Parallel

Designed and built a 0→1 SaaS meeting scheduler that balances availability with long-term fairness across time zones, taking the product from hypothesis to a deployed MVP and early validation.

Scope: Product Strategy · UX/UI · Development · Validation
Service: Product Design & Development
Category: SaaS / AI-Assisted Development
Date: 2026
Role: Product Designer / Builder
Live Product: parallelflow.app (opens in a new tab)

Parallel landing page — “Fair meeting rotation for global teams” — shown on a desktop monitor

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Parallel is an independently designed and developed meeting scheduler for distributed teams. Unlike tools focused solely on availability, it considers how scheduling inconvenience accumulates across recurring meetings. I took the product from hypothesis and UX/UI design through AI-assisted development, deployment, and early validation in approximately one month.

For global teams, finding a time everyone can attend does not guarantee fairness. Participants in certain time zones may consistently accommodate inconvenient hours. Parallel reframes scheduling from finding a single workable time to distributing meeting burden more intentionally across multiple weeks.

Fairness is difficult to quantify when team members have different working hours, availability, and time-zone boundaries. The challenge was designing a scheduling system that could evaluate these constraints, distribute inconvenience where feasible, and explain its decisions clearly—while keeping the product intuitive enough for everyday use.

I designed an end-to-end workflow for creating teams, defining availability, generating rotations, and reviewing schedules. The scheduling engine considers working hours, hard boundaries, and accumulated meeting burden across weeks. Fairness scores, sacrifice timelines, and scheduling explanations make algorithmic decisions visible. I used Next.js, TypeScript, Supabase, and AI-assisted coding tools to build and refine the functional MVP.

Delivered a deployed web application with team management, recurring meeting rotation, and fairness analysis. The product demonstrated technical feasibility and an end-to-end design-to-development workflow. Early validation suggested that scheduling fairness was often perceived as a nice-to-have rather than an urgent problem, helping me reassess the opportunity before investing further.

Fair meeting rotations generated: 4–12Weeks
Supported per Pro team: 20Members
Scheduling modes: 4Modes

Parallel taught me to separate successful execution from product-market need. AI-assisted development accelerated the journey from concept to working software, but building quickly did not guarantee demand. The most valuable outcome was learning to use early validation to challenge my assumptions and guide future product decisions.

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01Project OverviewDesigned and built a 0→1 SaaS product that distributes inconvenient meeting times more fairly across global teams through recurring scheduling.+

02The ProblemTraditional scheduling prioritizes availability, often overlooking how early or late meetings repeatedly disadvantage the same team members.+

03The ChallengeTranslated an abstract fairness concept into understandable scheduling workflows while balancing time-zone constraints, algorithmic complexity, and MVP scope.+

04Key DecisionsBuilt a fairness-aware rotation engine, prioritized transparent scheduling decisions, and used AI-assisted development to rapidly test the product hypothesis.+

05Results & ImpactShipped a functional SaaS MVP in approximately one month and gained early validation insights showing fairness was a meaningful but lower-priority user need.+

06LearningsLearned that building a functional product validates technical feasibility, but meaningful product success also requires evidence of genuine user demand.+

Let's make it workfor people.

Let's make it work
for people.