Agent & Protocol · Toolkit

Multi-Agent Orchestration Board

SIMULATEDVerified Jul 2, 2026

A supervisor decomposes the goal, agents coordinate, and a result assembles. The meter on the right is the point: multi-agent buys quality — but at a cost and latency multiple you should be able to name.

Authored, deterministic run — the steps and the cost/latency/quality figures are hand-built to teach the tradeoff, not captured from a live model. A real-model variant is on the roadmap.

Same instrument · three industries — pick a use-case to reconfigure the run

Goal · Prep a competitive brief on a new fintech entrant in card disputes.

Supervisor

Idle — press Run

Researcher

idle

Gather the entrant's public product claims, pricing, and integration model.

Analyst

idle

Compare their approach to ours and find the gaps.

Writer

idle

Assemble a one-page brief: the three things leadership must know.

Critic

idle

Red-team the brief for unsupported claims.

A2A-style coordination · task lifecycle: assigned → working → completed

No messages yet.

Assembled result

Run the orchestration to assemble a result.

Multi-agent vs single-agent

Qualitysingle 62 · multi 81

single

multi

Cost / runsingle $0.018 · multi $0.043

single

multi

Latencysingle 4.2s · multi 9.6s

single

multi

The ratio: multi-agent bought +31% quality for 2.4× cost on this task class. That ratio — not the demo — is the decision.

When multi-agent is worth it

Decompose only when the subtasks genuinely differ (research vs critique) and quality matters more than the 2–3× cost. For high-volume, low-stakes calls, a single agent wins. Budget for the harness, not the party trick.

Steering-committee takeaway: Multi-agent bought +31% quality on this task class for 2.4× cost. That ratio, not the demo, is the decision.

How this is built

Orchestration pattern: a supervisor decomposes the goal and delegates to role-specialized agents that coordinate over A2A-style messages with explicit lifecycle states (assigned → working → completed).

The run is authored and deterministic — a scripted supervisor/worker trace with illustrative cost, latency, and quality figures for this task class, not measured from a live model. A real-model variant against claude-sonnet-5 is designed for but not wired today, so the badge stays SIMULATED.

Stack: Next.js (static) + shared design system; client-side.

Limitations: the outputs and the cost/latency/quality figures are authored illustrations of a typical run on this task class, not measured from a live execution. The +31% / 2.4× ratio is representative, not a benchmarked result.