Cara North

How do you turn scattered learning resources into a capability ecosystem? Bring them together around the moments product professionals actually need support.

Problem

Product managers were navigating a fragmented learning ecosystem spread across multiple locations, while the existing hub was built on a rigid internal template that was difficult to update and visually indistinguishable from countless other internal pages.

The risk was obvious: even if the content was valuable, the experience made it harder to find, harder to navigate, and easier to ignore.

How did I know it mattered?

The friction showed up in how people had to interact with the learning ecosystem. Resources were scattered, discovery depended on already knowing where to look, and the existing site structure wasn’t flexible enough to support a growing product-learning experience.

I also knew that simply migrating the content into another standard template would solve the technology problem without solving the experience problem.

That mattered because the Hub needed to become more than a place where content lived. It needed to become a destination people could actually use before, during, and after formal learning.

As adoption grew, the signal became even stronger: nearly half of enrolled learners were interacting with the Hub, more than one-third were accessing it before training, and repeat visits suggested learners were returning because they were finding ongoing value.

What did I personally do?

I used an internal AI GPT as a coding partner to build bespoke front-end code from scratch inside the internal pages platform.

Instead of accepting the default template, I used AI to help me:

generate and refine custom HTML/CSS
prototype layouts rapidly
troubleshoot code
iterate on visual hierarchy
create reusable components
work around platform constraints
improve the overall user experience

I combined that AI-assisted development work with my own decisions around information architecture, content hierarchy, navigation, and learner flow.

The important part was that I knew what experience I wanted to create, what the template was failing to do, how to direct the AI toward a better solution, and how to evaluate and refine what it produced.

That transformed the Hub from another templated internal page into a more intentional, branded, and usable learning experience.

What happened?

The Hub became a centralized destination for learning opportunities, resources, and supporting content, with a significantly more usable and visually coherent experience than the standard platform template allowed.

Learners began using it not just as a one-time entry point, but as a place they returned to for continued support.

Nearly half of enrolled learners were engaging with the Hub, more than one-third were accessing it before training, and repeat visits indicated that people were coming back for additional resources and development opportunities.

Importantly, that adoption happened even before the Hub was consistently embedded across all training materials and learning journeys, suggesting meaningful room for continued growth.

What was different because I was there?

I challenged the assumption that the internal template was the experience we had to accept.

I used AI to expand what was technically possible inside the platform, then paired that capability with learning strategy, UX thinking, and product judgment to create something more useful.

Without that intervention, the Hub could have become another functional but forgettable internal repository.

AI made the custom code possible. I made the experience worth using.