Overview
Full Squish is a mobile app designed to help mountain bikers optimize their suspension setups through experimentation and data tracking. By allowing riders to record and analyze their suspension settings, Full Squish empowers users to find the perfect balance between performance and comfort, tailored to their specific riding conditions and preferences.
The Problem
Challenge
When setting up a mountain bike, suspension configuration is critical to performance and comfort. This setup varies based on trail conditions and riding style preferences. As riders evolve their skills or explore new terrain, they need different suspension settings for optimal performance. Many riders struggle to remember their preferred settings for various conditions, leading to inconsistent experiences and reduced enjoyment.
Beyond initial factory suggestions, suspension setup is intimidating. There is a fear that you'll mess something up by changing it. If you don't play around you won't know if the factory setting is the best setting or worst setting. Then comes the issue of remember what changes you did and how that affected your ride.
- Intimidation of changing suspension settings
- Difficulty remembering specific settings for different conditions
- Lack of data to compare different setups
The Solution
Full Squish provides a clean, intuitive interface that prioritizes quick recording and retrieval of suspension settings. The app empowers riders to experiment confidently with their suspension setup by maintaining a reliable record of their configurations.
Core Features
- Quick Setup Recording: Easily save complete suspension configurations for different riding conditions
- Configuration Management: Store multiple setups and switch between them as needed
- Notes & Context: Add details about trail conditions, riding style, and performance feedback
Development Process
I implemented "vibe coding" in collaboration with Windsurf, breaking down the larger vision into manageable components. This collaborative approach between human product thinking and AI technical execution created an efficient development workflow.
Technical Approach
Our approach involved:
- Structured AI Prompts: Using user story mechanics to maintain clarity and purpose throughout development
- Educational Framework: AI responses included what we were building, why it mattered, and educational explanations to facilitate learning
- Incremental Sprints: Developing in small iterations with regular testing and refinement
- Clean Architecture: Utilizing Node.js for backend functionality and SQL for data persistence
- User-Centric Design: Creating an intuitive interface that prioritizes quick recording and retrieval
Iterations & Testing
Before official launch, Full Squish was in beta for several months through TestFlight. I invited local mountain bikers and friends to provide immediate feedback, incorporating their insights to continuously improve the user experience.
The short feedback loop and my heavy involvement with testing enabled quick iterations, rapid fixes, and faster feature deployment.
Impact
Full Squish is now available for download in the Apple App Store! User feedback has been positive, with riders appreciating the convenience of storing multiple suspension configurations and the ability to track their setup experiments over time.
Check it out!
Skills Acquired
This project significantly expanded my technical knowledge and product management capabilities:
- React Native Development: Cross-platform mobile application development
- Apple Developer Ecosystem: Navigation of Apple's development tools and TestFlight deployment
- AI Prompt Engineering: Effective collaboration with AI for technical implementation
- Database Design: Structuring databases for user preference storage and data persistence
- Iterative Product Development: Building and refining minimal viable feature sets based on user feedback
The experience has been invaluable in bridging my product management expertise with hands-on technical implementation, while addressing a real need in the mountain biking community.
Future Roadmap
Full Squish is still version 1.0.2 so there are some tech debt I'd like to address and then incorporate features user could value
- Refactoring & Tech Debt: Continue improving code architecture and reducing technical debt to ensure long-term maintainability
- LLM Chatbot Integration: Incorporate a large language model-powered chatbot to help users with basic suspension knowledge and setup guidance
- AI Suspension Guru: Develop an advanced AI model that acts as a suspension expert, providing personalized setup recommendations based on rider data and preferences