Multi-Agent Systems

A single agent can accomplish a lot — but true power emerges when multiple specialized agents collaborate. Multi-agent systems (MAS) are the 2026 standard for complex enterprise workflows.

Why Multi-Agent?

A single "super agent" with 50 tools and an endless system prompt quickly becomes unreliable. The solution: specialization through division of labor.

Orchestration Patterns

1. Boss-Worker Pattern

An orchestrator agent distributes tasks to specialized worker agents:

Boss Agent (Orchestrator)
├── Research Agent → Researches information
├── Analysis Agent → Evaluates data
├── Writing Agent → Creates reports
└── QA Agent → Reviews results

Advantage: Clear hierarchy, simple error handling. Disadvantage: Single point of failure at the boss.

2. Pipeline Pattern

Agents work sequentially — one's output is the next's input:

Intake Agent → Processing Agent → Review Agent → Output Agent

Advantage: Easy to debug, clear responsibilities. Disadvantage: No parallelism, bottlenecks possible.

3. Peer-to-Peer Pattern

Agents communicate with each other without central control:

Advantage: Resilient, decentralized. Disadvantage: Hard to control and debug.

Practical Example: Recruiting Pipeline

A real multi-agent system for applicant management:

1. Screening Agent: Reviews incoming applications, extracts key qualifications
2. Matching Agent: Compares qualifications with job profiles, calculates match score
3. Communication Agent: Composes personalized responses (invitation/rejection)
4. Scheduling Agent: Coordinates interview appointments with hiring managers' calendars
5. Analytics Agent: Tracks KPIs (time-to-screen, conversion rate, diversity metrics)

Challenges

Multi-agent systems bring specific challenges:

• Communication overhead: Agents must share context — costing tokens and latency.
• Error propagation: A faulty agent can contaminate downstream agents.
• State management: Who has the current state? Shared memory vs. message passing.
• Testing: Each agent individually AND the interplay must be tested.
• Cost: More agents = more API calls = higher costs.

Practical Tip: Start with the Boss-Worker pattern. It's the easiest to understand, debug, and scale. Use Peer-to-Peer only for advanced use cases.