Day 4: What Is RAG, and What Does It Mean to Make It Agentic?

Welcome to Day 4 of Building Agentic AI Applications!

Missed previous days’ posts? Find them here

Yesterday, we looked at how tools help AI agents interact with real-world systems — send emails, file tickets, trigger APIs.

But what if the model doesn’t need to act? What if it just needs access to the right information?

That’s the case in many enterprise settings:

• Internal docs spread across teams

• Policy PDFs no one remembers writing

• Customer insights buried in CRM notes

• Dashboards and emails with useful context

Tools won’t help here. The model needs to think with your data.
That’s where RAG comes in.