Apoorv Durga

Like every other MarTech domain, AI is shaking up how people think about one of the traditionally most difficult marketing aspirations: personalization. In the first of a two-part series, I’ll review an age-old architectural question for enterprise marketers…Where should personalization live? Should it sit: In a central decisioning layer? Inside channel-specific platforms? In a data platform, such as a customer data platform (CDP)? Somewhere in the content stack? Somewhere else altogether?

Some enterprises that Real Story Group advises are finally moving beyond the pilot stage with Agent AI. They have real setups running in production, or they're getting very close. But the main issue stalling these rollouts is almost always architectural rather than related to the underlying LLM or prompt engineering. After my post on the context layer , the most common question I got was asking where that layer actually sits in the broader stack.

In this fourth post in my series, Observability: Why Did Your Agent Do That?, I look at the AI Agent observability problem. (You can find the three earlier posts here:  Part 1: Autonomy with Brakes: Why Refusal Comes First ,  Part 2: Disobedient or Just Probabilistic , and Part 3: The Importance of the Context Layer.) At Real Story Group, we’ve researched more than twenty Agent AI tools and have advised several enterprise clients on different Agent AI aspects.