The Learning Experience Ops Show

The Learning Experience Ops Show is a series of real conversations with the people building and running the systems that make learning work—across higher education, K–12, healthcare, clean energy, corporate L&D, and beyond. Each episode explores how learning teams are adapting to massive change: what’s working, what’s breaking, and what’s next. Guests share their strategies, tools, and stories from the front lines of Learning Experience Operations (LX Ops)—the evolving discipline where design, technology, and organizational systems meet. At its core, the show is about one big idea: learning gets better when it’s built on a clear, repeatable process that’s ready for whatever comes next.

The Learning Experience Ops Show is a education podcast hosted by Jackrabbit Learning Experience, with 26 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Jackrabbit Learning Experience hosts The Learning Experience Ops Show, a education show with 26 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  Episode #27

  Episode 26: From AI Disorientation to Traction: Hamit Hamutcu on the Six-Month Shift in How Educators Are Thinking and Talking About AI

  Aug 18, 202643 minS1

  Summary In this conversation, Jason Gorman talks with Hamit Hamutcu, founder of AIx Ed, an event and community platform that brings together K-12 teachers, university leaders, ed tech founders, and policymakers to make sense of what AI means for education. They discuss the striking leap in maturity he observed between the November 2025 and May 2026 AIx Ed conferences, the danger of siloing conversations by sector, and why education is making more progress on how we teach than on what we teach. Hamit also shares lessons from co-founding a data science skills taxonomy, offers practical advice for professionals drowning in AI news, and predicts a calmer near future where AI becomes embedded in workflows rather than remaining the dominant topic of conversation. Takeaways The maturity of AI conversations in education jumped dramatically in just six months. There is far more progress on how we teach than on what we teach. Cross-sector conversations are more valuable than sector-specific silos. AI skills must be integrated into subject context, not taught in isolation. Taxonomies help professionalize a field but must be ready to be thrown out. Durable skills like problem structuring and evaluation outlast any specific tool. Keeping up with AI daily creates anxiety; a monthly wavelength is enough. Individual initiative is driving more change than organizational policy right now. The real next step is tinkering with AI in your own workflows, not reading about it. In two to three years, AI will feel more like business as usual than a disruption. Watch the Full Episode From AI Disorientation to Traction: Hamit Hamutcu on the Six-Month Shift in How Educators Are Thinking and Talking About AI Read the Blog From AI Disorientation to Traction: Hamit Hamutcu on How Educators are Finding Their Footing

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  Episode #26

  Episode 25: The Talent Crisis Is Not a Skills Shortage- Anand Shekhar and Ram Iyer on What AI Is Doing to Labor Market Value and the Human Capabilities That Survive It

  Jul 23, 202640 minS1

  Summary In this conversation, Jason Gorman talks with Anand Shekhar and Ram Iyer, co-founders of ClaraLearn, a workforce intelligence platform built on a thesis that runs against the grain: the global talent crisis is not a skills shortage but a clarity shortage. Anand and Ram explain how AI is collapsing both the skills and scarcity that have historically determined professional value. They walk through their model for helping professionals discover their identity beyond job titles, explore adjacent career paths without starting from scratch, and retain what they learn rather than just consuming content. The conversation also covers why learning must be treated as infrastructure rather than a cost center, how critical thinking and domain knowledge are becoming the real differentiators, and why governments and institutions need to step in as the pace of disruption accelerates. Takeaways The talent crisis is a clarity problem, not a skills shortage. Professional value has always been a function of skills and scarcity, and AI is collapsing both. Your professional identity is a spectrum of capabilities, not a job title. Critical thinking and domain knowledge are the skills AI cannot replicate. Retention of learning matters more than consumption of content. Exploration should build on existing skills rather than starting from scratch. Learning must be treated as organizational infrastructure, not a cost line. Personalization is the missing layer in most learning experiences today. Governments, enterprises, and institutions must collaborate to reduce professional anxiety. Realizing your human potential is the most durable response to any disruption. Watch the Full Episode: The Talent Crisis Is Not a Skills Shortage- Anand Shekhar and Ram Iyer on What AI Is Doing to Labor Market Value and the Human Capabilities That Survive It Read the Blog Would You Do This Job If Nobody Paid You? Anand Shekhar and Ram Iyer on the Human Capabilities AI Cannot Touch

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  Episode #25

  Episode 24: Toward a Skills Roadmap for Learning Professionals- James Altman on 197 Survey Responses, Three Tiers, and the Crucial Work Ahead

  Jul 3, 202651 minS1

  Summary In this conversation, Jason Gorman and James Altman unpack the findings of the JLX Future Skills Survey, which asked 197 learning professionals across six regions and multiple sectors to rate nine skills on how important they believe each will be in the next three years. The results revealed three statistically distinct tiers, with learning strategy and design thinking at the top alongside AI tools and stakeholder influence, while traditional staples like LMS authoring tools and content development landed at the bottom. James walks through the methodology, the debates around the term "learning professional," and the surprising gaps between what practitioners value and what they believe their employers value, particularly around storytelling and data analysis. They also discuss the wide spectrum of AI adoption in the field, the qualitative responses that read as a general indictment of a profession without a roadmap, and the early vision for a cross-sector skills roadmap for learning professionals. Takeaways Durable skills dominated the top tier over purely technical ones. Learning strategy and design thinking rated highest across all respondents. AI tools ranked high but couldn't be statistically separated from durable skills. LMS authoring tools and content development fell to the bottom tier. Professionals value storytelling far more than they believe their employers do. Employers are perceived to prioritize data analysis and reporting over narrative. 44% named something AI-related as the top competency, but that number hides enormous variation. Judgment appeared constantly in open responses alongside AI. The qualitative data reads as a profession-wide indictment of having no clear roadmap. Cross-sector collaboration is essential to building a shared skills framework. Watch the full episode: Toward a Skills Roadmap for Learning Professionals- James Altman on 197 Survey Responses, Three Tiers, and the Crucial Work Ahead

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  Episode #24

  Episode 23: Brain Fry Is Real and Organizations Are Causing It: Heather Xu on Cognitive Burden, Pace Gaps, and the Human Cost of Too Much AI Too Fast

  Jun 25, 202648 minS1

  Summary: In this conversation, Jason Gorman and Heather Xu dig into the human side of AI transformation and the growing pace gap between technology, people, and organizations. Heather is the founder of Design for Flow and a former director at KPMG. They explore why learning teams must shift from being course creators to business-aligned capability builders, how to design workflows that preserve human thinking rather than surrendering it to AI, and why human connection is increasing in value, not decreasing. Heather introduces two practical frameworks: one for mapping AI relationships across a workflow (coach, thought partner, accelerator, automator) and another for personal AI value (amplify, unblock, stretch, free). The conversation closes with a discussion on human agency as the foundational skill for navigating an uncertain future. Takeaways: Technology, people, and organizations are moving at three different speeds. Your strengths are what make you feel strong, not just what you're good at. L&D teams must start with business strategy, not their own curriculum. If a learning program isn't adding value, it's actively reducing it. Design for human plus human plus AI, not just human plus AI. The real value of AI comes from strategic questions, not automated outputs. AI left on its own misses things that human judgment catches. Agency looks different for everyone: builders, explorers, sense makers, collaborators, creators. Organizations must account for cognitive burden as work intensifies. Human connection is becoming more valuable, not less, because of AI. Watch the full episode: Brain Fry Is Real and Organizations Are Causing It: Heather Xu on Cognitive Burden, Pace Gaps, and the Human Cost of Too Much AI Too Fast

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  Episode #23

  Episode 22: The Shadow Curriculum Is Already Here- Adarsh Lathika on What Happens When Learners Stop Waiting for Institutions and Start Building Their Own Systems

  Jun 8, 202639 minS1

  Summary In this conversation, Jason Gorman and Adarsh Lathika explore what happens to human capability when AI starts doing more of the thinking. Adarsh, a strategy and learning systems practitioner, introduces concepts like the shadow curriculum, cognitive debt, and the Anatomy of Work framework to explain how learners and employees are increasingly bypassing formal learning systems and building their own AI-powered solutions. They discuss why institutions and employers are losing relevance as learning providers, how prioritizing speed and output over depth is eroding foundational skills, and why human biology, judgment, and context are becoming the true competitive advantages in an AI-first world. Adarsh also unpacks three major shifts reshaping the field: from institutions to individuals, from courses to systems, and from knowledge to judgment. Takeaways Learners are building their own AI-powered learning tools outside formal systems. Knowledge is now abundant and instant; judgment is the real differentiator. AI is shortcutting the repetitive work that historically built domain expertise. Junior professionals are losing the chance to develop intuition through experience. Prioritizing speed and output creates only superficial skill development. Employees no longer trust that organizations are invested in their growth. L&D must shift from curating courses to building self-sustaining learning systems. Human biology, discipline, and habits outside work directly affect workplace performance. Transparency between employers and employees is essential to navigating this transition. Institutions must become places where cognitive and behavioral skills are built, not just credentials earned. Watch the full episode The Shadow Curriculum Is Already Here- Adarsh Lathika on What Happens When Learners Stop Waiting for Institutions and Start Building Their Own Systems

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