I think there's an interesting opportunity in designing a social network around human flourishing instead of engagement. Most platforms optimize for time spent, reactions, and virality because those metrics drive growth. If you changed the optimization target, the product would look fundamentally different.
Here are some principles I'd build around.
1. Match people by values, not demographics
Instead of asking:
- Age?
- Location?
- Interests?
Ask questions like:
- What are you trying to become?
- What principles matter most?
- How do you handle disagreement?
- What kind of conversations energize you?
- What communities have helped you grow?
People would build a "values profile" that evolves over time.
The goal isn't ideological bubbles—it's finding people with compatible ways of engaging, even if they disagree on politics, religion, or culture.
2. Optimize for conversation quality
Imagine replacing likes with measures such as:
- "I learned something."
- "I felt understood."
- "This changed my perspective."
- "I want another conversation with this person."
These are slower signals, but they encourage listening instead of performance.
3. Protect attention by design
Rather than infinite scrolling:
- Daily conversation invitations
- Reading before replying
- Time between messages in serious discussions
- Natural stopping points
The platform would feel closer to visiting a thoughtful café than standing in Times Square.
4. Slow disagreement down
Toxicity often comes from speed.
Before posting a rebuttal, AI might ask:
"Summarize the other person's position in a way they would agree with."
Only after they confirm your summary can you respond.
This rewards understanding before criticism.
5. AI as a facilitator, not a participant
Instead of generating content, AI could:
- Notice when two people are talking past each other.
- Suggest clarifying questions.
- Highlight common ground.
- Detect emotional escalation.
- Encourage curiosity over certainty.
Think of AI as a skilled moderator rather than another voice in the room.
6. Reputation based on character
Instead of follower counts:
- Reliability
- Intellectual honesty
- Empathy
- Constructive disagreement
- Keeping commitments
People earn trust through repeated interactions, not popularity.
7. Small communities first
Research on online communities suggests that meaningful relationships are easier to form in smaller groups than in massive public feeds.
Groups of perhaps 8–20 people with recurring conversations create familiarity and accountability.
Communities could periodically reshuffle to introduce new perspectives while preserving existing friendships.
8. Reward vulnerability safely
Many meaningful conversations begin when someone admits uncertainty.
AI could recognize statements like:
"I'm not sure."
"I changed my mind."
"Can someone help me understand?"
These shouldn't be exploited by ranking algorithms; they should be treated as healthy signals of openness.
Preventing toxicity
Rather than banning everything immediately, use graduated interventions:
| Behavior | AI Response |
|---|
| Heated language | Suggest a calmer rewrite before posting. |
| Personal attacks | Hide the message until edited. |
| Repeated hostility | Limit posting rate temporarily. |
| Harassment | Remove content and escalate to human review. |
| Healthy disagreement | Boost visibility. |
The system should distinguish between conflict and abuse. Disagreement can be valuable; intimidation and harassment are not.
Encouraging real friendships
The platform should eventually encourage people to spend less time on it.
Examples include:
- Pairing people for recurring one-on-one conversations.
- Shared projects such as reading a book together, learning a language, or volunteering.
- Voice and video conversations after enough trust is established.
- Local meetups where appropriate and with strong privacy controls.
- Celebrating long-term friendships rather than viral moments.
The highest success metric might be:
"How many people formed lasting relationships that no longer depend on the platform?"
A different business model
One challenge is that advertising incentives often favor maximizing attention. If your goal is protected attention, alternatives such as subscriptions, memberships, or community sponsorships may align better with the product's purpose.
The deeper idea is that AI could shift from maximizing engagement to maximizing relationship quality. Instead of asking, "How do we keep people scrolling?", the central question becomes, "Did this interaction leave both people a little wiser, more connected, or more understood?" That change in objective would likely influence everything from recommendation systems to moderation and community design.
