The Way We Work Changes, but Expertise Remains

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The product development process I learned followed relatively clear roles and stages. A PM organized the requirements, a designer shaped the interface and user experience, and a developer turned them into a working product. Each discipline owned its area of expertise and completed its part of the cycle.

Advances in AI are rapidly breaking down those familiar boundaries. One person can now take part in shaping an idea, creating an interface, and writing the code. The time and effort required to move between disciplines have fallen dramatically.

I witnessed this transition firsthand at work. The change was happening faster than I expected, and it had already become part of how we worked.

A Different Kind of Team

A hackathon at my previous company led to the creation of a new AI team.

The existing organization had been divided by discipline into design, frontend, backend, and data. The new team, by contrast, was a small group of four: one designer, one frontend developer, and two members of the data chapter.

The way this team collaborated was different. The designer implemented UI changes and opened pull requests directly. The frontend developer reviewed the code and handled logic that required additional expertise, such as state management. The data specialists took responsibility for data, infrastructure, and server-side work.

The boundaries between their responsibilities were not fixed. All four proposed ideas, discussed priorities, and built the resulting product themselves. Each person performed their primary role while also sharing the responsibilities of a PM.

AI had not simply added another tool to the workflow. It was changing both the path from idea to product and the roles of the people involved.

My Initial Doubts

As people watched the shape of a website appear with just a few clicks, I occasionally heard comments like this at the company:

If it can be built this easily, what do developers actually do?

At first, that question filled me with doubt.

What had I spent all this time learning? If implementation required less time and effort, did that make a developer's expertise less valuable too? If the skills I had built were no longer recognized, what was I supposed to do next?

Without an answer, I became increasingly cynical as I watched the changes unfold. Over time, however, I began to look at the question differently. What mattered was not who wrote more of the code by hand.

Expertise Does Not Disappear

There is no doubt that AI has expanded the range of work one person can handle. Tasks that once required waiting for another discipline can now be attempted directly. Ideas can be validated faster, and collaboration across roles can become more flexible.

That does not mean domain expertise disappears.

Designers understand the user's context and judge what makes a better UI and UX. PMs define the problem worth solving and shape the direction of the product. Developers consider not only the feature in front of them but also the system's safety, scalability, maintainability, and efficiency.

AI can shorten the process of producing an output, but it does not decide what should be built. People must still determine whether the result is good enough, identify unexpected problems, and take responsibility for the outcome. Those judgments are grounded in the expertise each person has developed.

The fact that expertise remains does not mean we can stay fixed in our old ways of working. Preserving expertise is different from clinging to a familiar workflow. When the tools change, the way we apply our expertise must change as well.

Not Disappearing, but Changing

The world has always changed, and it will continue to do so. It is also true that the current shift feels unusually fast and unfamiliar.

When one part of the work becomes easier, however, it gives us more time and energy to focus on more important problems. Developers, for example, can spend less time on repetitive implementation and more time thinking about architecture, quality, and the value delivered to users.

What we need in the face of change is neither to dismiss the expertise we have built nor to hold on to the old way of working. We need to use that expertise as a foundation, learn the new tools, and redefine what we can do within our expanding roles.

The way we work is changing. Expertise is not disappearing; it is beginning to take a different form.