Sub-agents & Multi-agent systems
Some work is too big or too varied for a single agent. Rival lets multiple agents work together — a pattern often called a multi-agent system. Think of it as the difference between a solo generalist and a small team with a lead.
Orchestrator and specialists
Section titled “Orchestrator and specialists”The common shape is one orchestrator agent that breaks a job into parts and hands each to a specialist agent built for that kind of task. The orchestrator coordinates and assembles the final result; the specialists do the focused work and report back. Each specialist can be simpler, better-tested, and easier to trust than one agent trying to do everything.
Agent-to-agent handoffs
Section titled “Agent-to-agent handoffs”Agents pass work and context to each other along the way. Every handoff is a natural checkpoint — a place to require review, log what happened, or pause for approval. In an enterprise, those checkpoints are where oversight lives.
Escalation patterns
Section titled “Escalation patterns”The most important enterprise pattern is escalation: when an agent hits something outside its confidence or its permissions — an unusual case, a high-value decision, a sensitive action — it escalates to a human, or to an agent with more authority, rather than pushing ahead. You decide where those escalation lines sit, and they’re what let you hand off routine volume while keeping humans on the judgment calls.
A quick example
Section titled “A quick example”An invoice-processing system uses an orchestrator that receives each incoming invoice. It routes data extraction to one specialist, policy-checking to another, and payment setup to a third. Anything under $1,000 that passes all checks is queued automatically; anything above it, or anything that fails a check, escalates to a finance reviewer. One system handles thousands of routine invoices while a person only ever sees the exceptions.
Designing for scale
Section titled “Designing for scale”A few principles keep multi-agent systems reliable as they grow: give each agent a narrow, well-defined job; put human checkpoints at the highest-risk steps; and handle exceptions explicitly rather than hoping they don’t happen.
Related
Section titled “Related”- The single-agent basics → What is a Rival Agent
- Where approvals fit → Approval workflows
- Advanced design → Enterprise deployment playbook