Loop

Inspiration

Creating connections is nothing new. Students regularly meet valuable new connections at networking events, classes, and campus activities, but many of those connections fade within days.

Our research revealed that the issue is not social anxiety or lack of opportunity. Instead, over half of respondents forget to follow up, and many cite busy schedules and uncertainty about what to say. Promising introductions dissolve not because of disinterest, but because of friction and cognitive overload.

We saw an opportunity to design a tool that prevents connection decay in the critical window after meeting someone.

What It Does

Loop is a lightweight relationship continuity tool that helps students convert initial interactions into sustained connections.

After meeting someone, users can quickly log:

• Where they met

• What they discussed

• Their follow-up intent

Loop then sends a timely reminder and generates a context-aware follow-up message, reducing the friction of reaching out.

Instead of letting weak ties fade, Loop activates them at the right moment, turning fleeting introductions into ongoing relationships.

How We Built It

We began with user research to validate whether the breakdown happened at the introduction stage, sharing contact stage, follow-up stage, or developing/maintaining stage. Our data clearly pointed to post-interaction friction.

From there, we:

• Defined a narrow scope focused on the first 7 days after meeting someone

• Designed a fast, under-20-second logging flow

• Created a reminder system tied to context

• Integrated AI-assisted draft generation to reduce initiation hesitation

Challenges We Ran Into

One major challenge was avoiding feature creep when it came to the scope of the project. It was tempting to add additional features like long-term tracking. However, our research showed the core problem was early-stage follow-up, not long-term relationship management.

Another challenge was ensuring the product did not feel transactional or artificial. We designed AI prompts to support authenticity rather than replace it, giving users autonomy of what they send.

We also had to carefully scope the product to remain feasible within the time constraints of a designathon.

Accomplishments That We’re Proud Of

• Identifying a precise and research-backed problem

• Narrowing the scope to a high-impact use case

• Designing a clear, friction-reducing user flow

• Building a concept that balances automation with authenticity

• Framing the product as “connection continuity” rather than networking

What’s Next for Loop

Next, we would:

• Conduct broader user testing across multiple campuses

• Refine AI tone calibration for different relationship contexts

• Explore calendar integration for scheduled follow-ups

• Develop event-mode logging for high-volume networking settings

Long term, Loop could expand into professional communities, conferences, and alumni networks, serving as an infrastructure layer for sustaining weak ties at scale.

Our vision is simple: Make meaningful connections easier to maintain than to lose.

Built With

• figma