I Used Base44 To COPY This $1.2M/mo App (Step By Step)

Cal AI makes over a million dollars a month from one core idea: take a photo of your food and the AI figures out the rest. Here's how to build your own version without writing a single line of code.
👉 Get Prompts: https://georgevibecodes.com/prompts/macrosnap-app
👉 Build App With Base44: https://base44.pxf.io/c/3690544/2049275/25619?subId1=macrosnap-app&trafcat=base (free plan + exclusive discount)

In this video, George Vlasyev walks through how to build MacroSnap, a Cal AI-inspired calorie and macro tracker, using Base44 from scratch. The build covers AI food scanning, a personalized onboarding flow, exercise logging with automatic calorie calculation, a food database, saved foods, a weight and calorie progress tab, and a full data sync pass. We're looking at the complete prompt-to-app workflow for 2026, built exclusively for mobile and tablet.

🕒 Timestamps:
00:00 - Intro
01:23 - Naming the app and setting the foundation
02:56 - Building the home dashboard
04:15 - Log exercise
05:41 - Scan food
06:51 - Food database and saved foods
07:31 - Progress tab
08:22 - Cleaning up the navigation
08:55 - Fixing the details
10:28 - Testing on mobile
11:29 - Verdict
12:21 - Outro

💡 About The Video:
Base44 is a prompt-based app builder that lets you create fully functional web apps without writing a single line of code. In this tutorial, George reverse-engineers the core feature set of Cal AI, one of the highest-grossing calorie tracking apps on the market, and rebuilds it as MacroSnap using prompts alone. The build is mobile and tablet only: at desktop widths, the app shows a message directing users to open it on their phone, which is the right call for an app built around food photography and on-the-go logging.

The foundation uses a four-step onboarding flow that collects the user's goal, activity level, and personal stats, then calculates a personalized daily calorie target and macro split using the Mifflin-St Jeor formula, all stored in localStorage so every other feature pulls from it. The home dashboard includes a weekly date strip, a calories remaining ring, three macro progress rings, and a recently logged list that surfaces both food and exercise entries. Scan Food sends the uploaded image to the AI and returns a full macro breakdown with an editable serving size multiplier before logging. The Food Database does the same with a text search, returning up to five variations per query. Exercise logging uses the MET formula to auto-calculate calories burned based on the user's onboarded weight, intensity, and duration, with dynamic activity icons matched to the exercise name.

The video also covers a post-build fix where the Add to Log button on the Scan Food screen was visible but not tappable on a real device, a reminder that browser emulators and actual phones don't always behave the same way. All prompts used are listed in the timestamps above.

📲 Connect:
- Work with me: https://vlasyev.com
- LinkedIn: https://linkedin.com/in/georgevlasyev

#GeorgeVlasyev #Base44 #VibeCoding

Видео I Used Base44 To COPY This $1.2M/mo App (Step By Step) канала George Vibe Codes