Is multi-agent orchestration the same thing as a chatbot that uses plugins?

Not necessarily. Plugins are usually extensions to one model inside one conversation. Multi-agent orchestration consists of multiple separate agents, which could have a separate memory and decision-making processes.

Do I need to use different AI models for multi-agent orchestration, or is it possible to use one model to play different agent roles?

Both options are fine. Many applications use the same base model but prompt it with different prompts, tools and permissions to play different "roles," while some applications use different models that are better at different things. Eg., coding vs. writing.

Can multi-agent orchestration be only used by large companies?

Not necessarily. Even small groups of people working on content automation, research or customer support will be able to use this method with just a few agents.

What is the primary risk associated with multi-agent systems?

It's compounding errors; when one of your agents makes a mistake, other agents further down the line will take advantage of it. This means that verification procedures should be very tight.

Start with a single workflow first and don't try to automate an entire department. Bring agents onboard one by one and spend some time setting up logging so you can monitor the agents and their actions closely.

From Prompting to Multi-Agent AI Orchestration

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