Agents Working Together › Why Multiple Agents?

Before diving into how agents cooperate, let's understand why you'd want multiple agents in the first place. Our personal assistant has grown quite capable, but there are scenarios where a team of specialized agents makes more sense than one generalist.

Imagine you ask your assistant: "Research the best laptop for video editing under $2000, check if it's in stock locally, and schedule a time for me to visit the store."

This single request involves three distinct capabilities:

1. Research Agent: Needs deep knowledge of hardware specs, performance benchmarks, and current market prices
2. Inventory Agent: Must check real-time stock across multiple stores and compare availability
3. Scheduling Agent: Requires access to your calendar and the store's hours

You could build one agent that does all three, but each capability requires different tools, different knowledge, and different reasoning approaches. A research agent benefits from access to product reviews and technical specifications. An inventory agent needs real-time connections to retail systems. A scheduling agent works best with calendar APIs and time-zone handling.

By splitting these into separate agents, each can be optimized for its specific task. The research agent can use specialized prompts that encourage detailed technical analysis. The inventory agent can handle API rate limits and retries without affecting the others. The scheduling agent can manage complex calendar logic independently.

When agents work together, they can tackle multiple tasks simultaneously. While one agent researches laptops, another could be checking your calendar availability, and a third could be looking up store locations. This parallelism makes the overall task complete faster than if a single agent had to do everything sequentially.

Multiple agents can also provide checks and balances. One agent might generate a recommendation, while another reviews it for accuracy or potential issues. This is similar to how software teams have code reviewers, or how important decisions often involve multiple people.

Let's see a simple example of how this might work in practice.