Choosing Breadth of Knowledge in the Age of AI

Author

xc2f

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Choosing Breadth of Knowledge in the Age of AI

When I first entered the industry, I was a typical “technology-first” person.

At that time, I believed one thing:

Only by pushing technology to its limits could I go further.

So I made many plans for myself:

  • Learn React, Vue, and Angular all together

  • Gain a deep understanding of TypeScript

  • Learn Rust

  • Explore new runtimes like Bun

Ten years later, looking back at these plans, the reality is somewhat different:

  • I’ve become more and more proficient with React

  • Vue and Angular were never systematically learned

  • My understanding of TypeScript is still partial

  • I haven't started looking into Bun yet

  • I’ve tried to learn Rust twice, and I’m not sure whether the third time will succeed

Recently, I’ve also developed an interest in graphics and color.

I’ve completed about one quarter of the Three.js Journey course, but I’m not sure when I’ll continue.

The world of technology is always accelerating.

New frameworks, languages, and tools appear constantly, like mushrooms after the rain.

But human time and energy are always limited.

Energy Is a Scarce Resource

For most people, life is not only about technology.

There are also:

  • Work itself

  • Personal interests

  • Family life

  • Physical health

When all these things come together, one fact becomes unavoidable:

Our energy is limited.

Some technical knowledge:

  • Has an actual usage rate of only 20%

  • Sometimes even just 2%

But mastering it completely might consume 80% of our time.

In these situations, I began to make a choice:

For things that are rarely used but extremely costly to master, I choose to set them aside.

From “Extreme Depth” to “Reasonable Breadth”

In the past, I pursued depth in technology.

Now, I lean more toward:

Expanding the breadth of my knowledge as much as possible.

Not everything needs to be mastered, but at least I want to:

  • Know what it is

  • Understand roughly what problems it solves

  • Know when it might be useful

When I actually encounter a problem, I can then dive deeper into the relevant area.

This approach often allows me to quickly judge:

“Which direction the solution should probably take.”

In the AI Era, the Skill Structure Is Changing

As AI becomes increasingly widespread, the cost of obtaining technical details is rapidly decreasing.

In the past, solving problems might require:

  • Reading a lot of documentation

  • Studying a lot of source code

  • Repeated trial and error

Now, many times it only requires:

  • Asking the right questions

  • Letting AI help fill in the technical details

Because of this, two abilities are becoming more and more important.

1. The Ability to Ask Questions

How clearly you can describe a problem often determines whether AI can provide a valuable answer.

2. The Ability to Combine

The ability to combine different technologies, tools, and ideas to solve real-world problems.

In such an environment, the value of knowledge breadth actually becomes higher.

Because breadth helps us:

  • Identify the direction of a problem

  • Choose the right tools

  • Quickly organize possible solutions

Meanwhile, AI can help us fill in the details.

A Personal Conclusion

If the traditional path of technical growth used to be:

Depth first

Then in the AI era, a more reasonable structure might be:

Maintain depth in one core field while continuously expanding your breadth of knowledge.

Breadth helps us determine direction.

Depth determines how far we can ultimately go.

And within limited time, learning how to make trade-offs is itself a valuable skill.