Athlete UGC Pipeline for Anothr Lap
Building the metadata, taxonomy, and trust substrate for credible AI-powered race intelligence.
For recruiters
30-second scan
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Lead Product UX Designer for Anothr Lap, designing multi-sided UX across athletes, race directors, and coaches.
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Owned end-to-end product systems across web + mobile: discovery, community, content creation, dashboards, IA, and trust-centered recommendation flows.
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Built the metadata, taxonomy, and trust substrate powering AI-driven race intelligence: 5–8× metadata quality, +40–50% descriptor consistency, ~5% vocabulary mismatch, and reduced moderation workload by 25–35% across 1,200+ submissions.
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Led cross-surface design systems governance (tokens, components, contribution standards) and streamlined design-to-engineering delivery via Figma MCP.
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Partnered cross-functionally on MVP scoping, usability validation, and systems-level product iteration.
Details
Anothr Lap
Client
Role
Lead UX Designer
End-to-end ownership from research through shipped components.
Timeline
Q2 2025 - Q1 2026 (ongoing)
Product management, engineering, data science, endurance athletes
Collaborators
Due to product confidentiality, certain data, metrics, and implementation details have been simplified or anonymized.
The design approach and system thinking reflect the real project work.
💌 Get in touch to learn more.
Background
Anothr Lap’s mission is to bring transparency to the racing industry by rewarding races that create great athlete experiences.
Athletes leave structured reviews → reviews become trustworthy discovery signal → race directors get actionable insights → better races get rewarded.
The product hinges on a fundamental loop:
The Problem
By 2025 rapid platform growth revealed three UX failures before AI could ship:
- Inconsistent review language blocked reliable race-data aggregation
- Athletes, directors, and coaches needed distinct decision‑support
- AI summaries were planned before the data layer was ready.
The Users
Runners, triathletes, and trail racers seeking real race tips from fellow athletes, tired of scattered Strava/Reddit reviews.
Athletes
Race Directors
Want clear athlete feedback to understand perceptions, compare with past years, and guide improvements
Internal Ops
Check submissions, keep data accurate, and make sure every published review is trustworthy
Use Case
🔍 Discover a race
Search by sport, location, or difficulty, surfacing peer-reviewed races with structured metadata.
📋 Evaluate with peer intelligence
Read structured athlete reviews: difficulty, terrain, vibe, and classifications, all in a common vocabulary.
✅ Submit their own review
After racing, contribute structured feedback that helps the next athlete make the same decision with more confidence.
Research
Interviews · 12 pro athletes · 16 beginners · 6 race directors
Beta Surveys · 148 responses
Weekly Moderation Reviews
Hotjar Session Replays
