Broadband maps are public. The useful answer still is not.

This issue launches Neighborhood Broadband Reality Explorer, a Seattle-region proof that compares broadband options in the shape a real decision needs: best available, upload-heavy work, price sensitivity, and backup resilience.

The key constraint is intentional. The prototype stays area-level instead of pretending exact-address certainty. That keeps the workflow honest while still making the capability obvious.

Broadband data is a good example of a larger public-data pattern. The hard part is usually not getting access to a map or CSV. The hard part is turning official fields into a product that helps a normal person decide what to do next.

That is why this proof matters beyond internet shopping. It shows how AI can take public infrastructure data and shape it into a decision surface with clear tradeoffs and clear truthfulness boundaries.

Start with one human question. Keep the first version small. Say what is cached. Say what still needs verification. Then let the interface explain the tradeoffs instead of forcing the reader to decode a taxonomy.

The follow-up paths are already visible: Starlink versus terrestrial backup strategies, rural-connectivity decision support, and work-from-home resilience planning.