Design-First Collaboration

When I pair program with a colleague on something complex, we don’t start
at the keyboard. We go to the whiteboard. We sketch components, debate data
flow, argue about boundaries. We align on what the system needs to do before
discussing how to build it. Only after this alignment — sometimes quick,
sometimes extended — do we sit down and write code. The whiteboarding is not
overhead. It is where the real thinking happens, and it is what makes the
subsequent code right. The principle is simple: whiteboard before
keyboard.

With AI coding assistants, this principle vanishes entirely. The speed is
seductive: describe a feature, receive hundreds of lines of implementation
in seconds. The AI may understand the requirement perfectly well — an email
notification service with retry logic, say. But understanding what to
build and collaborating on how to build it are two different activities,
and AI collapses them into one. It does not pause to discuss which
components to create, whether to use existing infrastructure or introduce
new abstractions, what the interfaces should look like. It jumps from
requirement to implementation, making every technical design decision
silently along the way.

The solution, I believe, is to reconstruct the whiteboarding conversation
that human pairs do naturally — making the AI’s implicit design thinking
explicit and collaborative. Rather than asking for implementation directly, I
walk through progressive levels of design. Each level surfaces a category of
decisions that would otherwise be buried in generated code.

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