Maintaining a pool requires tracking interacting chemistry readings and deciding what to do next. Pool Pulse translates these complex variables into a clear, approachable, mobile-first experience for everyday pool owners.
Opportunity & Differentiation
Existing pool maintenance apps can be overly complicated, cluttered with subscription paywalls, or assume a high level of chemistry expertise. Many surface a wall of numbers that leaves users guessing what to tackle first. Pool Pulse was conceived to fix this by focusing on an approachable everyday-owner experience. It replaces the cognitive load of balancing eight interacting variables with a single overall water-health score, clear reading statuses, and plain-language prioritized guidance.
My Role & Responsibilities
I defined the problem and the minimum viable product (MVP). My work spanned the full product cycle: designing the logging experience, creating the health score and status indicators, developing the recommendation logic, structuring the data, and designing the final interface. I tested all calculations, workflows, and usability.
Crucially, I built this application using an AI-assisted workflow—leveraging Replit alongside Claude, Gemini, ChatGPT, and Perplexity to iterate through prompts, write code, and refine product decisions.
Interactive Product Tour
Explore Pool Pulse
Click the product image to advance, choose a screen below, or use the previous and next controls.
Water Health Dashboard
An at-a-glance score, water-balance status, individual readings, and recent trends make the current condition easy to understand.
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The Chemistry
Eight Tracked Measurements
Pool Pulse tracks all essential parameters to ensure complete water balance.
The Experience
Visual Product Flow
The application guides users from raw data entry to confident action through three distinct phases.
1. Log Readings
Users input their latest test results via a mobile-optimized form designed for quick entry while standing at the pool deck.
2. Score & Status
Raw numbers are immediately converted into a unified Water Health Score and clear status indicators for each measurement.
3. Action Plan
The app synthesizes the data to provide plain-language, prioritized guidance on what needs to be adjusted and in what order.
MVP Capabilities
Mobile-First Logging
Frictionless data entry for daily tests on the pool deck.
Historical Records
Persistent log of past readings to track changes over time.
Status Indicators
Clear visual cues (green/yellow/red) for each measurement.
Health Score
A single, unified score to immediately gauge overall pool readiness.
Plain-Language Recommendations
Actionable guidance without dense chemical jargon.
Personalized Targets
Optimal ranges tailored to specific pool types and setups.
Trends
Visual progression of chemistry changes over recent logs.
An AI-Assisted Build
Building Pool Pulse was an exercise in AI-assisted development. Using Replit combined with models like Claude, Gemini, ChatGPT, and Perplexity, I moved rapidly from concept to working code. However, the process proved that AI is an accelerator, not a replacement for product intuition.
Human judgment remained central. I had to enforce clear requirements, understand the pool-chemistry domain to validate the recommendation logic, test edge cases in calculations, and make decisive product choices when the AI suggested overly complex features or generic UI patterns.
Current Result & Future Opportunities
The working MVP successfully allows users to create a pool profile, enter readings, review their current water health, and track historical results. It fulfills the core promise of simplifying pool maintenance.
Looking forward, there are clear opportunities to expand the platform's value: adding chemical-dose calculations, implementing proactive alerts, integrating weather data, creating maintenance schedules, and potentially packaging it as a native mobile application.
Lessons Learned
- AI accelerates, but doesn't decide: AI tools dramatically speed up code generation and troubleshooting, but they require clear requirements, domain understanding, and rigorous testing.
- Domain logic is the product: The value of the app isn't just the interface; it's the accuracy of the underlying chemistry logic and the clarity of how it's presented.
- Learning through building: Constructing a full application from scratch develops highly practical skills across product design, data structuring, application logic, and deployment.
- Simplicity is hard work: Boiling down complex, interacting chemistry metrics into a single score and plain-English actions takes significant design restraint and iteration.