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AI as a side-project multiplier.

The interesting gain is not typing faster. It is shortening the distance between curiosity and evidence.

3 min read

Side projects usually die in the gap between a promising idea and the first version you can actually react to. AI is useful when it compresses that gap.

A tighter loop

Start with a narrow outcome, generate the boring scaffolding, and get something running. Once the artifact is real, judgment becomes much easier: keep this, cut that, rethink the premise.

Judgment is still the job

Fast output increases the need for taste, verification, and clear intent. A plausible implementation is not automatically a good one. The maker still owns the choices.

Use AI to buy more iterations, then spend those iterations deliberately.

Working practice

  • Define the smallest testable version.
  • Ask for structure before detail.
  • Run and inspect the actual result.
  • Keep a short log of decisions and surprises.