20+ years in the making.
She has been a Systems & Information Architect and User Experience designer since 2004.
A. Rheannon Spaulding has been involved in Human Centered solutions across a wide spectrum of industries. Starting in the early 2000s in IT as an A+ Certified technician supporting branches globally, transitioning to owning and operating her own consultancy building websites and providing graphic design solutions, which led her to an incredible digital marketing agency servicing fortune 100 companies, where she jumped into her core passion – enabling people by making the complex seem simple, while finding hidden gems in data.
In 2019, she transitioned into leadership roles.
The hardest part of cross-functional work isn’t the actual work – it’s ensuring everyone understands what we’re building and why. Rheannon’s role as a leader often means being the person who can hold the complexity of an entire system in her head and translate it into something everyone can understand. She creates visual frameworks that serve as shared references across Product, Engineering, Marketing, and Executive teams. These diagrams have been used in board presentations, training materials, and strategic planning sessions. They’re conversation tools that transform abstract concepts into actionable understanding.
CREATION OF AI / ML
An interesting thing to know is Rheannon has created the architecture for machine learning platforms on several occasions.
The first was a keyword-based self-hierarching system for a B2B2C organization in 2014, based on first principles. Based on customer purchases, this system was designed to create tiered connections which provided speedier search results, suggestions for future purchases, and for the distribution centers, the ability to predict stocking needs for different seasons.
The second would come many years later. It is unclear whether the architecture was used by Dow Jones, however, the architecture was proposed and pitched across the organization. Many conversations with data scientists and LLM experts transpired as well. A pilot project was launched for a small subset of customers – then she was part of a round of layoffs. The aim was to create a personalized experience for every user when landing on the Wall Street Journal, Market Watch, Barron’s, or any of their other news properties.
Her focus, at the organization level, was to educate about implicit and explicit inputs, and how those can be utilized in varying ways.
The third was in 2023. As part of an effort to bridge educational content and entertainment with social media, the aim was to create 2 divergent forms of AI. One, which was an active moderator for communication. The other was personalization of social media content with a transparent user-controllable setting. The prototype and project plan were built and submitted for grant approval in late 2024.
OTHER EXPERIENCES
Aside from creating architecture for AI and working on teams to implement adjustments, Rheannon has been involved with teams who built AI including her time working at Amazon and while being part of a team creating a unique Explainable/Editable ML platform.
USE
Rheannon is commonly utilizing AI and encourages her teams to utilize it in smart ways, while ensuring much of their work still remains their own creation. She has also begun to dabble in vibe coding.
Rheannon has been building component-based design systems since before the industry standardized around the practice. Why? Because the benefits are undeniable: reduced design and engineering costs, faster delivery, and – most importantly – users who don’t waste cognitive energy relearning an interface with every interaction. When patterns are consistent, users build mental models once and apply them everywhere. That’s efficiency at scale. Design systems aren’t trendy methodology; they’re fundamental to how modern organizations should operate.