Understanding the Tech Behind AI
When generative AI began reshaping the technology industry, Makenna Mitchell knew she wanted more than a surface-level understanding of the tools everyone was talking about.
Already working as a product manager at Visa, she recognized that the future of product management would require more than business strategy. It would demand technical fluency, a deeper understanding of software development and the ability to collaborate confidently with engineering teams.
"When I started the certificate, ChatGPT had just launched, which further sparked my interest in emerging technologies," she recalls. "I wanted to take additional courses in machine learning, deep learning and Spark so I could develop deeper expertise in technologies that were already being implemented across several Visa products."
This program was an excellent complement to my existing software development experience and helped me take my technical knowledge to the next level.
Building Technical Depth
Makenna came into our program with a strong foundation. She had earned a bachelor's degree in economics and management information systems from Santa Clara University and had already spent a year at Visa supporting products that required "a strong understanding of systems architecture within the payments space," she clarifies.
Still, Makenna felt there were important gaps to fill in her understanding of programming languages and systems fundamentals.
"I could think of no better place to study than UC Berkeley Extension," she enthuses. "The coursework was grounded in real-world industry experience. The instructors brought practical perspectives on how the concepts could be applied across engineering, product management and other business functions."
Rather than simply teaching students how to write software, our instructors helped Makenna understand why technical decisions matter.
"This program was an excellent complement to my existing software development experience and helped me take my technical knowledge to the next level," she says. "Rather than simply understanding how to build something, the certificate helped me better understand why certain approaches, systems and models work better than others.
"While there may be multiple ways to solve a problem,” Makenna continues, “some approaches are more efficient, scalable and maintainable than others."
Those lessons changed how she thinks about building products at enterprise scale.
"I learned that software must be built on a strong technical foundation if it is going to support growth, increasing complexity and long-term scale," she explains.
I gained the technical fluency to lead sprints, collaborate more effectively with engineering teams and move flexibly between business and technical projects as needed.
Bringing AI Into Product Management
As AI capabilities expanded across the payments industry, Makenna found herself uniquely prepared to understand—not just use—the technology.
"My day-to-day work involves a significant amount of data analysis and interpretation, responsibilities that have become even more important with the rapid adoption of AI tools," she offers. "Because of the knowledge I gained through my UC Berkeley Extension classes, I was able to understand more clearly what was happening behind the scenes and adopt many of these tools earlier and more effectively than I otherwise could have."
The technical confidence she developed also expanded her responsibilities at Visa.
"Because I was able to speak more confidently about the technical development of our solutions,” Makenna relates, “I was able to take on projects that extended beyond the business side of product management. I gained the technical fluency to lead sprints, collaborate more effectively with engineering teams and move flexibly between business and technical projects as needed."
Just as importantly, the certificate gave her the confidence to contribute meaningfully to engineering conversations.
"It also gave me the confidence to take on complex engineering problems rather than shy away from them," she adds. "That knowledge allowed me to contribute more confidently to discussions about development approaches, technical tradeoffs and potential solutions."
For Makenna, succeeding in technology isn't about chasing the latest trend; it's about committing to continuous learning.
"My advice to anyone trying to remain relevant in an AI-assisted landscape is to embrace lifelong learning as one of our greatest assets," she says. "That means staying curious about emerging AI tools, understanding how they are being used and considering how they can help modernize outdated systems."
She believes the bigger challenge isn't simply adopting AI, but designing technology and systems “with enough flexibility to anticipate change and make future upgrades more efficient."
Looking ahead, Makenna hopes to eventually launch her own company. But one goal will remain unchanged.
"No matter where my career takes me, I always want to remain a student: continuing to learn, grow and challenge myself," she muses. “UC Berkeley Extension gives working professionals the opportunity to make lifelong learning a meaningful and ongoing part of their careers."
