In this episode from the archives, we’re joined by Vera Cubero, the Emerging Technologies Consultant for the North Carolina Department of Public Instruction (NCDPI) and a co-author of one of the nation's first K-12 AI guidelines. Vera shares her frontline experience transitioning from a classroom teacher piloting 1-to-1 Chromebooks to leading a statewide AI initiative. This conversation is a crucial exploration of how education must fundamentally change its approach—moving beyond simple tech "substitution" to truly "redefine" learning, assessment, and the role of the teacher to prepare all students for an AI-driven future.

• Beyond the Digital Worksheet: Vera warns that AI in education risks repeating the failures of 1-to-1 Chromebook adoption, where "substitution" (digital worksheets) won out over true learning "redefinition."

• The AI-Enabled Project: The future of learning isn't just using AI; it's pairing AI with Project-Based Learning (PBL). AI becomes a powerful tool for students to solve complex, real-world problems, moving assessment away from simple essays.

• Durable Skills Over Rote Answers: Vera argues that AI makes rote memorization obsolete. The new curriculum must focus on building "durable skills" like critical thinking, collaboration, and creativity—skills the future workforce demands.

• The Guide on the Side: AI doesn't replace teachers; it changes their role. The focus must shift from the "sage on the stage" (delivering content) to the "guide on the side" (coaching, fostering human connection, and guiding student inquiry).

• AI as the Great Equalizer: Vera's biggest concern is equity. Public schools must act as the "great equalizer," ensuring all students—especially from marginalized communities—gain AI fluency, or the economic divide will widen dramatically.

In this episode, we’re joined by Kris Younger, a longtime technologist and the Director of Education at Zip Code Wilmington, a nonprofit coding bootcamp. Zip Code is on the absolute frontier of technology, helping adults from diverse backgrounds, who often earn between $30,000 and $35,000 per year, rapidly transition into tech careers with salaries in the mid-eighties, all in just 12 intense weeks.

Kris shares his unique perspective on how the role of the software developer is fundamentally changing, shifting from a "coder" to a "programmer" who is more like a business analyst and a director. This conversation is an urgent exploration of how to make education nimble enough to prepare students for the future of work, not the past.

• The Age of Steam Programming: Kris likens the arrival of generative AI to the shift from sailing ships to steam engines, the fundamental skills needed to build software have changed forever.

• From Coding to Management: Traditional computer science knowledge of search routines and algorithms is being taken over by LLMs. The crucial human skills are now critical thinking, communication, and management of the AI tools.

• Projects are the New Exam: In a world where LLMs can generate code, the only effective way to assess knowledge is through project-based work that demands group collaboration and real-world delivery (like building a Slack clone in a week).

• Weaponize AI in Response: Instead of trying to ban AI, educators must change the assignment. AI is now a power tool; the education challenge is to teach people how to think critically enough to manage that tool effectively.

• The On-Ramp Problem: Kris's biggest concern is that businesses, confused about the future, will cut off entry-level hiring, denying themselves the adaptable, open-minded new talent who haven't yet learned "what's impossible."

In this episode, we’re visiting Duke University to meet Vihaan Nama, an AI engineer, researcher, and teaching assistant helping shape how AI is taught and built for the real world. From roles at PS&S and JPMorgan to graduate courses on explainable AI and product management, Vihaan brings a rare combination of technical depth and educator insight.

If you’ve ever wondered how to make AI education more human, or how to turn student learning data into actionable insight, personalized support, or even a study partner, Vihaan offers both clarity and concrete examples.

We talk about everything from his early experiments in sentiment analysis to why open-source models matter for student privacy, how retrieval-augmented generation (RAG) is quietly transforming knowledge work, and what schools can do right now to prepare for custom AI tools of their own.

• Your Notes, Your Assistant: Vihaan envisions a future where students can chat with their own lecture notes, using LLMs to review, revise, and apply information in their own language and context.

• From Archive to Advantage: Companies (and schools!) are sitting on decades of underused data. With the right AI systems, that information becomes actionable knowledge.

• Trust Through Transparency: Grounding AI outputs in clear, credible sources is key to building trust, especially in high-stakes environments like education and public services.

• Small Models, Big Wins: As open-source LLMs become lighter and faster, even modestly funded schools can host private AI tools, no cloud dependency required.

• Responsible AI = Responsive Leadership: From sustainability audits to ethical guardrails, Vihaan emphasizes that building AI responsibly starts with knowing what your organization values most.

In this episode, we're joined by Brian Jefferson, a professor at the University of Maryland's Robert H. Smith School of Business. Brian shares his incredible journey from a 20-year career as a partner at PricewaterhouseCoopers to becoming a recognized innovator in higher education.

Listen in as we discuss how to move beyond AI anxiety by fostering "awe and whimsy," why the goal should be "cognitive enhancement" rather than simple automation, and the unique challenges of preparing students for a workforce where their first job might be to audit an AI output. Brian offers practical advice for any educator curious about AI, shares his "aha" moment using AI to practice for high-stakes conversations, and provides a hopeful vision for the future of professional education.

• Cognitive Enhancement Over Automation: Brian's core philosophy is that AI's greatest potential lies not in replacing tasks, but in acting as a partner to augment our own thinking, practice skills, and deepen critical judgment.

• Play as an Antidote to Fear: The conversation highlights how low-stakes, creative exercises, like building a "family vacation GPT" or designing posters with DALL-E, can dissolve anxiety and build confidence for both students and educators new to AI.

• Co-Creation Builds Ownership: Brian’s strategy of co-creating a custom classroom GPT with his students demonstrates how involving learners in the design process fosters responsibility, engagement, and a more sophisticated understanding of the technology.

• Preparing Students for a New Reality of Work: As AI handles more foundational tasks, the essential human skill becomes the ability to critically review and audit AI's output. The discussion emphasizes the need to shift education to build this "auditor mindset."

• AI as the Ultimate Practice Partner: From rehearsing lectures on a commute to preparing for difficult conversations, Brian shows how AI can be used as a private, infinitely patient simulator for improving high-stakes human skills.

Listen in as we discuss how to move beyond basic AI tools and design award-winning VR projects, the unique opportunities and constraints of teaching in a rural district, and how to address equity and cultural responsiveness when bringing new technology into underserved communities. McKenna offers practical advice for educators who are new to AI, shares her "aha" moments with immersive technology, and provides a hopeful vision for the future of STEM education.

• Technology as a Bridge, Not a Replacement: McKenna's work demonstrates how VR and AI can be used to extend learning opportunities and immerse students in their subjects, from walking through ancient Rome to preserving Indigenous cultures.

• Rural Schools as Innovation Hubs: While rural districts face budget constraints, they also offer unique advantages, such as strong community ties and the ability to be nimble and innovative.

• Student Authorship in the Age of AI: The conversation emphasizes the importance of teaching students to use AI ethically and responsibly, with a focus on tools that support student authorship and critical thinking.

• The Human Element is Irreplaceable: When working with Indigenous and underrepresented communities, it's crucial to remember that AI is a tool and cannot replace the lived experiences and cultural knowledge of the people themselves.

• Support for Educators is Key: As technology evolves, so does the need for professional development. McKenna highlights the importance of resources like the Frontier Learning Lab and the AI Help Desk to support teachers in their journey with new technologies.

With a background that uniquely blends practical classroom experience with state-level policy work, Mike offers a realistic and hopeful roadmap for integrating AI thoughtfully. In this practical conversation, we discuss how he uses AI as an "idea bouncer" to reclaim time for students, his strategies for teaching AI ethics, and why the future of education depends on preparing both teachers and students for a world of constant change.

Highlights:

• The journey from swim coach to one of North Carolina’s leading voices on AI in education

• How to use AI as an "idea bouncer" to reduce lesson-planning stress and burnout

• Practical classroom examples: teaching AI ethics with self-driving cars and building chatbots with students

• Why "knowing your students" is a more effective AI detector than any software

• The big question keeping him up at night: What will school look like for his own children in just a few years

Susan C. McLeod, VP of Data Center Market Development at Hitachi Energy, joins us to explore how large organizations can successfully navigate AI adoption. Drawing from over 20 years in enterprise tech, Susan offers practical insights for turning complex technology into a wins for people on the ground.

With a background leading global support and success at Hitachi Vantara, Susan now works at the critical intersection of AI, data centers, and the energy sector. In this practical conversation, we discuss why most AI pilots fail, how to truly prepare your data and teams for new tools, and why communication is the most vital skill for a future shaped by automation.

Susan's insights challenge us to look beyond the hype, preserve the invaluable human knowledge within our organizations, and champion the critical thinking skills that will define the next generation of leaders.

Highlights:

• The "leapfrog" moment that sparked a shift from simple bots to generative AI
• Why leaders need to say everything seven times
• The reason 95% of corporate AI pilots are failing
• How to prevent the loss of irreplaceable knowledge as experts retire
• Why the next generation’s greatest challenge is protecting their own critical thinking

Angeline Corvaglia, founder of Data Girl and Friends and the soon-to-be-announced SHIELD, joins us to explore how AI education can equip the next generation to stay thoughtful, self-aware, and socially grounded in an age of algorithmic influence.

With a background in global finance and digital transformation, Angeline now works at the intersection of AI literacy and youth empowerment. In this expansive conversation, she shares how emotional design, biased data labeling, and chatbot companions are already shaping young minds, and what parents, teachers, and communities can do about it.

Angeline’s insights challenge us to center student voice, rethink “neutral” tech, and reclaim our inner compass in a time of persuasive machines.

Highlights:

• The chatbot conversation that sparked her shift from CFO to AI literacy advocate
• How young people are unknowingly outsourcing critical thinking to chatbots
• What educators need to know about AI bias, trust, and voice development
• Global stories from Nigeria to Italy revealing AI’s cultural blind spots
• Simple metaphors (like cookie crumbs!) that make data concepts stick