It is undeniable that one of the core profit models in the Web3 industry comes from information asymmetry. For "research and investment," whoever can discover a project's potential value earlier and position themselves ahead of time can reap excess returns. However, this is also the reason why I eventually abandoned this path.

Thinking back to 2018 and 2019, I was still doing project ratings. Thanks to my computer science background, many blockchain concepts that seemed obscure to outsiders were second nature to me. This made it relatively easy for me to distinguish between hollow projects and those with real technical substance.

However, by the time we reach 2025 (note: referring to the current and near-future industry environment), this methodology has almost become obsolete. It's not that blockchain technology itself has developed beyond my understanding, but rather that project teams have become extremely adept at using the latest AI large models to "package" themselves. Projects that were once easy to see through as shoddy can now, with the help of AI, create narratives, technical whitepapers, and even GitHub codebases that are seamless and convincing.

Let me be candid: in the past two years, I have helped some exchanges and project teams write quite a few "technically professional" promotional articles in the eyes of the public, but their real author was actually AI. Even those seemingly active project interaction data and on-chain transaction records are often batch-generated by scripts written by AI.

This means that in the era of widespread AI, the cost of traditional research and investment is increasing exponentially. To discern the authenticity of a project, you need to invest far more energy and time than before. Public information channels have been severely polluted by AI-generated "noise." It's as if we are watching a "magic duel" between AIs, while real and effective information is buried under layers of obfuscation. I have also tried using AI to analyze Web3 projects myself, but made little progress, feeling trapped in a dead loop of AI-generated content verifying each other.

Core Point 2: The Decoupling of Value—The Superficial Relationship Between Project Quality and Token Price

For many who have not deeply engaged in Web3 research and investment, this seems like a high-return path. Indeed, in the previous two cycles, I made considerable profits through research and investment. But that was an era when the industry was relatively "simple"—good projects really did go up.

Today, Web3 has developed into a highly mature industry chain with clear divisions of labor. From project preparation, fundraising, issuance, promotion, to market cap management, every step is operated by professional institutions or incubators behind the scenes. Even many KOLs you see are supported by exchanges behind the scenes.

As an independent researcher "outside the circle," the possibility of profiting solely from public information research has become extremely slim.

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

Therefore, when a project announces major positive news, such as a technological breakthrough, for the market-making team, this may actually be the perfect opportunity to distribute their chips. This explains the phenomenon we see time and again:Why does the price plummet after a technological breakthrough?

In the end, the industry has evolved to its current state:The quality of the project itself and the performance of its token price are completely unrelated. This is the fundamental reason why I find it impossible to answer friends' questions like "Is the project good? Is the token worth buying?"

Core Point 3: The Disappearance of Fundamentals—An Era Where Traffic and Sentiment Reign Supreme

This may be the most painful point: in today's Meme culture frenzy,the quality of the project itself no longer matters. Project teams 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 myself am also following some projects, such as the highly anticipated Monad ecosystem, which is about to airdrop, but its overall popularity and community engagement may be far less than some suddenly viral Meme project.

This precisely reveals a cruel characteristic of Web3 today:"I came to Web3 to make money. My goal is profit, not to build a quality project." When the entire market consensus is built on this, in-depth research on project fundamentals becomes insignificant, even somewhat "out of place."

On the other hand, as I have reached higher levels in the industry, I have gradually realized that for many project teams, when negotiating with investors or market-making institutions, the quality of the project itself is not the key topic. As long as you choose a sector that sounds good and is popular, use AI to weave a compelling narrative, the rest is all about social maneuvering and chip distribution games. As for the project's development progress, that's just a timing node they use to decide when to distribute their chips.

Conclusion: The True Value of Research and Investment

In writing this article, my purpose is not to completely deny the value of "research and investment." On the contrary, research and investment itself has immeasurable value in broadening personal horizons, deepening cognitive depth, and building a knowledge system. At the very least, it allowed me to grow from a naive "newbie" into a participant who can avoid most traps.

However, if youronly goal is short-term profit, then I believe that in this era, relying solely on public information research to make money has become an extremely narrow path.

Nowadays, public research and investment content has evolved more into a "traffic generation tool." For example, I once spent a month running a research account, and the articles easily reached ten or twenty thousand reads. But the end of this path is often to funnel traffic to third-party paid communities, which then guide you to buy certain tokens in various ways, with the ultimate profit point still falling on "selling tokens." Because I believe this model is not honorable and I did not profit from it, I eventually gave it up.

These years of research and investment experience have given me an unprecedentedly deep understanding of Buffett's famous saying:

"Never invest in a business you cannot understand."

In the past, I thought "understand" meant understanding the technology and the model. But now I realize that in Web3, "understand" 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.