Day 8: Multi-Agent AI Systems

Welcome to Day 8 of Building Agentic AI Applications!

So far, we’ve talked a lot about what makes a single agent act — from tools and RAG to memory and planning.

What if your agentic pipeline needs to:

• Parallelize tasks to speed things up

• Use different agent personas for different parts of a task

• Or break up complexity across specialized units, like in a team

That’s where multi-agent systems come in.

Why Use Multi-Agent Systems?

Sometimes, a single agent just can’t cut it because the problem itself might demand scale, specialization, or parallel thinking.

Let’s take a few examples:

• You're generating a marketing strategy that needs market insights, legal review, and creative suggestions.

• You're building a compliance assistant that needs to extract information, flag risks, and cross-check policies.

• You're automating a sales process where one agent talks to the user, another enriches data, and a third handles follow-ups.

Could you do this with one beefy agent? Maybe.

But when you split it into multiple, specialized agents, you can enable:

• Parallelization…