DATA-INFORMED ENABLEMENT

Once production became predictable, the next question was: what should we build next?

I proposed a Use Case Library as a cross-department initiative with the Product team.

The goal was to decrease time-to-value for OpenAEV adopters. We had a library of deployable scenarios, but users still struggled to understand how to use them to test their security tools.

I had to work closely with Product to ensure accuracy, scope, and alignment with roadmap direction. The Use Case Library is not just Academy content. It sits at the intersection of product design, enablement, and customer adoption.

OpenAEV Use Case Library - Pilot (H1 2026)

Validate Detection of Suspicious PowerShell Download Cradle Activity

CUSTOMER ENABLE PRIORITIZATION AGENT

Now I was producing or co-producing 3 types of content: Certification Courses, Mini Course, and Use Cases. The Academy still relied on internal perception to guide priorities, instead of a consistent way to tie content decisions to real customer friction. At the same time, AI adoption was becoming a company-wide priority. Rather than treating AI as a marketing concept, I used it to solve a practical problem. I built a content prioritization agent that analyzes support tickets and customer signals. It clusters recurring questions, ranks themes by frequency, and evaluates their impact on adoption and urgency. Instead of asking, “What feels important?” we could ask, “What is showing up repeatedly in customer behavior?”

The agent produces a ranked view of friction themes and recommends the most appropriate response format. Data-informed enablement shifted the Academy from producing more material to solving clearer problems. It introduced a visible link between customer friction, content investment, and product understanding.

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