Q&A with Foursquare co-founder Dennis Crowley on his startup Hopscotch Labs, which uses AI and headphones to give information as a person walks by a location
Dennis Crowley has built his career at the intersection of emerging technologies and human behavior. X: @om . Forums: Hacker News X: @om : I recently sat down with Dennis Crowley (@dens) to discuss his new startup, Hopscotch Labs. We discussed the convergence of new technologies such as LLMs, and augmented reality, and where we are going into our future. We got talking about AI, our children, and entrepreneurship. [image] Forums: Hacker News : With AI, the future of augmented reality is in your ears
Context & Ripple Effects
Crowley’s Hopscotch Labs extends a long-running thread from Foursquare: its earlier Pilgrim location technology was framed around making location data useful to other appmakers, while Hopscotch moves the interaction toward a person’s immediate surroundings.
The interview connects LLMs with audio-led augmented reality rather than camera-first interfaces. Related coverage later shows that direction becoming more product-specific through BeeBot’s combination of AI, audio, and location-based social features.
First-order effects
- Hopscotch Labs is positioned around headphones as the delivery layer for location-aware AI, giving users spoken information while moving through physical spaces.
- For Crowley, the startup applies his location-product experience to an AI interaction model that does not require users to hold up a phone or look at a screen.
Second-order effects
- Audio-first AR products must differentiate on the relevance and timing of their location cues; generic AI responses are less useful when the system is meant to react to a changing physical context.
- The approach creates a clearer contrast with camera-led AR, a direction associated with Snap’s view of a camera-dominated future, by making ears rather than eyes the primary interface.
Third-order effects
- If location-aware AI becomes a habitual ambient service, competition will shift from standalone AR displays toward the quality of context, consent, and interruption management in everyday interfaces.
- The model also keeps location-data governance central: products that deliver information in the background will need to earn trust around when location is used and how personalized the audio becomes.
The trend: This is one example of ambient AI moving from screen-based prompts toward context-sensitive, voice-delivered assistance in the physical world.