How I Built ReadyWOD with AI

From Data Chaos to an Offline AI-Powered Fitness App

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📱 iOS Available Now • 🤖 Android Coming Soon

🏋️ From Data Chaos to an Offline AI-Powered Fitness App

ReadyWOD is a fully offline, AI-driven iOS fitness app designed to make training effortless. It combines years of real workouts with Core ML intelligence — all built by me with the help of AI (Cursor), even though I had zero prior knowledge of coding in Swift.

The Problem

Over the years, I collected thousands of workouts across spreadsheets, screenshots, and notes. Every training session began with the same frustration — too many choices. I wanted one app where people could tap once and instantly get a workout, with the flexibility to modify movements or reps, all while working completely offline.

Building the Data Foundation

I used Python to scrape workouts from various free online sources, cleaned the data, and organized it into a structured JSON library with over 20,000 workouts categorized by EMOM, AMRAP, Task, Bodyweight, Strength, and Minimalist styles. That dataset became the foundation of the app.

Creating the App with AI

Since I didn't know Swift, I built ReadyWOD using AI-assisted development with Cursor. I wrote the logic and design intent, and Cursor generated the SwiftUI, Core ML, and StoreKit code. Through this process, I learned Swift by building, testing, and refining the app alongside AI.

What ReadyWOD Can Do Today

🧠 Core ML Integration: Learns from user history to recommend balanced workouts.
🔄 Smart Lift & Movement Rotation: Prevents overtraining and ensures variation.
🏋️ Custom Workouts: Users can add their own sessions — ReadyWOD automatically generates warm-ups and recovery.
🧾 Workout Logging: Tracks all sessions locally or via iCloud.
⏱️ Timers & Calculators: Includes EMOM, AMRAP, and lifting percentage tools.
💪 Bodybuilding Expansion: Includes dedicated hypertrophy programs and routines.
🌐 Completely Offline: Everything — data, AI logic, and history — runs on device.
☁️ iCloud & StoreKit: Enables syncing and premium subscription management.

Why Offline Matters

All workouts, recommendations, and user data are stored on the device. There are no servers, no trackers, and no dependencies — just fast, private fitness intelligence.

By the Numbers

20,000+
Workouts
6
Categories
100%
Offline
1
Tap to Start

Lessons Learned

  • AI can help non-developers build real, production-level apps.
  • Clean data and tagging make intelligent features easy to scale.
  • Offline-first design builds trust and speed.
  • Giving users control (custom workouts) creates long-term engagement.

The Future

ReadyWOD continues to evolve with smarter analytics, deeper AI adaptation, and new training modes. The goal is simple — reduce decision fatigue, promote consistency, and make training intelligent, adaptive, and private.