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Learning velocity is one of the strongest signals at the early stage. It measures how quickly a team forms hypotheses, runs tests, learns, and updates decisions.
What fast learning usually looks like
- clear hypotheses (what you expect to be true)
- small experiments that test a single assumption
- documented outcomes and what changed as a result
- short cycles (days or weeks, not months)
What slow learning looks like
- long build cycles before user contact
- unclear assumptions or undefined success criteria
- no changes in direction despite new information