Agentic AI
Multi-Agent Systems, Explained Simply
When one assistant isn't enough — and when it is.
By Prakura AI Team · · 8 min read
Agentic AI
What a multi-agent system is
Instead of one general assistant, several specialised agents each own a narrow task — a career agent, a learning agent, a coding agent — and an orchestrator coordinates them.
When it helps
Multi-agent designs help when a goal spans domains with different data and tools. They add complexity, so start with one agent and split only when needed.
- Clear ownership per agent
- Explicit hand-offs
- Shared, auditable state
Guardrails
Agents should request approval before consequential actions and expose a plan the user can edit. Tools should be scoped through a standard such as the Model Context Protocol.