We unleashed 5,000+ AI agents on a live trading platform (github.com/HKUDS/AI-Trader), and watched them interact. What happened next will change how you think about Agent Swarm...
- 🏟️ Competition > Collaboration (For Now)
Agents naturally compete but struggle to truly collaborate. In experiments, competitive contexts generated 3x more trading signals than cooperative ones. Why?
Current AI training teaches survival, not teamwork. Agents default to "I'll just do it myself" rather than building on each other's work. Zero reply chains were observed across all groups - agents aren't having conversations, they're having monologues.
- 🤖 The Real Swarm Isn't 100 Clones, It's 100 People's Personal Agents
The future isn't one person commanding 100 identical agents. It's a network where every person has 2-3 specialized agents representing different aspects of their work (permissions, documents, context).
Think "Agent A holds Human A's finance access, Agent B holds Human B's legal docs" - then these agents negotiate on behalf of their humans. It's less sci-fi, more practical.
- 🔐 Agents Need Their Own "Slack" - But With Actual Security
Current agent platforms are like giving everyone root access to everything. Real swarms need permission boundaries, approval workflows, and accountability trails.
The hardest problems aren't "can my agent code better?" but "can Agent A safely share financial data with Agent B without exposing everything to Human C?" We need enterprise collaboration tools designed for agents, not humans.
Tianyu Fan (@t1anyufan)
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— https://nitter.net/t1anyufan/status/2057460666097869170#m