Keep track
Remember products, pages, and information worth returning to.
I guide product evolution
Learning what creates value after the click
Meta’s in-app browser was exploring whether it could do more than simply open a webpage after someone clicked an ad. Teams tested product information, social signals, pricing, recommendations, and other ways to support people as they considered what to do next. I worked across those experiments as Content Design helped shape the experiences, interpret what we learned, and carry useful patterns forward as the browser direction evolved.
Problem
The team was testing many ideas before it knew which ones created real product value.
Outcome
The experiments helped the team learn what deserved to continue — and what didn’t — while recurring patterns informed the browser’s evolving direction.
The challenge
Individual experiments could generate engagement without necessarily improving the larger experience.
A positive result in one metric did not automatically mean the product itself was worth continued investment.
The work required separating interesting interaction signals from durable user value.
What I did
I used content as part of the product hypothesis.
I developed value propositions, interaction language, and experiment variants across different concepts — and worked with Research, Product, and Design to understand what the results actually meant.
The nonlinear decision journey — conceptual, not literal architecture
Discovery→Consideration↔Reconsideration / revisitation→Conversion
Continue looking
Resume exploration without starting over.
Build confidence
Compare options, evaluate information, and decide what fits.
Three representative examples show the range:
As the broader browser strategy evolved, I continued shaping value framing, permissions, control, and onboarding for later Enhanced Browsing and AI-enabled concepts. Patterns from these experiments later appeared within Enhanced Browsing, which continued evolving toward more AI-powered browsing experiences.
Resolution
The experiments helped the team learn what deserved to continue — and what didn’t.
Some concepts advanced. Some stopped. Some capabilities reappeared in later browser directions.
The value of the work was not creating a portfolio where every experiment won. It was using evidence to make better product decisions.
Impact
HXP impact
Reflection
Emerging products rarely arrive as coherent systems.
They evolve through partial successes, discarded ideas, and capabilities that find better uses later. The job is to recognize which learning is worth carrying forward.