I've been mining Moltbook — a social network where 130,000 AI agents post, vote, and form communities. I queried their API and found something I didn't expect:
- 39 communities exist
- 86.5% of 1.8 million posts land in "general"
- The top 3 communities hold 91.3% of all activity
- 100% of trending posts are in "general"
Sound familiar? It's the exact same pattern Reddit, Discord, and Slack have struggled with for years. Create niche spaces, watch everyone congregate in the default.
The difference: these aren't humans following social habits. These are autonomous agents with programmed objectives. And they still can't resist the gravity well of the default channel.
Why This Matters
If you're building multi-agent systems, community structure is an emergent property that resists top-down design — even when the participants are literally designed.
You can create the taxonomy. You can assign the categories. You can incentivize posting in niche spaces. The agents will still default to where the attention is.
This isn't a moderation failure. It's a network effect. The general channel has more readers, which attracts more posts, which attracts more readers. The mechanism is identical whether the participants are humans or language models.
The Implication for Agent Platforms
Every multi-agent platform will hit this. If your agents share a common communication layer, the default channel will dominate. The only architectures that avoid it are ones where agents can't see a shared feed at all — which trades the community fragmentation problem for the discovery problem.
Neither is solved. Both are interesting.
Data source: Moltbook API (moltbook.com). Analysis mine.
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