AI Plan Recommendations | FitConnect Coach Guide
Get AI suggestions for next training phases based on client progress. Proactive programme optimisation.
What Are AI Recommendations?
AI Plan Recommendations are proactive suggestions generated by analysing your client's data. Instead of waiting for you to request help, the AI identifies opportunities to improve their plan and surfaces actionable recommendations.
Think of them as an AI assistant that reviews each client's progress and says, "Based on what I'm seeing, you might want to consider this change."
Recommendation Types
Workout Recommendations
- Increase volume for lagging muscle groups
- Add progressive overload to stalled exercises
- Swap exercises for better muscle activation
- Adjust training frequency based on recovery
Nutrition Recommendations
- Adjust calories based on weight trends
- Rebalance macros for goals
- Address micronutrient gaps
- Meal timing optimisation
Recovery Recommendations
- Add deload week based on fatigue signals
- Improve sleep habits
- Reduce training intensity after plateau
- Schedule active recovery sessions
General Recommendations
- Update goals based on progress
- Connect wearable for better tracking
- Log measurements more frequently
- Schedule a check-in session
Priority Levels
Each recommendation is assigned a priority level:
Requires immediate attention
Client is at risk of injury, significant regression, or plan failure. Address within 24-48 hours.
Should be addressed soon
Will improve results if implemented. Review during your next planning session.
Nice to have
Optimisation opportunities. Consider when time allows or during plan reviews.
Data Used for Generation
The AI analyses multiple data points to generate relevant recommendations:
- Progress logs – Weight, measurements, body composition trends
- Workout history – Completion rates, exercise performance, volume trends
- Nutrition logs – Calorie and macro adherence, meal consistency
- Wearable data – Steps, sleep, heart rate variability, recovery metrics
- Engagement signals – Habit compliance, message responsiveness, session attendance
- Goals and timelines – Current objectives and target dates
More complete client data leads to better recommendations. Encourage clients to log consistently and connect wearable devices.
Applying Recommendations
Review the Recommendation
Read the suggestion and the rationale provided. The AI explains why it's making this recommendation based on the client's data.
View Suggested Changes
Click View Details to see the specific changes the AI is proposing – which exercises, foods, or settings would be modified.
Apply or Modify
Click Apply to implement the changes directly, or Editto make adjustments before applying.
Notify Client (Optional)
Choose whether to message the client about the change. The AI can draft an explanation message for you.
Dismissing Recommendations
Not every recommendation will be relevant. You can dismiss suggestions that don't apply:
Dismissing recommendations helps the AI learn. It will adjust future suggestions based on what you find useful.
Regenerating Recommendations
You can request fresh recommendations at any time:
- After applying changes – Get new suggestions based on the updated plan
- After new data arrives – Refresh after client logs progress or syncs wearable
- During planning sessions – Generate batch recommendations for multiple clients
Recommendations are generated based on available data. If a client hasn't logged anything recently, suggestions may be less accurate or unavailable.