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PRODUCT STRATEGY · UX/UI · AI-ASSISTED IOS BUILD

ALONGSIDE

From “who wants to go with me?” to a social coordination product built around real plans, real timing, and people nearby.

ROLEProduct Designer & Product Strategist
FOCUSiOS · Social coordination · Local activity
TOOLSFigma · Codex · VS Code · AI-assisted development
Alongside home feed showing nearby activities
Alongside activity detail screen with request to join action
POST A PLAN
FIND SOMEONE NEARBY
THE OPPORTUNITY

Fitness apps track the workout. Alongside focuses on the plan.

The idea started with a repeated real-world problem: people want to walk, run, lift, play pickleball, or simply get out of the house, but the hardest part is often finding someone nearby who is available at the same time.

The product opportunity was not to create another fitness tracker or another profile-browsing network. It was to make ordinary activities joinable.

WORKING IOS PRODUCT

THE PRODUCT IN MOTION.

See the Alongside experience move from discovery to real-world coordination.

THE PRODUCT QUESTION

How might we turn solo intent into a real plan with someone nearby?

01

Intent disappears fast

“I should go work out” is easy to postpone when there is no one else expecting you.

02

Availability matters

A perfect activity match is not useful if the other person is never free when you are.

03

Coordination creates friction

Too much messaging, planning, and uncertainty can kill an activity before it starts.

PRODUCT PRINCIPLE

MAKE ORDINARY PLANS JOINABLE.

Instead of asking users to build a social graph first, Alongside starts with something concrete:

“I’m doing this, at this time, in this place. Want to come?”

That decision shaped the feed, plan details, join flow, creation flow, and trust model.

THE CORE EXPERIENCE

See something relevant. Join quickly. Show up.

Alongside home feed with activity recommendations
01 · DISCOVER Relevant plans are visible immediately.

The home feed emphasizes activity, time, distance, pace, host, and remaining spots instead of generic profiles.

Alongside plan detail with host information and request to join button
02 · DECIDE Enough context to decide without overthinking.

Plan details surface the practical signals that matter: when, where, pace, group size, and host credibility.

Alongside post a plan activity step
03 · CREATE Posting a plan should feel lighter than planning an event.

The creation flow is intentionally structured around activity, timing, location, and fit instead of event-management overhead.

KEY PRODUCT DECISIONS

Designing for coordination, not browsing.

01

Plans before profiles

The primary object is the activity plan. People become relevant because they are attached to something happening.

02

Time and place are first-class signals

Distance, start time, duration, and pace help users decide whether a plan is realistically joinable.

03

Low-pressure creation

Posting should feel like saying “I’m going” rather than creating a formal event.

04

Trust has to exist before the meetup

Profile context, identity verification, location privacy, blocking/reporting, and community standards are treated as product features, not afterthoughts.

DISCOVERY + TRUST

The product has to work before the network feels big.

Alongside Explore screen with activity filters
ExploreFilter by time, distance, and pace when the feed is not enough.
Alongside profile and safety settings
Safety by designLocation privacy, block/report, and standards are visible in the product experience.
Alongside edit profile screen with activities and availability
Compatibility signalsActivity preferences, pace, and availability help improve fit without turning the app into a dating-style matcher.
AI-ASSISTED BUILD PROCESS

AI accelerated the build. Product thinking still drove the decisions.

Product strategy

Clarified the core problem, MVP behavior, information hierarchy, and experience priorities before implementation.

UX/UI design

Designed the native iOS flows and iterated on feed density, plan creation, joining, empty states, and trust patterns.

Codex + VS Code

Used AI-assisted development to move from design intent to working product faster, then iterated through real simulator builds.

Human review

AI supported execution, but product judgment, prioritization, usability decisions, and visual quality stayed human-led.

CURRENT STATE

A working product direction, still being validated.

What exists now

  • Native iOS product experience
  • Home feed and discovery
  • Activity detail and join/request flow
  • Post-a-plan flow
  • Explore, inbox, plans, and profile/safety patterns
  • Public waitlist and positioning site

What I would validate next

  • How quickly new users find a relevant plan
  • Plan creation completion rate
  • Request-to-join acceptance rate
  • How often plans actually result in people showing up
  • Which trust signals matter most before meeting
  • Cold-start behavior when nearby supply is limited
REFLECTION

The strongest version of Alongside is not “another fitness app.”

It is a lightweight coordination layer for real life. The product becomes more useful when it reduces the distance between wanting to do something and having an actual person to do it with.

PRODUCT WORK

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