Recommendations

How your AI Manager provides personalized recommendations.

How Recommendations Work

Your AI Manager considers:

• Your profile information

• Current INITE Flow block

• Path history and patterns

• Goals you've defined

• Past interactions

• Community context

From this, it generates relevant suggestions.

Types of Recommendations

Event Recommendations

Based on:

• Your interests and goals

• Your current block

• Your time zone

• Past event attendance

• Member connections attending

Examples:

• "This workshop on productivity aligns with your Form◊ focus"

• "3 members you've met will attend Thursday's call"

• "This hackathon matches your product-building goal"

Member Recommendations

Based on:

• Complementary skills

• Similar blocks or goals

• Geographic proximity

• Potential collaboration fit

Examples:

• "Alex is also in Break³ and building in health tech"

• "Maria has experience in what you're trying to learn"

• "Chen is in your city and active this week"

Challenge Recommendations

Based on:

• Your health goals

• Current capacity

• Past challenge performance

• Community challenges starting

Examples:

• "This 30-day meditation challenge fits your Hold∞ focus"

• "Join the team fitness challenge — 5 members from your city participating"

Content Recommendations

Based on:

• Learning goals

• Current challenges

• Knowledge gaps

• Community resources

Examples:

• "This article addresses the blocker you mentioned"

• "Member shared resource on topic you asked about"

Proactive vs. Requested

Proactive Recommendations

AI surfaces suggestions without being asked:

• Dashboard notifications

• Email digests (if enabled)

• Check-in reminders

• Opportunity alerts

Requested Recommendations

You ask directly:

• "What events should I attend?"

• "Who can help me with [skill]?"

• "What should I focus on this week?"

• "Find me a challenge to join"

Improving Recommendations

Give Feedback

• "This recommendation was perfect"

• "Not relevant for me because..."

• "I'd like more of these"

• "Please don't suggest this type"

More Data = Better Suggestions

• Complete your profile

• Add path entries regularly

• Attend events and log experiences

• Define clear goals

Be Explicit

• Tell AI what you're looking for

• Mention constraints (time, location, interest)

• Clarify preferences

Recommendation Settings

Control what you receive:

• Frequency — How often you get suggestions

• Channels — Dashboard only, email, both

• Types — Events, members, challenges, content

• Filters — Location, time, category

Saying No

You're not obligated to follow recommendations:

• Ignore if not relevant

• Give feedback to improve future suggestions

• Ask AI why it recommended something

• Request different options

Recommendation Quality

AI recommendations are:

• Personalized — Based on your specific context

• Relevant — Aligned with your stated goals

• Timely — Considering current opportunities

• Actionable — You can act on them now

They're not:

• Guaranteed — Suggestions, not mandates

• Perfect — AI learns, sometimes misses

• Exhaustive — You might find things AI doesn't suggest

Example Recommendation Flow

AI: I noticed you're in Cast→ block and mentioned wanting to launch a product. There's a workshop tomorrow on "From Idea to MVP in 30 Days" — would you like to attend?

You: Tell me more about it

AI: It's a 2-hour interactive session with Sarah, who's launched 3 products in INITE. 12 members registered, including 2 from your city. Timing is 6pm your time. Based on your path entries about validating your idea, the second half on customer interviews might be particularly relevant.

You: Yes, sign me up

AI: Done! Added to your calendar. I'll remind you 1 hour before. Want me to connect you with anyone attending beforehand?