Understanding AI Suggestions

Learn how the AI makes scheduling recommendations and how to interpret them.

Last updated this week

Sentuent's AI doesn't just book sessions - it actively suggests optimal times based on patterns, preferences, and best practices. Understanding how these suggestions work helps you make better scheduling decisions.

How AI Suggestions Work

The AI analyzes:

1

Historical Patterns

Reviews your past booking behavior and preferences

2

Calendar Availability

Checks both calendars for free time

3

Learning Science

Applies optimal spacing for retention

4

Both Parties' Preferences

Finds win-win time slots

5

External Factors

Considers timezone, time of day, day of week

Types of Suggestions

Time Slot Recommendations

When you ask for availability:

You: "When can we meet next week?"

AI suggests: "Based on your schedules and preferences:

Recommended:

  • Tuesday, Dec 12 at 4:00 PM ⭐
  • Thursday, Dec 14 at 4:00 PM ⭐

Also available:

  • Wednesday, Dec 13 at 3:00 PM
  • Friday, Dec 15 at 5:00 PM"

Why stars (⭐) appear:

  • Matches your typical session times
  • Good spacing from last session
  • Overlap with historical patterns
  • Both parties' preferred times

Session Frequency Suggestions

For ongoing tutoring:

AI notices: You've had 3 sessions in 2 weeks

AI suggests: "You're currently meeting 1-2 times per week. For consistent progress, would you like to schedule recurring sessions? I can set up the same day/time each week."

Rationale: Regular sessions improve learning outcomes

Frequency recommendations based on:

  • Subject difficulty
  • Student goals (casual learning vs exam prep)
  • Learning science (spaced repetition)
  • Both parties' availability

Session Length Suggestions

AI recommends durations:

For exam prep: "For comprehensive exam review, I recommend a 90-minute session instead of your usual 60 minutes. This allows time for practice problems and Q&A."

For quick help: "Since you have specific questions, would a 30-minute session work? Saves credits and fits your schedule better."

Based on:

  • Session purpose
  • Amount of material to cover
  • Historical session effectiveness
  • Student's learning pace

Optimal Spacing Suggestions

For multi-session planning:

Scenario: Exam in 3 weeks, need 6 sessions

AI suggests: "For best retention, I recommend spacing sessions like this:

Week 1: Monday & Thursday Week 2: Monday & Thursday Week 3: Monday (final review 4 days before exam)

This 3-4 day spacing optimizes learning retention better than cramming 6 sessions in the final week."

Spacing science:

  • 2-4 days between sessions = optimal for most subjects
  • Too close = not enough practice time
  • Too far = forgetting between sessions

Interpreting Suggestion Confidence

High Confidence Suggestions

Marked with ⭐ or labeled "Recommended"

High confidence means:

  • Strong match with your patterns
  • Both calendars clearly available
  • Aligns with learning best practices
  • Similar to previously successful bookings

✓ You've had 4 Tuesday 4pm sessions ✓ All went well ✓ Both calendars free Tuesday at 4pm → AI strongly recommends Tuesday at 4pm

Medium Confidence Suggestions

Listed as "Also available"

Medium confidence means:

  • Available but not perfect match
  • Different from your usual pattern
  • Or first-time booking (no history yet)
  • Still viable, just less optimal

Context-Specific Suggestions

AI explains reasoning:

AI: "Thursday at 6pm is available, though it's later than your usual 4pm sessions. However, it's the only overlapping time this week that gives you 3 days to practice before your Friday exam."

Explanation: Sub-optimal time, but best for your specific goal

Common Suggestion Scenarios

New Student/Tutor Relationship

First booking together:

AI: "Since this is your first session together, I recommend a 30-minute introductory session to:

  • Assess your current level
  • Discuss learning goals
  • Confirm you're a good fit

After that, you can schedule longer regular sessions."

Why: Reduces commitment risk, allows evaluation

Exam Preparation

When you mention an exam:

You: "I have a chemistry exam on December 20"

AI suggests: "With 2 weeks until your exam, I recommend:

  1. This week: 2 sessions for content review
  2. Next week: 2 sessions for practice problems
  3. Exam week: 1 final review session 2-3 days before

Book all 5 sessions now?"

Strategy: Content → Practice → Review progression

Inconsistent Schedule Patterns

When your schedule varies:

AI notices: Your last 5 sessions were all at different times

AI suggests: "I notice your schedule varies. Would you like me to check your availability each week and suggest the best times? Or would you prefer to set recurring sessions for consistency?"

Options:

  • Flexible: AI suggests weekly
  • Consistent: Pick a standard time

Long Gap Between Sessions

After a break:

AI: "It's been 3 weeks since your last session. Would you like a review session to refresh the material before continuing with new topics?"

Rationale: Longer gaps may need review

Understanding "Why" Behind Suggestions

AI Explains Reasoning

When you ask "why?":

You: "Why do you recommend Tuesday over Wednesday?"

AI: "Tuesday is better because:

  1. You've had good success with Tuesday sessions (3 of your last 4)
  2. It's 3 days after your last session (optimal spacing)
  3. Wednesday you have an evening commitment (per your Google Calendar)
  4. Tuesday at 4pm has been your most productive time historically

But Wednesday is definitely possible if you prefer!"

Transparency in Suggestions

AI shows its work:

  • References your patterns
  • Explains scheduling logic
  • Notes external constraints
  • Acknowledges uncertainties

Overriding Suggestions

You're Always in Control

You can:

  • Accept suggestions as-is
  • Modify suggested times
  • Pick non-recommended times
  • Manually schedule without AI

AI suggests: "Tuesday at 4pm" You: "Actually, can we do Wednesday at 6pm?" AI: "Absolutely! Booking Wednesday at 6:00 PM."

No pushback, AI just confirms

When to Override

Good reasons to override AI:

  • You know your schedule better (upcoming commitments)
  • Personal preferences (prefer evenings even if mornings suggested)
  • Specific constraints AI doesn't know
  • Just want to try different time

AI learns from overrides: If you consistently override a pattern, AI adapts future suggestions

Improving Suggestion Quality

Provide Feedback

Help AI learn your preferences:

After booking: "I prefer morning sessions, even though we've done afternoons. Can you suggest mornings going forward?"

AI learns: Deprioritizes afternoon suggestions

Sync Your Calendar

More data = better suggestions:

  • Google Calendar sync shows all commitments
  • AI avoids suggesting times you're actually busy
  • Suggests times that align with your routine

Set Scheduling Preferences

Settings > Scheduling Preferences:

  • Preferred days of week
  • Preferred times of day
  • Minimum time between sessions
  • Default session length

AI incorporates preferences into suggestions

Learning from Suggestion Patterns

Recognizing Your Patterns

AI reveals insights:

Dashboard > Insights: "You book most sessions on Tuesdays and Thursdays at 4-5pm. Your completion rate for these times is 95%, compared to 78% for other times.

Recommendation: Stick with Tuesday/Thursday 4pm for best results."

Useful for:

  • Understanding what works
  • Optimizing your schedule
  • Improving session attendance

Adapting to Changes

AI notices schedule shifts:

AI: "I notice you've shifted from afternoon to evening sessions in the last 3 weeks. Should I start suggesting evening times by default?"

Adapts to: New job, schedule change, seasonal shifts

Advanced Suggestion Features

Multi-Factor Optimization

AI balances multiple criteria:

Factors considered:

  1. ✓ Your preferred time (4pm) - Weight: High
  2. ✓ 3-day spacing from last session - Weight: Medium
  3. ✓ Tutor's typical availability - Weight: Medium
  4. ✗ Your exam in 5 days - Weight: High

Result: Suggests slightly earlier (3pm) to give more study time before exam, overriding usual 4pm preference

Weighting:

  • Urgent constraints (exams) override preferences
  • Long-term patterns weighted heavily
  • One-time preferences weighted lower

Seasonal Adjustments

AI adapts to academic calendar:

During finals week: "I notice many of your peers are scheduling intensive review sessions this week. Would you like more frequent sessions (e.g., 3-4 this week instead of your usual 2)?"

After semester ends: "Schedule looks lighter next week. Maintain your current pace or reduce to 1 session per week?"

Suggestion Notifications

Optional proactive suggestions:

Settings > Notifications > AI Suggestions

AI can notify you:

  • "It's been a week since your last session. Ready to schedule the next one?"
  • "Your tutor has new availability on your preferred days"
  • "Recommended: Book your exam prep sessions now (exam in 3 weeks)"

Frequency: Weekly, bi-weekly, or off

Understanding Suggestion Limitations

AI suggestions are helpful but not perfect:

AI doesn't know:

  • Undisclosed personal preferences
  • Changes to your routine not yet reflected in calendar
  • Subjective factors (energy levels, stress, etc.)
  • External commitments not in calendar

Use AI as a helpful assistant, not absolute authority

Feedback Loop

Help AI improve:

After each session:

  • "This time worked great, suggest similar times"
  • "Too early, prefer afternoon"
  • "Perfect spacing from last session"

AI incorporates feedback immediately

Examples of Great Suggestions

Example 1: Exam Optimization

Context: Student has exam Dec 20, currently Dec 1

AI suggests:

Dec 5 (Tue) 4pm - Chapter 1-3 Review
Dec 8 (Fri) 4pm - Chapter 4-6 Review
Dec 12 (Tue) 4pm - Practice Problems
Dec 15 (Fri) 4pm - Advanced Topics
Dec 18 (Mon) 4pm - Final Review (2 days before exam)

Why it's great:

  • Consistent times (4pm)
  • 3-day spacing
  • Progressive difficulty
  • Final review 2 days before (not day before)

Example 2: Building Consistency

Context: New student, first 3 sessions all different times

AI suggests: "Your first sessions have been at varying times. For building a routine, I recommend picking a consistent day and time. Based on overlapping availability, Tuesday and Thursday at 4pm work well for both of you. Try this for 4 weeks?"

Why it's great:

  • Recognizes need for routine
  • Suggests achievable pattern
  • Time-boxed trial (4 weeks)

Need Help?

  • Adjust preferences: Settings > Scheduling Preferences
  • Disable AI suggestions: Settings > AI Features
  • Report bad suggestions: Help > Feedback
  • Learn more: Optimizing AI Performance