Health App

MyFitnessPal is for someone else's body — a fitness influencer's, a generic adult's, a database average. I wanted Josh-shaped: my lifts, my macros, my cadence, with no nag screens or paywalls between me and the numbers I just generated. Max personalization isn't a feature — it's what's left when you delete every assumption a generic app has to make about who you are.

• Swift
• Gemini Vision
• Supabase
• AVFoundation

Phone-only — every entry has to be one-thumb-fast or I won't log it mid-set, and that's the whole game.

1. Summer 2025 — opening

   Generic trackers ask the body to fit the schema. I wanted the schema to fit the body. Three screens: log a set, log a meal, see the month.

2. First lift logged

   Dumbbell Bench Press, SET 1: weight, reps, RIR. Three numbers, three taps. The schema for the entire app is essentially that row.

   [image: iOS dumbbell bench press logger in dark mode — Weight/Reps/RIR fields stacked for Set 1 and Set 2, large numeric keypad below]

3. RIR over 1RM

   Picked Reps in Reserve instead of estimated 1RM. 1RM is a theoretical number; RIR is what I actually felt at the top of the set. Honesty in the moment beats a fiction I'd recompute later.

4. Pointing the camera at a Fairlife bottle

   Photographing replaced typing. Aim, snap, write to meal_logs. The only way logging survives a real day.

   [image: Gemini Vision food-log card analyzing a Fairlife Chocolate Protein Shake bottle and extracting 150 kcal and 30g protein straight into the Nutrition Log]

5. Macros, four bars

   Calories, Protein, Carbs, Fat — four progress bars across the top of the Nutrition Log. Targets are mine, not a database default for a 30-year-old male.

   [image: Nutrition Log screen — Calories, Protein, Carbohydrates, and Fat progress bars filling against personalized daily targets, list of today's logged meals beneath]

6. Radar chart of the body

   Six axes — Back, Chest, Core, Shoulders, Arms, Legs — pulled from 30 days of sets. Leg day becomes undeniable when the polygon is visibly lopsided.

   [image: Radar chart of 30-day muscle distribution: Back, Chest, Core, Shoulders, Arms, Legs, with the polygon stretched toward Back and Chest and clearly pinched on Legs]

7. meal_logs, raw

   Opened the Supabase dashboard and saw it all unfiltered. Typos and all — that's the truth of the week.

   [image: Supabase meal_logs table with logged rows including Scrambled Eggs with Gems and Mozzar, BelVita Crunchy Breakfast Biscuits, Bottled Beverage, Dried Apricots, and General Tso's Chicken with Rice — columns for id, created_at, title, calories, protein, fat, carbohydrates]

8. Mid-July, the gap

   Sets per day, meals per day, macro intake — all three rolling averages drop to exactly 0 for a week. That's Belize. The graph already remembered; the slide just had to admit it.

   [image: Three charts on a pink background — 7-day rolling avg sets/day and meals/day line graphs both flatlining at 0 in mid-July, and a stacked area chart of daily macros (Protein, Carbs, Fat) collapsing to zero across the same window, with a large red circle around the gap and a red arrow labeled 'Vacation' pointing at it]

30-day training view, end-to-end on my own data.

Building a tracker for your own body is a different problem than building one for everyone's — there's no edge case I have to politely accommodate, no field I have to surface because some other user might want it. The radar is calibrated to my split, the macro targets are mine, meal_logs is full of the things I actually eat. The graph also remembers the things I didn't do — mid-July is just zero, and the zero is honest.