Would this also support weight gain, in addition to weight loss? It would be awesome to see both calorie deficits and surpluses as possibilities

To enable Bevel to fully support users in achieving their weight goals, the app should align daily calorie targets dynamically with energy expenditure, while offering predictive guidance and flexible macronutrient control. This combination of real-time accuracy, AI-powered foresight, and personalized nutrition settings would set Bevel apart from any existing solution.

Dynamic Calorie Targets

Core Principle

• Resting Energy (BMR) forms the baseline (Apple: Resting Energy).

• Active Energy (workouts, steps, daily activity) adds on top (Apple: Active Energy).

• A deficit is subtracted to ensure consistent progress.

Users should be able to overwrite Apple’s BMR with a measured value (e.g., Seca/Tru body analysis) for more accuracy, esp. with atypical body composition.

Example

• Morning: baseline = Resting – Deficit.

• Evening: +600 kcal Active Energy updates goal dynamically.

• Resting Energy source = Apple or user input.

AI Habit Recognition

Dynamic targets are precise but unpredictable. AI improves usability through forecasts:

1. Pattern Detection: weekly cycles, time anchors, duration, consistency, absence decay.

2. Context Awareness: gym visits, calendar events, weather, sleep/recovery, social triggers.

3. Projections: show baseline + 2–3 likely scenarios (e.g., “Strength adds ~420 kcal,” “Cycling +600–800 kcal”).

4. Confidence Levels: Low 20–40%, Medium 50–70%, High 80%+.

5. Online Learning: recent data weighted higher; old habits fade after 6–8 weeks; cold start uses averages; runs on-device for privacy.

Macronutrient Targets: Flexible Setup

Most apps lock macros to calorie percentages. Bevel should allow per-nutrient choice:

• Protein: fixed grams (e.g., 2 g/kg BW).

• Fat: minimum in grams for hormonal health, or %.

• Carbs: fill the remainder (as % or fixed grams).

Each macro can be set as grams or %, not one-size-fits-all. Example: Protein fixed, Fat %, Carbs auto-fill.

Summary

• Dynamic targets = consistent deficits/surpluses via Resting + Active Energy.

• BMR flexibility = Apple or measured input.

• AI recognition = forecasts activity with probabilities and context.

• Macro flexibility = protein by BW, fat minimums, carbs adaptive.

Together, this creates a precise, adaptive, athlete-friendly system that combines real-time tracking with predictive intelligence — supporting both weight loss and weight gain, helping athletes optimize for either goal with equal precision.

I couldn't find that yet... nice when it gets picked up!

This would be an awesome feature!