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Contextual CDPs: Contextual Fluency

Contextual CDPs: Contextual Fluency

Part 6 of 6: Being contextual is also about competence.

Over the last five posts, we’ve moved from speculative to strategic to practical. We’ve looked at how memory, inference, and model context protocols can enhance personalization, orchestration, governance, and architecture in and around the CDP. So, where does that leave us?

Right here.. yes, with the last post in the series, but more importantly, with the people, with YOU!

Because it’s one thing to build a system that can understand context. It’s another thing entirely to make that understanding usable across your organization. That’s what this final piece is about, turning contextual awareness into team

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Letting go of control

Letting go of control

What agentic AI can teach Martech about trust, autonomy, and actual intelligence

I used to think I understood AI agents. In Martech, we talk about them all the time. Tools that take action based on data, automate tasks, score leads, and optimize send times. That’s what we call an agent, right? A helpful script or model that executes a narrow task faster or more accurately than humans can.

Then I had a conversation with Aampe’s CEO Paul Meinshausen on my podcast Couch Confidentials, and something clicked. Paul introduced a distinction I hadn’t fully grasped. An AI agent follows instructions. Agentic AI operates with goals, persistence, and the ability to

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Contextual CDPs: Composable, not chaotic

Contextual CDPs: Composable, not chaotic

Part 5 of 6: Contextual CDPs need lightweight structure, not heavyweight rebuilds

By now, we’ve explored what context can unlock in a CDP, from dynamic profiling to real-time orchestration and trust. We’ve talked about layering memory and inference without blowing up your current stack. So in this fifth part, let’s look at what happens when you want to make these contextual layers stick… without making everything feel like a pile of duct-taped services.

Because that’s the risk. Composability gives us incredible flexibility, but without some architectural discipline, it becomes hard to explain, harder to maintain, and impossible to govern.

Let’s explore how to structure context-aware systems in

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If the warehouse can think, what’s left for the CDP?

If the warehouse can think, what’s left for the CDP?

A critical reflection on Databricks, data gravity, and what comes next.

Nope, this isn’t an analysis of a press release. We’ve seen all Databricks partners do that generously all over LinkedIn. It’s a reflection, a personal one (I had some spare time over the weekend), on something that’s been building quietly in the background and what it means now that someone has taken a concrete step forward. That someone is Databricks.

Last week, Databricks launched something called Data Intelligence for Marketing. And sure, you could skim the headline and file it under “AI feature drop.” But that’s not what caught my attention.

What stood out was

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Contextual CDPs: Building the bridge

Contextual CDPs: Building the bridge

Part 4 of 6: What connects today's CDPs to tomorrow’s agent-driven context

If the first three parts of this series explored what’s possible when context becomes the driving force behind customer data, then this one asks a more grounded question:

How do we actually get there?

I’ve spoken with teams who are genuinely excited by the idea of using memory, inference, and context to make their CDPs smarter. But many feel stuck between inspiration and implementation. They see the potential, but don’t quite know where to start.

Let’s be honest, the martech stack is already complex enough. The last thing anyone wants is to bolt on a new

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Contextual CDPs: Trust as a feature

Contextual CDPs: Trust as a feature

Part 3 of 6: Why identity graphs can’t create relationships, and how context might.

In Part 1, I looked at how model context protocols could reshape the customer profile, from static to dynamic, from collected to interpreted. In Part 2, I spoke about how that same shift could drive smarter, more human orchestration across channels and touchpoints.

But there’s a deeper layer we need to talk about. Not tech. Not tactics. Trust.

Because when our systems start inferring, remembering, and deciding → the stakes change. And our responsibilities as builders shift right along with them.

Dynamic Context == Dynamic Responsibility

With great memory comes great obligation.

Sorry, Uncle Ben.

When we move from static profiles

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