- Role
- Modeled how answers, citations, competitors, and risks should become a usable product surface.
- Outcome
- The experiment turned answer-engine ambiguity into dashboard states and comparison views.
- Evidence
- Sanitized product model and visuals.
- Context
- Brands need to see how answer engines describe them.
- Built
- Prompt sets, answer capture, source maps, competitor views, risk tags.
- Stack
- Next.js, TypeScript, prompt runs, source classification, dashboard UX.
- Proof
- Private product experiment with sanitized visuals.
case notes
A bounded product surface.
Each experiment is useful because it makes a constraint concrete: device limits, operator visibility, answer-engine ambiguity, or agent review.
Prompt trackingSourcesCompetitorsRisk tagsDashboards
system notes
- What: Track answers, citations, competitors, and changes.
- Shape: Runs grouped by topic, engine, geography, and source.
- Proof: Product model and dashboard design.