We are building products faster than ever before. Yet they have never been more interchangeable.

Do not get me wrong: I am not against AI. I use these tools daily, I build my own workflows with them, and they massively accelerate my work. That is exactly why I am noticing a trend that is currently taking over many product teams. The classic iterative design process is being sacrificed for the sake of pure speed.

Design happens straight in code, finished screens are generated through AI tools, and the detour through Figma or any other design tool disappears. On paper this sounds like a dream for time to market. But there is a price, and most teams only notice it much later.

One thing up front, so my point is not misread: I am not arguing against code as a medium. Design in code is a legitimate and growing discipline. I am arguing against throwing out iteration and the shared foundation that good design needs, no matter which tool you use.

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The three major losses of blind velocity

When you cut iteration, you cut one of the key levers for real business success. Rushing ahead blindly creates three serious problems.

1. Thinking before building disappears. When you start directly in code, you automatically think only in building blocks that already exist. You stop asking what the best solution for the user would be, and start asking what can be clicked together fastest.
2. The Sea of Sameness. AI tools tend to default to the most common, statistically safe patterns, because that is the average of everything they have been trained on. Ready made libraries make it worse: when a core product leans entirely on them, everything ends up looking identical. The same rounded corners, the same gradients, the same blue. And yes, these libraries can be themed and customized. But without a shared layer for exploration and craft, the sameness creeps back in, in any tool, Figma included.
3. The team loses its foundation. Without a shared visual source of truth, there is no place left for exploration, for critique, for capturing design decisions and the reasoning behind them. New colleagues have no way in. The design intent ends up scattered across the code, and nobody remembers why things are the way they are. That is design debt by design.

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Design is not just making things pretty. It is a business factor.

This is where the data comes in, and it is worth being precise, because design here means design maturity, not surface polish.

McKinsey, The Business Value of Design (2018): across more than 300 companies, the top design performers achieved 32 percent higher revenue growth than their industry peers over five years. One of the four factors driving that edge was continuous testing and iteration with real users. This is a correlation, not a guarantee, but a strong and consistent one.

DMI Design Value Index: over a ten year period, a portfolio of design led companies outperformed the S&P 500 by more than 200 percent.

Both studies predate the current AI wave, so they prove nothing about AI directly. What they make a strong case for is the value of iteration and differentiation, the very things that get cut first when speed becomes the only metric.

Especially in fintech and payments, where I am at home, differentiation is not a luxury. It is survival. Trust and recognition are built through tailored details, not off the shelf components.

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Bottom line: speed is not a product

The problem is not AI. The problem is removing the strategic thinking layer and confusing speed with progress. The strongest teams I know use these tools to reach better decisions faster, and they keep iteration and craft as the foundation. Speed and quality are not mutually exclusive. But speed on its own is not a product.

Right now an entire generation of products is being built in record time, and they all feel the same. The question is whether we will still think that is a good thing two years from now.

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