In the past couple of days, I experienced Flowith's newly launched AI Agent "Flowith Neo" and was pleasantly surprised by how engaging it is.

Currently, it is indeed not a very mature product, but it is certainly an assistant that can help me with a lot of tasks, giving me a more tangible experience of what an AI Agent can do. I won’t elaborate on the detailed features here; interested friends can look it up themselves.

This experience has made me seriously ponder a question: Web3 asset management, especially in the realm of stable financial management, might actually be the most suitable application of "Web3 + AI".

To be honest, I have always held a reserved or even negative attitude towards projects like "Web3 + AI" in the past.

There are too many projects in the industry that use this concept to tell a story, only to end up with a UI wrapped around GPT, claiming to be an Agent with a large model and a few prompts. Our technical colleagues commented on several product prototypes—"It could be done in an afternoon".

Especially in scenarios like trading cryptocurrencies or chasing memes, I believe Agents have little opportunity.

What do you rely on when you want to chase memes or trade short-term? It’s speed, emotion, information, and intuition; often you aren’t even sure why you buy or sell. The current large models have inherent data input delays, and the context window is limited.

On-chain events are real-time, but the model's understanding of the world is often a snapshot from hours, days, or even weeks ago. Do you expect it to help you bottom out or top out under such conditions? It’s better to just operate with your eyes closed.

If someone could truly create such an intelligent trading entity, they would have started their own fund long ago; who would still open it up for you to use?

But Web3 asset management and stable financial management are completely different. It’s not about speed, accuracy, or intuition; it’s about "who can consistently and stably execute strategies".

Many Web3 financial actions seem not too complicated, such as:

- Monthly dollar-cost averaging

- Rotating yield pools across multiple protocols

- Automatically interacting with airdrops

- Staking and re-staking

- Running LRT strategies, tracking L2 incentives...

But getting a person to consistently carry out these actions over the long term is actually very difficult. It’s not about being incapable; it’s about how tedious, taxing, and mechanical it is.

At the end of the day, people are prone to laziness, forgetfulness, and emotional influences.

But an Agent won’t be.

Of course, for an Agent to take over asset management, a few basic issues must be resolved:

Technical security, permission boundaries, data readability, strategy transparency, and privacy protection.

These are indeed not perfect at present, but if we make an assumption: in the future, they can be resolved.

Then the next logic becomes clear: AI Agents doing Web3 asset management is reasonable and technically feasible.

You set the rules, for example:

- Convert 20% of USDC to BTC every month

- Allocate the remaining USDC among three high-quality protocols, weighted by yield/risk ratio

- Automatically rebalance every quarter

- Reinvest profits

- Automatically interact with airdrops, withdraw, and account for them

You can certainly complete these actions manually, but it’s impossible to execute them meticulously every week or month. You’ll get bored, forget, or simply have no time.

But the Agent doesn’t have this problem. It doesn’t need emotional stability; it is inherently stable.

More importantly, the structure of Web3 is extremely friendly to Agents.

Unlike the financial world of Web2, where funds are scattered across different platforms with closed information, and an Agent would need to negotiate authorization with companies to access an account.

An Agent can write strategies according to your needs, control permissions, and execute tasks, helping you with asset management across chains and protocols.

This is impossible in Web2; at least you can’t expect an Agent to operate your funds in Alipay, Yu’ebao, Xueqiu, and Licai Tong.

But in Web3, it is fundamentally a unified structure of a programmable financial space.

As I write this, I suddenly feel that the product form most likely to carry this capability in the future may not be a plugin or a bot, but rather a new type of browser.

A dedicated AI browser for Web3.

- You log into your wallet inside, connect the Agent, and configure your goals, strategies, and permission boundaries.

- It can understand the pages you open, recognize the protocols and asset structures on the pages, and provide executable suggestions;

- It can comprehend the commands you input: "Help me reconfigure my stablecoin position" or "Check if there are any new airdrops to claim";

- It can even run tasks in the background over the long term, such as automatically adjusting asset allocation, executing profit reinvestments, or organizing a weekly asset performance report.

- This browser won’t just be an information window; it will be a true control hub for assets.

You can even configure multiple Agents:

One running stable investment strategies, one dedicated to airdrop tasks, one focused on optimizing gas and cross-chain operations, and another responsible for regularly generating asset performance reports.

It may sound distant, but if you really break down the financial processes on the blockchain today, most can actually be modularized.

What’s missing is a scheduling system, a logic entity that can link them together and execute them over the long term.

So, AI Agents are not a futuristic fantasy.

They are a reality that can be assembled.

Not because they are so "intelligent" but because they can make your assets "continuously" move.

Not to help you earn the most, but to help you make fewer mistakes, waste less, and feel less anxious.

For most Web3 users, that is already enough.