Multi-agent systems + Voice agents and agent interoperability (awareness)
Comes up in: AI engineering, AI system design
This concept is being written. It gets the full five steps — explanation, predict, interview angle, practice with tests, and review cards. Here is exactly what it will cover, so you can study it elsewhere in the meantime.
What it covers
- orchestrator + sub-agents
- parallel research
- handoffs
- shared vs isolated context
- costs (token multiplication) and failure modes
- when a single agent is better (cite Anthropic multi-agent research post, 2025)
- realtime voice pipelines (speech-to-text → LLM → text-to-speech vs speech-to-speech models)
- latency budgets and turn-taking
- interruptions
- agent-to-agent protocols such as A2A (status, facts) vs MCP
Words you will know
What you will practise
- orchestrator with 2 research sub-agents
- compare cost and quality
- latency budget for a voice support agent
Interview questions this answers
- When is a multi-agent architecture worth it?
- What are the failure modes of multi-agent systems?