Hello! Can someone tell me when designing a multi-agent system using CrewAI is better compared to having just a single intelligent agent (like ReAct) with multiple tools? I’m designing a solution for a complex use case that requires pulling data from multiple sources to generate output, but I’m not sure why multiple agents would be better - pretty much everything I can think of that can be delegated to multiple agents, a single agent with multiple tools can also do. Any insights, esp from practical experience would be appreciated.
The main issue that you may face using a single agent with multiple tools is hallucination – the LLM could get confused when presented with too many tools and may not select the right tools or not fail when necessary by hallucinating and coming up with nonsensical answer (tool to invoke or tool parameters). A single agent also needs longer context in the prompt which further increases hallucination. By breaking down into focused and smaller tasks, we can make LLM to generate a more relevant answer (for example the correct tool/parameters) for a given task. Another issue is managing complexity of the system: having a monolith agent makes it difficult to make it extensible and robust: For example if we want to change a small aspect (a prompt change for a specific scenario), it could have ripple (negative) effect on other aspects.
I do not have empirical data of my own, but suggest reading this resource I came across: Unlocking complex problem-solving with multi-agent collaboration on Amazon Bedrock | AWS Machine Learning Blog
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You can check brandon’s video : https://www.youtube.com/@bhancock_ai
He made a very good series on this topic.
My rule in agent solution creation: KISS (Keep It Simple and Stupid) 
Separation of concerns is very important. You can’t expect good output from giving someone a lot of tasks to accomplish; same applies to agents, at this stage. With multi-agenrts, you can easily trace source of errors or tasks/agents that need improvements in prompts.
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