Designing Pool Pulse with AI and Replit
OPPORTUNITY
Maintaining a swimming pool requires tracking multiple chemistry readings, understanding how they interact, and deciding what action to take next. Existing apps are often overly complicated, subscription-heavy, or designed for users who already understand pool chemistry.
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Pool Pulse enters a space that already includes capable tools such as PoolMath, which emphasizes chemistry tracking and dosing calculations; Orenda, which focuses heavily on chemical dosing and Langelier Saturation Index management; and Leslie’s Pool Care, which connects water testing with treatment plans, products, and retail services.
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Rather than attempting to replace every feature in those established products, I saw an opportunity to create a simpler, more approachable experience for everyday pool owners. Pool Pulse differentiates itself through a mobile-first dashboard, a single overall water-health score, clear status indicators for every reading, historical trends, and plain-language guidance that explains what needs attention and why. The goal is to reduce the cognitive load of pool maintenance by turning a collection of chemistry measurements into a prioritized, personalized action plan.
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Role
I developed the concept, defined the product requirements, designed the user experience, and built the working web application in Replit with the support of AI-assisted development tools. My work included:
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Defining the core user problem and MVP scope
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Designing the chemistry logging experience
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Creating health scores and status indicators
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Developing the recommendation logic
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Structuring the data model
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Designing a mobile-first interface
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Testing calculations, workflows, and usability
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Iterating through prompts, code, and product decisions
APPROACH
I started by identifying the pool measurements that matter most, including free chlorine, pH, total alkalinity, calcium hardness, cyanuric acid, salt, temperature, and total dissolved solids. I then designed a simple workflow that allows users to enter results, see an overall pool health score, review the status of each measurement, and receive plain-language actions. Replit and AI-assisted coding allowed me to move quickly from concept to a deployed MVP while learning how to evaluate generated code, refine requirements, troubleshoot issues, and make product tradeoffs.
WHAT I BUILT
Pool Pulse provides a centralized place to record pool chemistry readings and monitor how conditions change over time. The dashboard translates individual measurements into status indicators, an overall health score, and a prioritized action plan.
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The MVP includes:
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Mobile-first chemistry logging
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Historical test records
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Per-measurement status indicators
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Overall pool health scoring
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Plain-language recommendations
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Personalized target ranges
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Trend visibility across previous readings
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The working MVP allows users to create a pool profile, enter chemistry readings, review the current health of the water, and track results over time. It demonstrates how structured data, rule-based logic, and AI-supported development can come together in a focused consumer application. The product is still evolving, with future opportunities around chemical-dose calculations, alerts, weather integration, maintenance schedules, and native mobile delivery.
LESSONS LEARNED
Building Pool Pulse reinforced that AI can dramatically accelerate product development, but it does not remove the need for clear requirements, domain understanding, testing, and judgment. The most valuable work was often not generating code, but deciding what the product should do, identifying when the generated solution was incomplete, and simplifying the experience around the user’s actual problem.
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It also showed me that learning through building creates a different level of understanding. By moving from idea to working application, I gained practical experience with product design, data structures, application logic, deployment, and AI-assisted software development.