AI Is Redefining What It Means to Be a Developer

Since joining Hypercape as CTO, the biggest thing I’ve realized is this:

AI is no longer just a tool for improving development productivity. It is changing the very definition of what it means to be a developer.

My reason for joining Hypercape was clear.

A fully validated dropshipping model—one that tightly integrates logistics, marketing, and sales channels—was already working exceptionally well in the K-beauty space. I was convinced that this domain could expand into many other industries, and I wanted to be at the center of leading that expansion through technology.

When I actually joined, the business was already running well.

But to scale it further, I believed that rebuilding the development organization was absolutely necessary.

At the time, the system was operating on a legacy Spring-based architecture, and for a certain era, that had been a perfectly rational choice. But in a world where the market is changing rapidly because of AI, there were clear limits to how quickly we could respond with that structure alone.

A lot of work was still being handled through Excel, and information sharing between teams was very limited. That led to unnecessary communication costs and frequent mistakes.

For the past nine years, I had already been running a development company and adopting AI into development faster than most people. And when GPT-3.5 was released, I became almost certain of one thing:

Developers can no longer remain people who simply memorize syntax or spend their time naming functions and variables.
At their core, developers now have to become planners.

And today, I believe that prediction is becoming reality.

These days, I rarely write code myself.

Most implementation is carried out by AI through natural language, while I focus more on designing architecture and shaping business models.

Planning, implementation, validation, and QA—AI is now deeply involved in almost every stage of the process. More recently, development teams using Openclaw have reached a point where they can autonomously create internal tools on their own.

The changes I’ve felt from integrating AI deeply into real work are very clear.

First, the need to memorize unnecessary things has disappeared.
We no longer have to spend as much energy on memorizing syntax or dealing with minor implementation details. Instead, we can focus more on solving fundamental problems.

Second, developers are becoming closer to *“planners who can build” *or even *“marketers who can build.” *
Personally, I now spend far more time on problem definition, strategy, and customer understanding than on technology itself.

Third, the speed of forming and testing hypotheses has become overwhelming.
Experiments that used to take weeks or months can now be created, tested, and discarded in much shorter cycles. The lifecycle of products itself has become shorter, which means faster judgment and higher-resolution problem definition matter more than ever.

Of course, there are still areas AI cannot fully replace.

In particular, questions like what people truly want, what strategy will actually work, and how to interpret irrational and imperfect human choices still belong to humans.

I believe that the core human role will increasingly move toward
intuition, direction, interpretation, and responsibility.

There are also capabilities that become even more important in the age of AI.

Many people think that once AI advances, computer science knowledge and engineering conventions will become meaningless. I see it the other way around.

That knowledge still matters. But rather than viewing it as something to memorize, we should understand it as a language for communicating human logic to computers more precisely.

And on top of that, what becomes even more important is the ability to define problems, deeply understand multiple domains, and understand people.

The developer market will also change significantly.

Even in the past, simply being good at coding was never enough to be recognized as a senior developer.

But going forward, I think that boundary will become even clearer.

The senior developers of the future will not just be people who are good with a particular tech stack.
They will be the ones who can understand multiple domains, interpret business, design structure, and push execution forward together with AI.

Hiring standards are already changing as well.

Even at Hypercape, we no longer prioritize* “experienced developers who are good at coding” *above all else. Instead, we value people who can define problems well, have a strong will to solve them, and have built a broader way of thinking through diverse experiences beyond development itself.

More than a prestigious school or degree, what matters to us is that person’s intellectual honesty, attitude, persistence, and real problem-solving ability.

To put it more bluntly,
the developers who survive will not simply be coders.
They will be engineers who can design business models as well.

And this may not be a story about developers alone.

Routine office roles that do not think for themselves, and roles that cannot define problems independently, are likely to disappear faster and faster.

In the age of AI, what matters is not just
“What can you build?”
but rather
“Can you define what should be built, and why?”

I am working in the middle of that change right now.

And I believe that the developers of the future will increasingly be technologists and planners at the same time,
engineers and business designers at the same time.