What Tai Chi Taught Me About Data-Driven Work

Recently in Tai Chi, my teacher told me something that has stayed with me. He said that we need to be relaxed where we need to be relaxed, and focused where we need to be focused. It sounds simple, but it is actually a very deep idea.

The common mistake is that people become tense in the wrong places. The shoulders are tight, the hands are stiff, and the body carries stress where it does not help at all. Because of that, the movement loses clarity and power.

The more I think about it, the more I realize this is exactly what happens in data-driven work in AEC.

We often put too much tension on the wrong things. We spend a lot of energy discussing the tools, the model, the pipeline, the dashboard, and all the technical details. Of course these things matter, but sometimes we become so focused on the technical side that we forget the most important question: why are we doing this in the first place?

What decision are we trying to improve? What feedback are we trying to create? What problem are we actually trying to solve?

This was also the main idea behind my talk at the Helsinki conference on AI in AEC. The bigger picture matters more than the technology itself.

Even though AEC deals with physical things like concrete, steel, and construction materials, the work itself is still knowledge work. Projects move forward based on how information moves, how quickly we learn, and how fast feedback comes back.

This is where I think AI becomes useful. Not because it is just another technology, but because it helps close the gap between technologies, people, and decisions.

Sometimes we focus too much on the system and not enough on the outcome.

Maybe the real challenge in data-driven work is knowing where to stay relaxed and where to stay focused.

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