Metrics question

How would you measure whether the Hub is the default starting point for AI builders?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Metrics thinking around brand and habit dominance rather than simple usage counts.

Clarify what default starting point means: the first place a builder goes when starting a new AI project, before considering alternatives.
Propose a direct signal: percentage of new model or dataset searches that originate from direct navigation or bookmarks rather than a general web search, showing habitual use.
Propose an indirect signal: share of voice in developer surveys or GitHub README references pointing to the Hub as the source for a model.
Propose a competitive signal: percentage of new open-source model releases that publish first or exclusively on the Hub versus alternatives.
Acknowledge limits: some signals like survey share of voice require external data collection, not just internal analytics.

Separates habitual-use signals, like direct navigation, from popularity signals, like raw traffic, since the former better proves default status.
Proposes tracking where new major model releases choose to publish first, a strong external signal of the Hub's default status among model creators specifically.
Names a guardrail against a misleading number, like total traffic, which can rise from one-off searches without reflecting habitual default use.
Suggests combining internal analytics with an external developer survey since internal data alone cannot capture mindshare outside the platform.

Relying only on total traffic or downloads as a proxy for being the default choice.
Ignoring the creator side of the ecosystem, meaning where new models get published first, not just where they get consumed.

How would you measure this if a competitor started attracting major model releases?
Which single metric would you prioritize if you could only track one?