Scaling Group Dynamics with Intelligent Routing
Seamless Exploration
The Problem
In every group, one person ends up managing the trip instead of enjoying it.
Dead navigator,
lost group
Many opinions,
no decision
Eyes down,
experience missed
Hours of planning, one rain kills it
The Insight
Navigation apps solve the wrong problem. Getting from A to B is easy. Managing five opinions about where to go next isn't. WalkWith orchestrates people, not just paths.
My Role
Self-initiated concept project. Usability walkthroughs with friends across solo and group travel contexts. AI used for initial drafts, final decisions made from scratch.
💡
Strategy &
System Design
🛠️
High-Fidelity UI & Prototyping
⚙️
AI
Orchestration
The System
Phase A • Profiling & Smart Logic
Preferences are stored once and applied automatically. Hard exclusions (e.g. wheelchair access) never change. Soft interests (transit vs. walking) adjust by context.
When the Admin's battery drops below 15%, navigation passes to a pre-assigned Co-Admin. The whole group sees the handoff. Automatic handoff to whoever has the most battery creates the wrong problem: the wrong person in charge.
Phase B • The Planning Engine
Instead of an open search field, the Mood Mixer offers three AI-prepared routes as entry points. Group preferences are applied automatically. The route is a proposal, not a fixed plan.
Phase C • Active Experience
Transit-Pivot: One tap switches between walking and transit. Arrival times update for the whole group. The route doesn't restart.
Anonymous Voting: Proposals appear as swipeable cards without revealing who suggested them. The format makes the volume of ideas visible and the decision fast.
Eyes-Up Navigation: Secondary info sits bottom right. Readable in under two seconds, in motion, without stopping.
Phase D • Achievement & Memory
Nothing is visible until you tap. GPS data, photos, and highlights combine into a shareable trip diary. Not a data export. A story.
AI in My Process
AI produced layouts fast. Every one needed fixing.
Route Guide
The AI output centered weather information at the top of the screen. Weather is secondary information: Useful as context, not as the first thing you see while navigating in motion. I moved it to the bottom right and rebuilt the hierarchy around what matters when you're moving: Direction, distance, next stop.
The final version took two prompt iterations before I had enough structure to finish in Figma.
Anonymous Voting
The AI produced a single-card layout. In a group with multiple simultaneous proposals, a single card hides the problem: you don't know how many ideas are on the table. I restructured around a swipeable stack format so the group could see the volume of options and move through them quickly. The Tinder reference wasn't an aesthetic choice. It was a decision about how fast a group needs to reach consensus when they're standing on a street corner.
Achievement
The AI showed all statistics and trip information upfront. I removed everything. Nothing is visible until you tap. The reveal is the moment. Showing the data before the tap kills it.
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The Transit-Pivot came from Japan and feet that gave out after too many kilometers. Anonymous Voting came from watching one loud person override a group of ten. The tagging system came from a sister whose dietary needs kept getting forgotten. Battery Handoff came from realizing that automatic role assignment creates new social problems instead of solving old ones.
Good product thinking doesn't start with frameworks. It starts with noticing what breaks and asking why.
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The design work felt like a sprint. AI could take a rough brief and return a layout within minutes. But it returned fragments: Structurally plausible, contextually wrong. Knowing which rule to apply to fix each one is not something AI could do. That knowledge came from real trips, real friction, real moments where the plan collapsed.
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The second prompt always produced better results than the first. Not because AI improved, but because articulating what was wrong with the first output forced more precision about what was actually needed. Prompt engineering turned out to be problem articulation. That is a transferable skill.
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The design process was fast. Explaining why each decision was right took much longer, because the thinking happened quickly and intuitively. That gap between doing and explaining is something worth closing earlier in future projects.
Learnings
Closing
I was the one staring at my phone while my sisters were looking at the city.
WalkWith exists so that the next time someone plans a trip for the people they love, they can put their phone away.
Good design doesn't replace human judgment. It creates the conditions for it. Every feature in this system is built around one question: What needs to work so that the person navigating can stop thinking about navigation?
AI helped me move faster. But the decisions that made it real came from broken moments on real trips, with real people who trusted me to figure it out.
