Why do I create this blog?

Preface

If you have already read the About Me section, you probably noticed that both my academic and professional background are quite unconventional and complex.

I am interested in many different things.

Professionally and academically, I spend time across areas such as Data Analytics, Quantitative Finance, Blockchain, Trading, Business Analysis, Product Management, Artificial Intelligence, Energy Systems, and even Physics & Mathematics.

Personally, I also enjoy French, Rock Music, Tennis, Snooker, and even topics like concrete road maintenance, urban infrastructure, and bridge construction — mostly influenced by my family background.

Let me tell you a small story.

Recently, someone I genuinely liked ended things with me because she thought I was:

“boring” and lacking any “interesting passions.”

After reflecting on that, I realized the issue was never the lack of interests.

It was actually the opposite.

I have too many interests, scattered across too many different domains.

Most of these thoughts only appear in specific moments of life, while reading, building projects, trading, walking on the street, or suddenly noticing how a city is designed.

But because everything is fragmented, I often fail to express them clearly in conversations.

Sometimes the thought disappears before I even get the chance to articulate it.

So instead of letting all those thoughts vanish, I decided to record them.

In many ways, I hope this blog eventually becomes:

a personal autobiography of my thinking process.

1. Recording Thought Processes, Not Just Results

Most projects eventually leave behind only a presentation deck, a model output, a strategy backtest, or a piece of code.

But what truly matters is usually the process behind them.

Why did I choose this direction? What mistakes did I make? Which assumptions later turned out to be wrong? How was an idea gradually formed? Why did certain strategies fail?

I want this blog to document those processes.

Not just polished conclusions or successful outcomes, but also failed experiments, incorrect decisions, overfitted models, abandoned product ideas, and moments of self-doubt.

Because those are usually where real learning happens.

2. Building My Own Knowledge System

Modern information is extremely fragmented, especially under the circumstance of fast AI development.

One day I might study AI agents. The next day I may work on on-chain analytics. Then suddenly spend hours researching market microstructure or energy trading systems.

Without output, people can easily fall into a state of:

“Knowing many things, but having no system.”

Writing forces me to organize ideas, simplify complexity, connect unrelated fields, and truly understand what I learn.

I hope this blog gradually becomes a personal knowledge system around AI, Quantitative Finance, Blockchain, Data Analytics, Product Thinking, and Markets & Systems.

At the same time, this process also improves my storytelling ability.

Because:

Having knowledge is one thing.
Being able to explain your thinking clearly is another.

This is exactly what I learned from Business Analytics.

3. Sharing Real Practice Instead of “Packaged Success”

The internet already has enough content about perfect success stories, unrealistic returns, revolutionary AI claims, and heavily polished personal branding.

But reality is rarely that clean.

Real research and real product development are usually filled with uncertainty, failed ideas, messy datasets, changing assumptions, and constant iteration.

I would rather share how a trading signal is actually tested, how an AI product idea gradually fails, how research evolves over time, and how people make decisions under uncertainty.

I think those experiences are far more valuable than simply displaying polished outcomes.

4. Creating Long-Term Value

This blog is also a long-term asset.

Over time, this space will quietly document how I learn, research, build, think, and gradually evolve across different fields.

Years later, I believe looking back at these records will be incredibly meaningful.

I also hope this blog eventually helps me meet people working in AI, Quant, Crypto, and Product, exchange ideas, collaborate on projects, and build meaningful long-term connections.

5. Preserving Independent Thinking in the AI Era

Content generation is becoming easier every day.

But genuine perspectives are becoming rarer.

I do not want to become someone who simply reposts information or repeats whatever is currently popular online.

Instead, I want to continuously train myself to think independently, build logical frameworks, question assumptions, and form my own judgment.

In many ways, this blog itself is a long-term exercise in thinking.

Final Thoughts

This blog is not meant to:

“Show what I know.”

It is meant to document how I think, how I learn, how I build, how I fail, and how I continuously evolve over time.

That matters much more to me.