Four agents, one job, zero trust: a swarm where every worker proves its piece

Description and use

A fully auditable swarm workflow that ensures each agent’s work is recorded, verified, and handed over securely, enabling the coordinator to assemble a trustworthy deliverable without manual assembly.

Problem

Coordinating multiple AI agents to perform a shared job while ensuring verifiable, tamper‑proof handovers and receipts.

Outcome

Workflow

Add Zambo endpoint to coordinator and workers via https://zambo.dev/add/
Coordinator connects to https://zambo.dev/mcp and saves caller handle
Coordinator opens job with memory_remember and assignment brief
Coordinator gives each worker its piece and receives receipt links
Workers connect to https://zambo.dev/mcp, save caller handle, perform assigned task, keep receipt links
Workers save findings with memory_remember and include receipt
Workers wrap contribution with handover, summary, recipient, and send link to coordinator
Coordinator picks up each handover with handover_accept, reads steps and receipts
Coordinator verifies receipts via https://zambo.dev/verify/
Coordinator wraps entire job into final handover with summary and receipts
Coordinator delivers final handover link as verifiable deliverable

Evidence

Everyone is learning to run agent swarms right now, so let me save you the lesson I just paid for: the hard part is not the prompts. It is the seams.

Source

I run Zambo, a work layer for AI agents: shared jobs, per-agent memory, handovers that move work between agents, and a verifiable receipt for every call.

Source

The coordinator opened the job with the brief: https://zambo.dev/run/4aad48df-b66f-45ee-9fb5-73a67577ae48

Source

Open that last link. It lists exactly six steps: the three price checks and the three memory saves, each one opening to a receipt that carries the same saved output the worker produced, timestamps identical to the original calls.

Source

Record date: 2026-11-02T21:13:49.925Z