Leaders in the Loop – Episode 12 – Rethinking Assessment in the Age of Generative AI

Leaders in the Loop – Episode 12 – Rethinking Assessment in the Age of Generative AI

Dan [https://www.linkedin.com/in/danjenkinsphd/] and Gaurav [https://www.linkedin.com/in/gkhanna1/] are joined by three researchers who are doing some of the most focused, longitudinal work in higher education on how assessment professionals are actually experiencing generative AI — not in theory, but in practice, in policy, and in the profession itself: * Dr. Ruth Slotnick [https://www.linkedin.com/in/ruthslotnick/] is Director of Assessment at Bridgewater State University and a co-lead of a national GenAI pulse survey for higher education assessment professionals that has now run across four administrations since early 2025. * Dr. Will Miller [https://www.linkedin.com/in/willmillerphd/] is Associate Vice President for Continuous Improvement and Institutional Performance and SACSCOC Liaison at Embry-Riddle Aeronautical University. He oversees institutional effectiveness and accreditation across more than 100 sites globally and serves on the SACSCOC Board of Trustees. * Dr. John Hathcoat [https://www.linkedin.com/in/john-hathcoat-771a19352] is Associate Professor of Graduate Psychology and Associate Assessment Specialist in the Center for Assessment and Research Studies at James Madison University, where his work focuses on measurement theory, validity, and the emerging challenge of assessing AI literacy. Episode Overview Dan Jenkins [https://www.linkedin.com/in/danjenkinsphd/] and Gaurav Khanna [https://www.linkedin.com/in/gkhanna1/] open the episode by framing assessment as one of higher education's most persistent challenges — and one of the most consequential sites for navigating generative AI. Ruth, Will, and John bring longitudinal survey data, institutional case studies, and sharp theoretical perspective to a conversation that moves from the origins of their research collaboration, through what the data actually show about adoption and institutional readiness, into deeper questions about what it means to assess student learning when AI is always in the room. Dan also brings firsthand perspective from his own institution's AI task force and from a recent program review he conducted using AI tools for the first time. Topics Covered * How Ruth, Will, and John each came to generative AI independently — and how they found each other at the Assessment Institute in Indianapolis * Ruth's early 2022–2023 experiments using Bing, Bard, and ChatGPT for qualitative data analysis alongside colleague Joanna Boeing * John's shift from skepticism about early automated scoring systems to genuine excitement after a JMU book club read Ethan Mollick's Co-Intelligence * Will's conviction that AI disruption — like COVID before it — creates rare windows for meaningful change in institutions that otherwise resist it * The difference between programmatic/institutional assessment and course-based assessment — and why that distinction matters for how AI enters the work * Gaurav's framing: adoption has won; institutionalization has not * The GenAI Pulse Survey: four administrations since early 2025, more than 278 assessment leaders in Spring 2026, longitudinal tracking of use, tools, policy, training, and influence * Key survey findings: 79% regular or occasional users; 87% report efficiency gains; 87% self-taught; 71% report ongoing privacy and ethical concerns * What "self-taught" reveals about the gap between individual adaptation and institutional support * The policy question: why moving from individual use to institutional guidelines is harder than it looks — and why guidelines may serve institutions better than formal policy * The "tragedy of the commons" dynamic when institutions lack shared AI expectations * John's three-frame model for assessing in an AI-enabled world: what students can do without AI, with AI, and across new contexts * Will's challenge: we know how to verify math before allowing calculators; we don't yet know how to verify critical thinking before letting students go all-out with AI * John's concept of "co-constructed performance" — when learning and assessment no longer happen separately, but in real time alongside AI * Ruth's argument for innovation space: "skunk works" thinking, cross-functional data collaboration, and the role of curriculum design * Dan's firsthand experience using AI (Copilot and Claude) during a program review at JMU — taking stakeholder notes and generating a first-draft report * Faculty reluctance, faculty openness, and what happens when assessment professionals arrive carrying both the assessment agenda and the AI agenda * Lee Shulman's concept of signature pedagogies and why AI integration must reflect disciplinary tradition * Will's analogy: higher ed still gives students summers off because they once needed to work the fields — and AI is forcing the same kind of reckoning with inherited structure * Reasons for optimism: growing AI use in the assessment profession, a tenfold increase in AI-focused presentations at the Assessment Institute, the boot camp Ruth, Will, and John built for the field * The resource gap: many assessment professionals are using free tools because institutions haven't yet funded access * The sphere of influence finding: assessment professionals have substantial influence within their immediate team — but that drops sharply at the department, institution, and external levels * Lightning round: AI tools (Gamma, Claude, Codex/Claude Code), a co-constructed AI wish list, and Ruth's "velvet hammer" prompt approach Key Takeaways * Adoption has outpaced institutionalization — and that gap has consequences. The survey data are clear: assessment professionals are using generative AI, often daily, and mostly on their own. But institutions have not kept pace with training, policy, or tool access. The result is fragmented, inconsistent practice that puts students, faculty, and practitioners in difficult positions. * The cheating frame is a distraction from a harder question. John argues that higher education needs to move past the academic integrity panic and toward a more serious reckoning with what we're actually trying to assess. Three distinct frames matter: what students can do without AI, what they can do with AI, and how they transfer skills across contexts. Most institutions haven't fully confronted any of these. * Co-constructed performance changes what assessment means. When AI is available in real time — prompting students, monitoring thinking, offering feedback — the act of learning and the act of being assessed begin to collapse into each other. John sees this as one of the most urgent conceptual challenges in the field, and one that current measurement frameworks weren't built for. * Assessment professionals are caught in a double bind. Ruth describes the dynamic with characteristic directness: assessment practitioners are already navigating limited sphere of influence on campus. When they also arrive carrying AI advocacy, some faculty "doubly don't like" what they represent. That reality shapes what change is possible and how it has to be introduced. * Guidelines may serve institutions better than policy — for now. The survey and the guests converge on a shared concern: formal policies take years to pass through governance, and the technology changes faster than institutions can ratify. Guidelines — clear but flexible — may allow institutions to move like speedboats instead of tankers. * The field needs to train itself. With 87% of assessment professionals self-taught on generative AI, and with institutions slow to fund either tools or professional development, Ruth, Will, and John built their own boot camp. The field is not waiting — but it is under-resourced. * The window for change is open, but it won't stay open. Will is explicitly optimistic about higher education's discomfort. Discomfort creates opportunity. Faculty are rethinking entire programs — not because an accreditor is coming, not because enrollment is down, but because AI is forcing a real look at what curriculum is actually for. That pressure, he argues, is a rare gift. Resources & Mentions Research & Survey * GenAI Pulse Survey for Higher Education Assessment Professionals – Spring 2026 Results [https://genaiassessment.neocities.org/Spring2026/Spring2026] — Ruth Slotnick, Joanna Boeing, & Bobbijo Grillo Pinnelli * GenAI Assessment main site [https://www.genaiassessment.com/] Book Referenced * Co-Intelligence: Living and Working with AI — Ethan Mollick (Amazon [https://www.amazon.com/Co-Intelligence-Living-Working-Ethan-Mollick/dp/0593716744]) Conference * Assessment Institute at Indiana University Indianapolis [https://assessmentinstitute.indianapolis.iu.edu/] — chaired by Dr. Stephen Hundley; described as the oldest and largest U.S. higher education assessment event AI Tools Mentioned * Gamma [https://gamma.app/] — AI-powered presentation tool (Will's recommendation) * NotebookLM [https://notebooklm.google.com/] — Google AI research and synthesis tool (Dan mentions new slide editing capability) * Claude [https://claude.ai/] — Anthropic (Dan and John mention; John references Claude Code) * Codex [https://openai.com/codex] — OpenAI coding tool (John mentions alongside Claude Code) * Microsoft Copilot — Dan used during program review at JMU Frameworks Referenced * Lee Shulman — Signature Pedagogies (landmark concept in discipline-specific teaching) * Metacognitive practice in AI-integrated curriculum (Ruth references work by Mike Kent — affiliation unverified; Needs Human Review) * "Skunk works" / innovation sandboxes in higher ed — attributed to Nick Bero Jones at Northeastern (name spelling uncertain; Needs Human Review) Organizations * Bridgewater State University [https://www.bridgew.edu/] — Ruth Slotnick's institution * Embry-Riddle Aeronautical University [https://erau.edu/] — Will Miller's institution * James Madison University – Center for Assessment and Research Studies [https://www.jmu.edu/assessment/] — John Hathcoat's center * SACSCOC [https://sacscoc.org/] — Southern Association of Colleges and Schools Commission on Colleges (Will serves on Board of Trustees) * Walden University [https://www.waldenu.edu/] — Ruth teaches here; AI use required in curriculum * American University – Kogod School of Business [https://www.american.edu/kogod/] — cited by Ruth as example of visible, external AI integration commitment * University of South Florida [https://www.usf.edu/] — where Dan and Ruth completed their PhDs together Forthcoming * Book chapter by Ruth Slotnick on AI and assessment, forthcoming in a volume edited by Will Miller (title and publisher TBD) Stay curious. Stay human.

Leaders in the Loop – Episode 11 – Global AI Architect Annie Hardy on Re-Architecting the Cognitive Workforce

Dan [https://www.linkedin.com/in/danjenkinsphd/] and Gaurav [https://www.linkedin.com/in/gkhanna1/] are joined by Annie Hardy [https://www.linkedin.com/in/annie-hardy-9a1a5a5/], Global AI Architect and Futurist at Cisco Systems, for a wide-ranging conversation about what it actually takes to lead AI adoption inside a large organization — not through engineering or edict, but through empathy, movement-building, and a fierce commitment to the humans who get left behind when leaders skip straight to the technology. ----more---- Episode Overview Annie traces her path from communications major and White House intern to community health worker to boutique agency founder to Cisco's Generative AI Architect — and makes a case that every turn in that journey shaped her ability to do what engineers and consultants often cannot: connect the technology to the people it affects.  The conversation moves from Cisco's early generative AI adoption story, through the creation of the Generative AI Explorers community, into the deeper question of what it means to re-architect the cognitive workforce for the age of agents. Along the way, Dan and Gaurav bring in frameworks from leadership theory, organizational learning, and their own classroom and practitioner experience to push the ideas further. Topics Covered * Annie's non-traditional path from communications to Global AI Architect * How she helped lead and evangelize Cisco's Generative AI Explorers community from five people to tens of thousands * Why creating open AI communities actually decreases organizational risk — not increases it – through visibility and support to enable best practices. * Navigating legal, governance, and information security teams during AI adoption * The difference between corporate value programs and genuine innovation culture * Why most organizations throw tools at people without re-architecting the workforce * Convergent vs. divergent thinking and what it means for job design in the age of AI * The data/information/knowledge/wisdom pyramid as a framework for understanding AI's impact on roles * Being in the loop, on the loop, and out of the loop — and what each means for job descriptions * Annie's Code of AI Ethics and its five principles * The Job Lab: an AI-powered career pivot tool she built as a Georgetown capstone project * Shadow AI, personal infrastructure spending, and what it reveals about leadership gaps * Why responsible AI practitioners are being sidelined — and why that should concern everyone * The innovation gap facing women in AI * Community colleges as faster, more agile partners in AI workforce education * Range, cognitive diversity, and why a workforce of strategists is a disaster Key Takeaways * Human-centeredness and strategic influence are both required to build movements. Empathy alone doesn't create change. Neither does strategy without connection. Annie argues that the most effective AI leaders in organizations combine both — and that this combination is rare. * Creating a community around AI reduces risk, it doesn't increase it. When employees have a visible, moderated space to explore generative AI, governance teams gain visibility into what's actually happening. Shadow AI thrives in silence, not in community. * Agentic AI begins with process design, not technology. Before deploying agents, organizations need internal experts who understand both line-of-business workflows and AI capabilities. The knowledge transfer has to happen first. * Leaders are failing workers by skipping the "what comes next" conversation. It is irresponsible, Annie argues, for executives to signal that jobs are at risk from AI without defining what new roles look like and building pathways to get there. * Job descriptions need to be rewritten around the human-in-the-loop. Most organizations haven't begun this work. The question isn't just what AI will automate — it's where human judgment must remain, and how to write that into the role itself. * Cognitive diversity is an asset, not a problem to manage. Not everyone is a strategist. Re-architecting a workforce requires understanding the cognitive profiles already present — and designing for them, not against them. * Start with the pain, not the technology. The most successful AI implementations Annie has seen begin by identifying real human workflow problems, then building toward a solution. The reverse almost always fails. Resources & Mentions Guest * Annie Hardy – LinkedIn [https://www.linkedin.com/in/anniehardy/] * Annie Hardy on Cisco: Global AI Architect and Futurist Hosts * Dan Jenkins – LinkedIn [https://www.linkedin.com/in/danjenkinsphd/] | University of Southern Maine * Gaurav Khanna – LinkedIn [https://www.linkedin.com/in/gkhanna1/] | Cisco Systems / Stanford Continuing Studies Books * If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All [https://www.amazon.com/Anyone-Builds-Everyone-Dies-Superhuman/dp/0316595640] – Eliezer Yudkowsky and Nate Soares (Little, Brown and Company, 2025) * Paddle Forward: Teaming in the Age of AI [https://www.amazon.com/Paddle-Forward-Teaming-Age-AI/dp/1971173002] – Pat Bodin * Range: Why Generalists Triumph in a Specialized World [https://davidepstein.com/the-range/] – David Epstein Organizations & Programs * Cisco Systems [https://www.cisco.com/] * Cisco Trust Center [https://trustportal.cisco.com/] * Austin AI Alliance [https://austin-ai.org/events/] * Ann Richards School for Young Women Leaders [https://annrichards.austinisd.org/] * Georgetown University – AI & Strategic Foresight Program [https://scs.georgetown.edu/] * University of Maine System [https://www.maine.edu/] * International Leadership Association [https://ilaglobalnetwork.org/] * Center for Creative Leadership – Visual Explorer [https://www.ccl.org/leadership-challenges/visual-explorer/] Frameworks & Concepts * Generative AI Explorers (Cisco internal community) * Code of AI Ethics (Annie Hardy, in development) – five principles: protect human privacy, pursue human prosperity, build smart guardrails, retain your brain, use your powers for good * The Job Lab (Annie Hardy, Georgetown capstone project) * Data / Information / Knowledge / Wisdom Pyramid * In the loop / On the loop / Out of the loop framework (referenced from ILA Global Conference) * V2MOM (Cisco goal-setting framework) People Referenced * Amy Edmondson – psychological safety research (Harvard Business School [https://www.hbs.edu/faculty/Pages/profile.aspx?facId=6451]) * Edgar Schein – organizational culture * Warren Bennis – leadership and organizational change * John Lewis – "get into good trouble" * Dale Carnegie * John Capobianco – Cisco network automation / Network GPT * Kevin Kerner – Mason Zimbler / AI podcast * Dr. Lemieux – Georgetown University AI and Strategic Foresight * Provost Adam Tuszynski – University of Southern Maine AI Tools & Platforms Referenced * ChatGPT (OpenAI) [https://openai.com/chatgpt] * Claude (Anthropic) [https://www.anthropic.com/claude] * GitHub Copilot [https://github.com/features/copilot] * Claude Code [https://www.anthropic.com/claude-code] * Google Stitch [https://stitch.withgoogle.com/] (Annie's recommended tool to check out) * Cisco Circuit (internal agent builder) * GPT-3, GPT-2, DistilBERT, RoBERTa (referenced in early LLM context) AI Influencers & Newsletters * Ruben Hassid – How to AI on Substack [https://ruben.substack.com/] (Annie's recommendation) * Allie K. Miller – LinkedIn [https://www.linkedin.com/in/alliekmiller/] | alliekmiller.com [https://www.alliekmiller.com/home] (Annie's recommendation) Music * Joey Harney – Life Bites Back (Annie's album, available on iTunes) Stay curious. Stay human.

Leaders in the Loop -- Episode 10 -- ILA 2026 AI & Leadership Virtual Summit Preview | Leading With AI Across Sectors

Dan and Gaurav are joined by Dr. Mary Tabata [https://www.linkedin.com/in/marytabata/] and Dr. Kevin Bottomley [https://www.linkedin.com/in/kevin-bottomley-phd-cde%C2%AE-506745b/] to preview the International Leadership Association’s 2026 AI & Leadership Virtual Summit [https://ilaglobalnetwork.org/events/2026-ai-leadership-virtual-summit/?utm_source=chatgpt.com], The Integration Frontier: Leading With AI Across Sectors. The summit takes place live on May 6–7, 2026, with on-demand access available afterward. Mary Tabata serves as associate faculty at American Public University System [https://www.apus.edu/] and Eastern University [https://www.eastern.edu/]. Kevin Bottomley is an assistant professor of Global Leadership at Indiana Tech [https://www.indianatech.edu/]. In this conversation, they discuss how the summit came together, why cross-sector dialogue matters right now, and what leaders can expect from this year’s program. ----more---- Episode Overview This episode introduces the purpose and structure of the ILA 2026 AI & Leadership Virtual Summit [https://ilaglobalnetwork.org/events/2026-ai-leadership-virtual-summit/?utm_source=chatgpt.com] and explains why its cross-sector focus matters. The conversation highlights how AI is reshaping leadership practice in education, business, healthcare, and organizational development, while also raising questions about ethics, governance, literacy, and implementation. The summit is designed as a space for leaders, educators, researchers, and practitioners to explore those questions together. The official event page describes the summit as ILA’s second virtual AI summit and emphasizes themes such as ethical and responsible AI, AI literacy, innovation, productivity, leadership development, and reskilling. Event details and registration [https://ilaglobalnetwork.org/events/2026-ai-leadership-virtual-summit/?utm_source=chatgpt.com] Topics Covered * Preview of the ILA 2026 AI & Leadership Virtual Summit [https://ilaglobalnetwork.org/events/2026-ai-leadership-virtual-summit/?utm_source=chatgpt.com] * The summit theme: The Integration Frontier: Leading With AI Across Sectors * The growth of the International Leadership Association [https://ilaglobalnetwork.org/]’s AI and Emerging Technologies member community * Early leadership and teaching use cases for ChatGPT [https://openai.com/chatgpt] and Claude [https://www.anthropic.com/claude] * Hallucinations, verification, and responsible use * AI literacy and implementation frameworks * Leadership challenges in business, education, and healthcare * Human-centered leadership in AI-enabled systems Key Takeaways * The ILA 2026 AI & Leadership Virtual Summit [https://ilaglobalnetwork.org/events/2026-ai-leadership-virtual-summit/?utm_source=chatgpt.com] is designed to connect leaders across sectors around shared AI adoption challenges. * AI implementation is not only technical; it also requires leadership in governance, culture, and change. * Early experiences with generative AI revealed both practical value and clear limitations, especially around fabricated references and unreliable links. * AI literacy needs to be developed with role, context, and sector in mind. * Cross-sector dialogue can help leaders identify common patterns in AI adoption. * Human judgment remains essential in high-stakes environments such as education and healthcare. * The summit emphasizes ethical, inclusive, responsible, and impactful AI leadership. Examples & References Discussed Mary and Kevin describe their early experiments with generative AI in professional and academic settings. Those experiences included testing classroom assignments, reviewing AI-generated papers, and encountering hallucinated citations and broken links. These examples helped shape their approach to responsible AI use and to the kinds of summit sessions they believe leaders need now. The episode also traces the development of the AI and Emerging Technologies member community within the International Leadership Association [https://ilaglobalnetwork.org/]. That work grew out of earlier conference conversations and collaborations around AI, ethics, education, and leadership. The summit program [https://ilaglobalnetwork.org/events/2026-ai-leadership-virtual-summit/?utm_source=chatgpt.com] brings together voices from multiple sectors and includes sessions focused on leadership development, implementation, governance, AI literacy, and organizational practice. The event page also lists Ganna Pogrebna of Queen’s University Belfast [https://www.qub.ac.uk/] as the closing keynote speaker. Mary highlights Pogrebna’s work at Queen’s University Belfast [https://www.qub.ac.uk/] and the broader mix of speakers contributing to the summit. The conversation makes clear that one of the event’s central goals is to help attendees think more clearly about how leadership and AI intersect in real organizational settings. Resources & Mentions * ILA 2026 AI & Leadership Virtual Summit [https://ilaglobalnetwork.org/events/2026-ai-leadership-virtual-summit/?utm_source=chatgpt.com] * International Leadership Association [https://ilaglobalnetwork.org/] * ChatGPT [https://openai.com/chatgpt] * Claude [https://www.anthropic.com/claude] * Chris Wildermuth [https://www.linkedin.com/in/criswildermuth/] * Ganna Pogrebna [https://pure.qub.ac.uk/en/persons/ganna-pogrebna] * Queen’s University Belfast [https://www.qub.ac.uk/] Stay curious. Stay human.

Leaders in the Loop -- Episode 09 -- Greg Allen on AI Practice, Feedback, and The Leaders Lab.io

In this episode, Dan [https://www.linkedin.com/in/danjenkinsphd/] and Gaurav [https://www.linkedin.com/in/gkhanna1/] are joined by Dr. Greg Allen [https://www.linkedin.com/in/gregwallen/], founder of The Leaders Lab.io [https://leaderslab.io/], co-founder of Ascendant Global Leadership, LLC, and a professor of leadership at The Citadel. In this episode, they explore how AI can support leadership development through structured practice, reflection, and feedback. Check out the video version here: https://youtu.be/N5f_fzsGl5o [https://youtu.be/N5f_fzsGl5o] ----more---- Episode Overview Greg shares the thinking behind The Leaders Lab.io [https://leaderslab.io/] and explains the developmental gap he set out to address: what happens after a leadership workshop, class, or assessment, when learners need opportunities to practice, receive feedback, and improve over time. The conversation focuses on AI as an augmentation tool for leadership learning, not a replacement for human coaching. Dan and Gaurav connect Greg’s approach to familiar leadership development practices, including assessments, coaching, communication feedback, and role-play. Topics Covered * The gap between leadership learning and leadership practice * Why Greg Allen built The Leaders Lab.io * The role of Virtual Sapiens in communication feedback * Transformational leadership as a foundation for the platform * AI role-play, Practice Mirror, video Q&A, and uploaded video analysis * Feedback on clarity, empathy, buy-in, framing, and trustworthiness * Using AI to extend leadership development beyond workshops and assessments * Greg’s perspective on safe, prosocial, human-centered use of AI Key Takeaways * Leadership development often breaks down after the initial learning experience, when people need practice and feedback to turn ideas into behavior. * The Leaders Lab.io is designed to support rehearsal, reflection, and improvement over time. * Greg positions AI as a practice partner and feedback mechanism rather than a substitute for human coaching. * Assessments become more useful when paired with conversation, reflection, and action. * The platform’s feedback addresses both the content and delivery of communication. * Practice matters more than simply adding more leadership content. * Greg emphasizes the importance of using AI in ways that are constructive, ethical, and grounded in human development. Examples and References Discussed A recurring theme in the conversation is the difference between acquiring leadership knowledge and building leadership skills. Greg explains that leaders often gain insight from courses, workshops, and assessments, but still need structured ways to rehearse difficult conversations, test approaches, and receive feedback. Dan connects that point to strengths-based development and other assessment tools, while Gaurav emphasizes that the real need in leadership development is not more content, but more meaningful practice. Greg also walks through the main functions of The Leaders Lab.io, including AI role-play, Practice Mirror, video Q&A, and uploaded video analysis. He describes how the platform can generate feedback on both what a leader says and how they show up while saying it, including factors such as clarity, empathy, buy-in, eye contact, trustworthiness, posture, intonation, and filler words. The discussion also situates The Leaders Lab.io within the broader landscape of leadership and AI. Dan references an earlier Leaders in the Loop episode with Gary Lloyd and LeadershipSkillsLab.ai, and Greg explains how his work was shaped by leadership scholarship, practical coaching needs, and collaboration with Virtual Sapiens. In the closing segment, Greg also recommends Teaching with AI by José Antonio Bowen and C. Edward Watson. Resources and Mentions * The Leaders Lab.io [https://leaderslab.io/] * Virtual Sapiens [https://www.virtualsapiens.co/] * The Citadel [https://www.citadel.edu/] * Gallup CliftonStrengths [https://www.gallup.com/cliftonstrengths/en/252137/home.aspx] * Leadership Practices Inventory (LPI) [https://www.leadershipchallenge.com/leadership-assessments/lpi-360] * DiSC [https://www.discprofile.com/] * Myers-Briggs / MBTI [https://www.themyersbriggs.com/en-US/Explore-Solutions/MBTI] * Toastmasters [https://www.toastmasters.org/] * Descript [https://www.descript.com/] * Audacity [https://www.audacityteam.org/] * OpenAI [https://openai.com/] * Teaching with AI [https://www.press.jhu.edu/books/title/54122/teaching-ai] by José Antonio Bowen and C. Edward Watson Stay curious. Stay human.

Leaders in the Loop – Episode 08 – Expanding our Context Windows with Chief Creative Officer Dr. Jonathan Reams

Dan Jenkins [https://www.linkedin.com/in/danjenkinsphd/] and Gaurav Khanna [https://www.linkedin.com/in/gkhanna1/] are joined by Dr. Jonathan Reams [https://www.linkedin.com/in/jonathan-reams-08bb2/], Co-Founder and Chief Creative Officer at the Center for Transformative Leadership [https://www.transformleadership.no/], founder of Adeptify [https://www.adeptify.ai/], and author of Maturing Leadership, to explore what leadership development looks like in an AI-saturated environment—especially when information is abundant but developmental capacity is not. ----more---- Episode Overview This episode frames leadership growth as a developmental process rather than a knowledge-transfer problem. Drawing on adult development theory, neuroscience-informed models of prediction and emotion, and applied AI practice, the conversation explores how leaders expand capacity, interrupt reactivity, and remain accountable in complex systems. Topics Covered * Leaders “create the weather” through emotional and relational climate * The bricoleur mindset and adaptive learning * Predictive processing and constructed emotion * Horizontal vs. vertical development * Downward assimilation of complex concepts * Psychological Aikido and interrupting reactive cycles * Learning loops and dynamic skill theory * Context windows and attention (human and AI parallels) * Intentional AI collaboration and ethical acceleration Key Takeaways * Leadership behavior reflects predictive models shaped by early experience. * Capacity expansion—not content accumulation—drives developmental growth. * Complex ideas degrade when leaders lack the capacity to hold them. * Iterative learning loops enable meaningful skill development. * AI tools require deliberate framing and human accountability. * Ethical maturity must keep pace with technological capability. Examples & References Discussed Adult Development & Learning * Robert Kegan – Harvard profile [https://www.gse.harvard.edu/faculty/robert-kegan] * Jean Piaget – Stanford Encyclopedia of Philosophy [https://plato.stanford.edu/entries/piaget/] * Kurt Fischer – Dynamic Skill Theory * Theo Dawson – Lectica [https://lecticalive.org/] Neuroscience & Psychology * Lisa Feldman Barrett – Official site [https://lisafeldmanbarrett.com/] * Benjamin Libet – readiness potential research * Andy Clark – University of Edinburgh profile [https://www.ed.ac.uk/profile/andy-clark] Leadership & Organizations * The Leadership Circle [https://leadershipcircle.com/] * Arbinger Institute [https://arbinger.com/] * Amy Edmondson – Harvard Business School [https://www.hbs.edu/faculty/Pages/profile.aspx?facId=6451] * Peter Senge – The Fifth Discipline (Publisher page [https://www.penguinrandomhouse.com/books/160027/the-fifth-discipline-by-peter-m-senge/]) AI, Technology & Culture * Google AI Studio (Gemini) [https://aistudio.google.com/] * Claude (Anthropic) [https://www.anthropic.com/claude] * Visual Studio Code [https://code.visualstudio.com/] * Kilo Code (VS Code extension) [https://marketplace.visualstudio.com/items?itemName=kilocode.Kilo-Code] * The Coming Wave – Official site [https://www.the-coming-wave.com/] * Co-Intelligence – Publisher page [https://www.penguinrandomhouse.com/books/738266/co-intelligence-by-ethan-mollick/] * Algorithmic Justice League [https://www.ajl.org/] Stay curious. Stay human.