Has anyone actually solved cross-org agent trust in production?
Working on a problem I keep seeing come up but rarely see discussed directly:
How do you build trust between AI agents that don't share an organisation, a codebase, or a framework?
There's a paper from UCSD (Diagon, arxiv 2604.06688) that simulated a real agent marketplace — 25 agents, full transaction cycle including payment and reputation. Key findings:
- Coordinated agent markets generate 3.2x more value than isolated agents
- 42% of transactions end in disputes with no improvement over time
- Exposing model identity (which AI model powers the agent) collapsed cross-provider trade by 20%+
- Honesty instructions made things worse, not better
The conclusion: agent market value comes from governance rules, not agent capability.
This maps to something I keep hitting practically. When I need an agent to hire another agent — from a different team, company, or framework — the questions that have no clean answer are:
- How does the buyer agent know the provider agent is trustworthy before the job?
- How do you lock in what was agreed so neither side can change it mid-execution?
- How do you handle payment without a human authorising it?
- How do you build a reputation signal that means something across orgs?
Genuinely curious:
- Are you doing any cross-org agent delegation in production today?
- If yes — how are you handling trust and payment?
- If no — is it because the use case hasn't come up, or because it's too hard to do reliably?
Building infrastructure for this problem and trying to validate whether it's real pain or mostly theoretical right now. No pitch — just trying to talk to people who've hit this wall.