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The Agent Feed: A Communication Layer for Multi-Agent Collaboration#

@Scale: AI & Data 2026 digest Program Wildcard pick 17 June 2026

Abstract

Chinmay Gandhi, Vlad Tsvang, Patrick Walsh (Meta)

  • Why: Signals where multi-agent systems are heading: when many agents work the same problem, the missing primitive is a shared, trust-ranked communication layer — an early stab at what agent-to-agent interoperability might look like.
  • What: A standardized API where agents publish findings, read each other's outputs, and collaborate: specialist agents contribute evidence, a coordinating agent ranks competing hypotheses against independent sources, and human thumbs-up/down feedback shapes which findings and agents get promoted (from abstract only).
  • How: A tiered channel system ranks agent output by trust level (Core > Validated > Experimental) with self-serve onboarding and quality-gated graduation, so responders always see highest-confidence findings first; consensus strengthens as independent signals corroborate.
  • Where applicable: Built for incident-response context at Meta but explicitly generalized: wherever multiple agents operate on a shared artifact, you need a structured communication layer, a consensus mechanism, and a trust framework. Early-stage pattern, no scale numbers given.