In Part 1, I explored how model context protocols (MCPs) could shift CDPs from passive data stores into dynamic context engines. Profiles that update themselves in the moment, based on intent, tone, and history. Not just segments, but signals. And now? Let’s see what happens when those signals actually drive decisions… in real time, across multiple touchpoints.

Because here’s the next big unlock: context-aware orchestration.

Real-time isn’t just about speed

Let’s be honest, "real-time" has been one of those buzziest of buzzwords we’ve collectively abused for years. It often means “fast batch,

There’s been a lot of noise lately about context windows, model memory, RAG systems, and how all these emerging AI patterns might play out across industries. And if you’re working in customer data or Martech, you’ve probably felt a mix of curiosity and overwhelm. I know I have.

So let’s slow it down for a moment and approach this from a different angle. I’m not an MCP expert, far from it. This series is more about curiosity than conclusions. It’s a way for me to explore how these ideas could apply to CDPs and