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What can organizational leaders learn from military-tested leadership practices to realign teams, sharpen execution, and move forward with greater clarity? In this episode of The TechEd Podcast, Matt Kirchner sits down with Jay Richards, retired U.S. Navy Senior Chief, former Naval Special Warfare operator, CIA contractor, and author of The Standdown Framework: Advance Over Retreat. Richards brings a rare perspective shaped by elite military service, global special operations collaboration, and high-stakes leadership environments, then applies those lessons to the challenges leaders face inside businesses and educational institutions. Every organization experiences drift: the slow movement away from standards, clarity, discipline, and mission through small compromises and tolerated inconsistencies. The Standdown Framework is about using a deliberate reset to create stronger alignment, uncover untapped intelligence across the team, improve accountability, and open up new possibilities for performance, innovation, and culture. Leaders will learn how to ask better questions, create better discussions, and turn a reset into a lasting operating standard. The result is a practical conversation about how strong leadership can help organizations not only correct course, but build something sharper and more resilient on the other side. In this episode: How drift takes hold inside organizations, and why drift can't be ignoredThe 9-step Standdown framework Jay uses to help teams reset, realign, and move forwardWhy the questions leaders ask often determine whether they get surface-level updates or real truth from their team membersHow to confront breakdowns in performance without creating a culture of blameWhat it takes to turn a one-time reset into stronger culture, sharper accountability, and lasting execution3 Big Takeaways from this Episode: Drift rarely looks dramatic, which is exactly why it’s dangerous. Richards defines drift as the slow movement away from standards, discipline, clarity, and mission through small compromises and tolerated workarounds. In manufacturing, education, or any team environment, the problem often is not collapse. It's gradual erosion that gets normalized over time. A stand down is not a retreat. It is a disciplined reset. Richards reengineered a military-inspired process for organizations that need to stop, realign, and move forward with greater precision. The framework is built to help leaders identify the signal, align the team, define the anchor points, discuss hard truths honestly, and execute a better plan with accountability. Strong leadership is less about control than clarity, accountability, and development. Richards repeatedly returns to the same themes: ask better questions, create psychological safety, praise people publicly when they model the standard, and build systems that hold teams accountable after the reset. He makes the case that great organizations don't just extract value from people today. They develop people for what they can become tomorrow. Resources in this Episode: Read The Standdown Framework book on AmazonMore resources on the episode page: We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

Nikki Gonzales has built a career at the intersection of industrial automation, software, and systems thinking, and in this episode, she makes the case that the next chapter of manufacturing won’t be defined by AI alone. It will be defined by how well people understand process, data, machines, and the interfaces that connect them. The future of automation is as much about human judgment and lifelong learning as it is about smarter technology.  A big part of that story runs through the human-machine interface. The HMI has evolved from a control screen into a communication layer between machines, operators, plant systems, and increasingly, AI-enabled tools. The conversation explores how open standards, AI assistants, scripting support, and emerging protocols like MCP could expand what industrial systems can do, while also lowering the barrier for more people to work with them.  But the episode is not a story about technology replacing expertise. We also discuss technology raising the premium on real understanding. Gonzales argues that even as AI becomes more capable, foundational knowledge of physics, process, controls, and manufacturing systems still matters. She also makes the case that careers in this space are built not just through technical skill, but through curiosity, relationships, mentorship, and the willingness to keep learning. In this episode: How NVIDIA’s Inception program is helping a 30-year-old HMI company innovate like a startupWhy HMIs are a great starting point for applied AI projectsWhat MCP can make possible in industrial automation that a standard API connection cannotHow AI could lower the barrier to entry in automation while raising the bar for process knowledgeWill the future of skills be more specialized, or more generalized?3 Big Takeaways: The HMI may be one of the best places to start with applied AI in manufacturing. The HMI already sits at the intersection of the machine, the PLC, plant systems, and operator decision-making, which makes it a natural place to aggregate data and connect AI tools. In that sense, the future of applied AI in manufacturing is about smarter interfaces that can translate, contextualize, and move information where it needs to go.  AI will make automation more accessible, but not less demanding. Nikki argues that AI can reduce the barrier to entry by helping newer users with scripting, debugging, and development workflows, especially on the HMI side. But she is equally clear that these tools raise the premium on people who understand process, physics, controls, and how manufacturing systems actually work, because the consequences of getting it wrong are too high.  The future automation workforce will be built as much through community as through technology. Through Automation Ladies and OT SCADA CON, Nikki makes the case that technical careers are shaped not only by tools and training, but also by mentorship, relationships, and exposure to the full range of roles in the industry. Resources in this Episode: Connect with Nikki on LinkedIn Learn more about Automation Ladies More links & resources: https://teche We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

What skills actually matter in technical careers now that the work is more digital, more automated, and more interconnected? Industrial employers are not asking schools to choose between hard skills and soft skills. They're asking for both, and they still need the hard skills to come first. At Bosch, Justin Allen sees that every day: teamwork, drive, and professionalism matter, but technical problems don't get solved unless people understand the systems, tools, and engineering underneath them. In this episode: The hard skills vs. soft skills debate: soft skills matter, but technical work can't get done without hard skillsAre digital skills now a soft skill?What employers really mean when they say they want drive, work ethic, and teamworkHow MAGMA has figured out how to successfully re-skill the current workforceHow technical careers are shifting from narrow expertise to systems thinking3 Big Takeaways from this Episode: 1. Industrial employers still expect hard skills for all technical positions, not just "soft" or "employability" skills. Justin says it directly: while companies like Bosch value teamwork, drive, and professionalism, technical problems don't get solved unless people understand the systems, tools, and engineering behind the work. It's an important distinction for schools that hear employers talk about soft skills and assume the technical bar has somehow been lowered. 2. Digital fluency is moving from specialized skill to baseline expectation. Justin argues that younger workers are already showing up comfortable with digital tools, automation, scripts, and AI, while many employers are still adjusting to how fast that shift is happening. In technical roles, that means software awareness and digitalization are becoming part of the expected skill stack. 3. Schools and workforce programs need tighter alignment with industry's talent and skill needs. Justin shares how he's working directly with universities to help shape curriculum, evaluate where students are still missing key competencies, and bringing real engineering problems into capstone projects so learning stays connected to actual technical work. He also points to MAGMA and Michigan’s workforce ecosystem as examples of how employers, public partners, and training providers can help incumbent workers build new skills, retrain for technical roles, and stay aligned with what industry needs now. Resources in this Episode: Learn more about Bosch: https://www.bosch.us/ Learn more about MAGMA: https://miautomobility.org/ More links & resources on the episode page: https://techedpodcast.com/allen We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

Imagine being able to track your brain health before serious decline sets in, understand your personal risk factors, and intervene early enough to help prevent dementia rather than simply react to it. In this episode of The TechEd Podcast, Matt Kirchner talks with Christin Glorioso, MD, PhD, founder and CEO of NeuroAge Therapeutics, about one of the most intriguing frontiers in health and longevity right now: whether brain aging can actually be measured, influenced, and in some cases pushed back. If you’ve paid attention to the rise of biohacking, brain games, cognitive optimization, or the broader longevity movement, this conversation gets underneath the trend and into the science. Glorioso explains how brain MRI, cognitive testing, blood biomarkers, genetics, and AI can be used together to create a more individualized view of brain health. More broadly, the conversation shows how brain health is starting to shift from late-stage treatment toward earlier measurement, prevention, and ongoing optimization. In this episode: Why one of the biggest assumptions in dementia research may have been wrong for years  The 65% number that could completely change how you think about Alzheimer’s riskWhy brain aging starts earlier than almost anyone realizes, and what that means for prevention  Whether you can actually make your brain younger, not just protect it from declineThe 9 daily factors that may matter more than any miracle supplement or trend  How AI is enabling faster research and more personalized interventionA roadmap for accessible tests + personalized recommendations for a healthier brain3 Big Takeaways from this Episode: 1. Dementia is not one disease, and treating it like one has held the field back. Glorioso argues that Alzheimer’s has been approached too narrowly for too long, with the pharmaceutical industry spending decades focused almost entirely on amyloid. Her point is bigger than one protein: brain decline is multifactorial, which means future progress will depend on earlier diagnosis and more personalized intervention.   2. Brain aging starts earlier than most people realize, but it is not a fixed downhill slide. In the episode, Glorioso says measurable shrinkage in the hippocampus begins in the mid-20s and accelerates with age. She also points to evidence that targeted exercise can increase volume in that same brain region, making the conversation far more hopeful than most people expect.   3. You're more in control of your brain health than you may realize. Glorioso cites research suggesting that up to 65% of Alzheimer’s cases may be preventable through lifestyle interventions, then grounds that claim in concrete areas like exercise, sleep, stress, diet, metabolic health, and social connection. That turns brain health from an abstract fear into something people can measure, manage, and improve over time. Resources in this Episode: NeuroAge Therapeutics Follow Christin on Substack Visit the episode page for the rest of the resources: https://techedpodcast.com/glorioso/ We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

Artificial intelligence is moving from novel feature to core infrastructure, and that shift is forcing companies, schools and regulators to confront a harder question than how to use the technology: how to govern it. In this episode of The TechEd Podcast, Matt Kirchner talks with Patrick Sullivan, Vice President of Strategy & Innovation at A-LIGN, about the emerging rules of the AI economy. From the EU AI Act and a patchwork of state-level regulation in the U.S. to new standards like ISO 42001, Sullivan explains why AI is beginning to look less like a software feature and more like a system that carries real operational, security and compliance risk. The conversation also gets into the practical tension leaders are facing now. How do you innovate without creating blind spots? How do you use AI to improve decisions without mishandling student data, exposing customers or introducing risk you do not fully understand? Sullivan’s argument is that done right, governance is not the brake pedal. It is the structure that allows organizations to move faster without losing control. In this episode: Why AI products are starting to face the kind of scrutiny manufacturers already know wellWhat the EU AI Act reveals about where regulation can quickly become burdensomeWhy adding AI without a clear value proposition is becoming an expensive mistakeAll about new ISO standards for AIHow bias, de-identification, and prompt injection are reshaping AI risk3 Big Takeaways from this Episode: 1. AI is forcing leaders to think about products, risk, and compliance in a new way. Patrick draws a sharp distinction between how the U.S. often treats AI as software and how the EU increasingly treats AI as part of a broader product, including embedded systems like medical devices. That shift matters because it changes how organizations think about safety, conformity, and responsibility before a product ever reaches the market.  2. The AI race is producing a lot of motion, but not always much value. Many organizations are adding AI because the market expects it, not because the business case is strong. One MIT study suggests only a small share of enterprises surveyed were realizing meaningful ROI. Leaders need to ask whether the technology creates real value or simply creates new cost, risk, and complexity.  3. Good governance is not a brake on innovation; it's what makes innovation durable. Patrick’s most effective metaphor is the football field: the lines are not there to punish you, but to show where you can move fast and where you are out of bounds. That idea comes through again when he discusses ISO management systems, lifecycle thinking, investor expectations, and enterprise buyers who increasingly want proof that AI is being developed and used responsibly. Resources in this Episode: Follow Patrick on LinkedInISO 42001 - AI Management SystemsMore links & resources on the episode page: https://techedpodcast.com/sullivan/ We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

Are employers hurting themselves by only asking for 'soft skills' and ignoring their real technical needs? How can homeschool students get the same access to STEM labs as students in traditional schools? And what can education leaders learn from the way the Manhattan Project mobilized talent and innovation to solve an enormous problem? These questions (and more!) came directly from the you, and we're answering them on this episode of Ask Us Anything. Entrepreneurship, career strategy, workforce skills, and the rapidly evolving role of AI in modern organizations - we cover them all! In this episode: The best times to take entrepreneurial risksWhy your professional network is probably bigger than you thinkThe "soft skills" issue and why employers are actually hurting themselves by asking educators to teach themRapid-fire real examples of AI being used in business3 Big Takeaways from this Episode: 1.Early-career risk can be an advantage for entrepreneurs. Matt explains that early in your career the consequences of failure are often much smaller, which makes it an ideal time to experiment with starting a business or pursuing a bold opportunity. With fewer financial obligations and more flexibility, young professionals often have the greatest ability to take meaningful risks. 2. Industry is hurting itself by only asking schools for soft skills instead of technical ones. Businesses frequently tell educators they want graduates who communicate well, collaborate, and show initiative. So why is industry so shocked that there aren't enough students with any technical background or interest? Employers: take a look at your job postings and start asking education to teach all the skills for those jobs: soft and technical (hard) skills alike. 3. Private schools have a unique opportunity to innovate in STEM education. Because they often have more flexibility than traditional public systems, private schools can move quickly to adopt emerging technologies, modern equipment, and new instructional models. That freedom creates an opportunity to design programs that expose students to advanced STEM fields earlier and more creatively. Resources in this Episode: Jack Dorsey’s Block to Lay Off 40% of Its Workforce in AI RemakeOppenheimer movieDeveloping an AI Strategy: Best Practices for Business Leaders - Todd Wanek, CEO of Ashley Furniture IndustriesUsing AI to Build Better Relationships with Your Network - Canay Deniz, CEO of RenMore notes & resources on the episode page! We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

What does the rise of AI mean for technical programs? Surprisingly, it's not a new concept to CTE fields. It is embedded in robotics, automation, diagnostics, and data modeling across modern manufacturing facilities today. In this episode of The TechEd Podcast, Matt Kirchner sits down with Dr. Andrew Neuendorf, Associate Dean of Manufacturing, Engineering, Trades, and Transportation at Des Moines Area Community College (DMACC), to explore what applied AI actually means inside CTE programs and why education must move beyond generative AI. With a background in English and the humanities, Andrew offers a rare perspective on how artificial intelligence is perceived differently across academic disciplines. From robotics labs to industrial technician programs, he explains where AI has already been embedded for years, where disruption is coming next, and how community colleges can respond with clarity rather than panic. From design software disruption to AI-assisted troubleshooting and entry-level data modeling skills, this conversation will help technical educators think about applied artificial intelligence in their programs. In this episode: Why robotics and automation programs have been teaching AI longer than they realizeThe hidden risk inside CAD and design-heavy technical pathwaysHow students are using AI to troubleshoot equipment faster than faculty expectWhy the “trades are safe from AI” narrative may be dangerously simplisticWhy competency-based education might be a better model in this AI-driven world3 Big Takeaways from this Episode: 1. Applied AI has already been embedded in CTE for years. Robotics vision systems, PLC-driven automation, driver-assist sensors, and predictive maintenance models have quietly trained students in machine intelligence long before generative AI dominated headlines. The difference today is scale and accessibility, not the existence of AI itself. 2. The future disruption isn’t blue collar versus white collar — it’s discipline by discipline. Andrew argues that assuming the trades are immune to AI disruption is a strategic mistake, particularly in design-heavy roles like CAD and digital modeling. Education must evaluate AI’s impact at the skill level rather than rely on outdated workforce categories. 3. Students may lead the applied AI shift inside technical programs. From uploading robot manuals into NotebookLM to accelerating troubleshooting in automation labs, students are modeling AI-assisted problem solving in real time. Institutions that recognize this and structure learning around it will move faster than those focused solely on policing its use. Resources in this Episode: Connect with Andrew on LinkedIn Other resources: "Something Big is Happening" by Matt SchumerJensen Huang (NVIDIA) CES KeynoteSix Days in China: The Speed, Scale and Strategy Outpacing U.S. Innovation - Todd Wanek, CEO of Ashley FurnitureTry Google's NotebookLMWe want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

The labor market is evolving faster than traditional signals of competence can keep up. Roles are shifting, technology is accelerating, and employers are searching for clearer ways to identify real capability. In that environment, degrees remain valuable, but verified skills are becoming increasingly central to hiring and advancement. In a marketplace now saturated with more than a million credentials, clarity has become the differentiator. Some credentials function as marketing tools. Others function as infrastructure for trust. The difference lies in independence, rigor, defensibility, and industry validation. In this conversation with Kathleen McNally, CEO of NOCTI, we explore how high-quality third-party credentials create reliable signals for employers, meaningful exit value for learners, and actionable tools for educators. From ISO-backed certification standards to performance testing and stackable micro-credentials, this episode reframes credentials as essential infrastructure for a more agile, skills-driven economy. In this Episode: Why employers are shifting from degree-first to skills-aware hiringWhat separates a participation badge from a legally defensible certificationHow micro-credentials create flexibility without sacrificing rigorHow “exit value” changes the way we think about graduationWhy performance-based assessment strengthens workforce confidence3 Big Takeaways 1. Verified credentials are strengthening the signal in a fast-moving labor market. As job roles evolve more quickly than traditional degree cycles, employers are seeking precise indicators of job-ready capability. Third-party certifications developed with national industry input provide measurable proof of occupational and technical competency. 2. Quality and independence determine whether a credential carries real weight. With more than a million credentials available, rigor is what separates noise from trust. ISO-aligned, legally defensible certifications built through independent subject matter experts reduce hiring risk and create consistency across regions and employers. 3. Micro-credentials are enabling lifelong learning with structure and momentum. Stackable certifications allow learners to document specific competencies at any stage of their career. Whether entering the workforce, reskilling mid-career, or adding new capabilities such as AI literacy, credentials create flexible on-ramps and sustained pathways for advancemen We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

Over the past several years, many leaders have noticed a subtle but meaningful shift inside their organizations: the erosion of basic workplace courtesies, particularly from younger employees new to the professional workplace. Not misconduct; not ethical lapses. But something more subtle. Employees announcing time off instead of requesting it. Cameras off in meetings. Missed meetings treated casually. Messages left unanswered for a day or more. Delegating up. Matt Kirchner addresses these patterns directly, sharing firsthand stories from his own companies and examining what has changed in professional norms, and why. This is not a critique of younger employees. We're all for promoting emerging leaders and believe early-career professionals bring energy, ambition, and a willingness to attempt what others might dismiss. But many of these individuals also entered the workforce after losing formative years of in-person education, internships, and social development during COVID-era isolation. As a result, expectations that once felt intuitive often now require explicit instruction. This episode explores specific areas where standards are slipping and explains how organizations can reestablish expectations without embarrassment or blame. Matt closes with a practical framework for addressing unprofessional behavior consistently and constructively, with the goal of strengthening culture rather than policing it. Listen to Learn: The workplace behaviors that are quietly reshaping organizational cultureHow pandemic disruptions affected professional social developmentWhy virtual meeting norms have outsized cultural impactWhat “delegating up” reveals about accountability and ownershipA structured approach for restoring workplace standards without alienating newer employeesResources in this Episode: Read the article in Products Finishing: "Relearning Common Courtesies in the Workplace" Follow Matt on LinkedIn View more resources on the episode page! We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

Imagine giving middle and high school students a full week to explore careers without grades, homework, or “regular” classes. That’s the core idea behind Camanche Community School District's J-term: a dedicated pause in the academic grind that turns school into a career-exploration lab, where 5th-12th grade students can test-drive career fields, build confidence, and discover options they didn’t even know existed.  That's right: J-term is no longer only reserved for the college experience. What makes this model so compelling is the way it engages students & teachers in a way that the traditional classroom never could. Middle and High School Principals Melissa Phillips and Josh Davis saw higher engagement and clearer direction in this real-world, hands-on week of learning. You see it in the outcomes and reactions: the high school generated 100+ internships, the middle school reported zero office referrals that week, attendance hit a high-water mark, and the community showed up in force. In this episode: Why a “no grades, no homework” week can reveal a different version of students and teachers.How J-term creates equity in exposure by removing barriers families can’t always overcome on their own. Why employers and community partners are more likely to say “yes” to short, high-impact experiences than longer commitments. How a J-term can reshape course choices and future plans, helping students move from “I don’t know” to a real next step. 3 Big Takeaways from this Episode: 1. A grades-free, hands-on week can encourage a different level of student engagement. At the middle school, they saw zero office referrals and “not one student” sent down for behavior during J-term. The deeper lesson is that when the goal shifts from performance to exploration, more students lean in because the experience finally matches how they learn best.  2. J-term is an equity play because it reduces the “who you know” advantage. The high school framed it explicitly as removing barriers for families who “don’t have the means” or the pathway to get students these opportunities on their own. Guardrails like requiring internships not be at a student’s current job help ensure the week is about new exposure, not just extending what already exists.  3. Short, real-world exposure can change trajectories faster than a semester of coursework. One student had such a strong internship experience that she reworked her schedule to keep going back, and it shifted her likely postsecondary plan toward education. The big insight is that a one-week “test drive” creates clarity either way, helping students confirm a direction or rule one out while the stakes are still low.  Resources in this Episode: Read about Camanche CSD's J-Term week Visit Camanche CSD See more on the episode page! We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

Your organization doesn’t have a data problem. It has an intelligence problem: the gap between having information and being able to act on it with speed, clarity, and confidence. That gap shows up everywhere: hospitals, schools, manufacturers, and any team drowning in dashboards while leaders still wait on someone to “find the story.” Rick Anderson (Chairman & CEO, The Hive Health) is back to show just how much AI has impacted one organization in 12 months. Enter Corby Furrer (Harvard AI fellow, builder since college) and Will Furrer (former NFL quarterback turned COO). Together, they've built what they call a "trade intelligence platform" - not another analytics tool, but a system that encodes economic expectations, reconciles them against purchasing reality in real-time, and tells people exactly what action to take when behavior drifts off course. Intelligence isn't about regression models anymore. It's about knowing what "good looks like," verifying AI assumptions through human-in-the-loop, and translating observations into stories that change behavior when delivered by the people who speak the right language (physician to physician, engineer to engineer, teacher to teacher, not consultant to administrator). Sustainable change requires three legs: understanding the rules of the game, seeing what's actually happening (not what's supposed to happen), and coaching insights through stakeholders who can shift behavior. AI scales when it creates shared clarity people can validate and act on repeatedly, not when it generates reports that collect dust behind the CEO's desk. In this episode: Why your organization can have endless dashboards and still lack decision-grade intelligence. What must be true for leaders to trust AI results enough to act on them. How a data observation becomes a story for the change agent that actually drives behavior change. How coding and product building changes when AI can generate code, and why knowing “what good looks like” matters.Why one-time improvements fade, and what it takes to build a repeatable system.3 Big Takeaways from this Episode: 1. Decision-grade intelligence starts with clear expectations and a next action. The bridge from data to intelligence = what should happen, reconciling it against what is happening, and using that gap to drive the next corrective step. The takeaway is widely applicable: if you cannot state the intended economic or operational outcome, you cannot reliably diagnose variance or drive consistent performance. 2. If the improvement is not repeatable, it is not a solution. Build a system that codifies the work, monitors performance against targets, and keeps savings from reverting once the project ends. The real value in AI projects is durable behavior change and ongoing detection of the next opportunity, not a one-time finding. 3. Insights only matter when they are delivered to the change agent as a story that drives action. A data observation has to become a narrative that the person who can change the behavior will actually respond to. In the AI era, that elevates a specific skill stack: storytelling, curiosity, and building, because trust and adoption live or die in communication and execution, not in the existence of a model.  Links & resources on the episode pa We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

The U.S. Department of the Interior manages the nation’s most consequential assets—public lands and waters, energy resources, and critical minerals—making it a crucial center for AI capabilities, national security, and workforce opportunity. In this episode of The TechEd Podcast, host Matt Kirchner sits down with Doug Burgum, U.S. Secretary of the Interior, to connect the dots between Interior's responsibilities and the next generation of innovation in the U.S. Today, Interior manages 500 million acres of public land, plus subsurface and undersea resources, territories, and the nation’s historic sites, national parks, Fish & Wildlife, and offshore energy footprint. All of those resources are tied to America's opportunity to innovate in areas like artificial intelligence. Secretary Burgum frames AI data centers as “intelligence factories”, industrial-scale facilities that convert electricity into intelligence, and argues the next wave of competitiveness will be decided by scalable energy and the materials supply chain behind it. We get into rare earth minerals, nuclear power, the tech and energy race with China, and the opportunities for today's students to pursue cutting-edge careers. The episode also widens the lens to the country’s long-term innovation narrative. Burgum ties today’s tech inflection point to America 250 and the Theodore Roosevelt Presidential Library—a reminder that public lands, history, and national ambition can be part of how we inspire the next generation to build. In this episode: The shift from AI as software to AI as physical infrastructure — and why land, power, and materials suddenly matterWhy data centers are becoming “intelligence factories” — and what that changes about how AI scalesThe truth about rare earth minerals — (why they aren’t actually "rare") and why processing is the real bottleneckThe nuclear energy race with China — and why speed, not discovery, is the deciding factorWhere the real career opportunities are emerging — far beyond software, deep into energy, minerals, and infrastructureResources in this Episode: Visit the U.S. Department of the Interior More resources from this episode: Bureau of Indian EducationTheodore Roosevelt Presidential LibraryMore notes & resources on the episode page! https://techedpodcast.com/burgum2 We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

Most leaders have a vision, a plan, and the authority to move it forward, but real momentum shows up when you understand how culture is being shaped through trust and influence behind the scenes. Host Matt Kirchner sits down with Dr. Ben Johnson, Assistant Superintendent for Secondary Schools at Bismarck Public Schools, and Bobby Dodd, Assistant Principal at May River High School, co-authors of Intentional Influence. They break down how influence really spreads inside an organization, in schools, in business, and in industry, and why the people with the most impact are often not the ones with the biggest titles. At the center of the conversation is their cultural mapping framework—making the invisible influence network visible. You’ll hear how to identify formal and informal influencers, classify commitment on a five-point scale, and invest your time where it will actually shift the culture instead of just managing noise. In this episode: How to move a team from compliance to commitment—without pressure, politics, or performative buy-inWhy “trust is the currency of culture,” and how to build it in everyday leadership momentsThe cultural mapping basics: formal vs. informal leaders, a five-point commitment scale, and understanding how influence flows throughout your organizationThe difference between positional power and personal power, and why titles can create action without creating true alignment“Energy vampires” and the “pinging effect”: how attitudes spread through a team, and how strong leaders respond in a way that protects momentum3 Big Takeaways from this Episode: 1. Lasting change is a culture outcome, not a plan outcome. Compliance can produce short-term execution, but commitment is what sustains new behaviors when nobody is watching. The work is to build alignment and trust so people internalize the “why” and carry the standard forward. 2. Cultural mapping helps you lead the real organization, not just the org chart. Influence runs through informal networks of credibility and relationships, and the highest-impact people often do not have the biggest titles. When you identify formal and informal influencers and where people sit on a commitment scale, you can invest your time where it will actually shift the culture. 3. Influence spreads fast, so leaders have to manage energy and momentum intentionally. “Energy vampires” and the “pinging effect” are real, and unchecked negativity multiplies through the network. The goal is not to label people, but to understand what’s driving resistance, address it directly, and redirect influence toward the commitments the organization is trying to build. Resources in this Episode: Get the book Intentional Influence: Harnessing Cultural Mapping to Build Commitment More resources on the show notes page: https://techedpodcast.com/influence We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

Higher education is shifting toward a connected model where colleges and universities function as one learner ecosystem. The goal is simple: make credentials stackable, transfer predictable, and pathways flexible enough for learners to move in and out of education as their careers evolve. In this episode of The TechEd Podcast, Matt Kirchner speaks with Dr. Katherine Frank (Chancellor, University of Wisconsin–Stout) and Dr. Sunem Beaton-Garcia (President, Chippewa Valley Technical College) about how their institutions have developed streamlined pathways for learners that support lifelong learning. They break down how institutions can design on-ramps and off-ramps, align programs across tech/community college and university systems, expand credit recognition, and keep partnerships active so transfer works in real life (no more "credits to nowhere"). The conversation also expands to what this shift means nationally as technology and workforce needs change faster. Watch this episode on YouTube! In this episode: What a connected model for colleges and universities actually requires in program design and policyHow to make transfer predictable and student-friendly without lowering academic standardsWhy stackable credentials and credit for prior learning matter more as learners move in and out of educationHow to get around the red tape that has traditionally prevented colleges and universities from creating streamlined transfer pathwaysWhat higher education leaders should do next if they want to build the new model in their own region3 Big Takeaways from this Episode: 1. A connected model keeps learners moving across colleges and universities. Stackable credentials, credit for prior learning, and predictable transfer reduce the stop-and-start pattern that derails working adults and career-changers. When pathways are designed for entry, exit, and return, education becomes a long-term system learners can use throughout their careers. 2. Transfer works at scale when it becomes an operating habit, not a one-time agreement. The UW–Stout and CVTC alignment shows what changes when institutions treat pathway design as ongoing work with shared ownership and recurring check-ins. That consistency is what makes transfer feel clear to students and sustainable for faculty and staff. 3. This model makes it easier to keep programs aligned as technology and jobs change. Modular, competency-aligned pathways let institutions update portions of a program without rebuilding the entire structure. It is a practical way to respond faster to industry signal while protecting rigor and program quality. Resources in this Episode: Read the op-ed co-written by Drs. Frank and Beaton-Garcia: "Reframing Higher Education" ➡️ Find more resources on the episode page: https://techedpodcast.com/disruption/ We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

What actually happens inside those massive Amazon facilities—and how do products arrive at your door with such astonishing speed? In this episode of The TechEd Podcast, host Matt Kirchner explores these questions with Amanda Willard, Strategic Workforce Development, and Logan Schulz, Senior Manager of Reliability & Maintenance Engineering at Amazon. They take us behind the scenes of the advanced robotics, mechatronics, and automation systems that power Amazon’s fulfillment network—and the skilled technicians who keep the entire operation running. Amanda and Logan share how the Reliability & Maintenance Engineering (RME) team prepares the workforce behind this technology, including Amazon’s mechatronics and robotics apprenticeship. They reveal what today’s technicians actually do, the durable skills that matter most, and how Amazon develops talent capable of maintaining one of the world’s most complex automation ecosystems. Listen to learn: How Amazon uses robotics, AMRs, vision systems, and miles of automation to move products at remarkable speedWhat actually happens inside the RME apprenticeship, from 12 weeks of training to 2,000 hours of structured mentorshipWhy durable skills like troubleshooting, analytics, and system connectivity matter more than any specific technologyHow data, AI, and predictive maintenance are reshaping the technician’s roleWhat technical educators should teach now to prepare learners for next-generation automation careers3 Big Takeaways from this Episode: 1. Maintenance roles have shifted from mechanical work to high-level cognitive problem-solving. Technicians at Amazon diagnose interconnected networks, sensors, PLC systems, and smart devices alongside mechanical equipment. This evolution requires system-level thinking, the ability to interpret data, and strong analytical abilities—skills that anchor long-term career growth. 2. Apprenticeships are a business strategy that strengthens the entire talent pipeline. Amazon’s mechatronics and robotics apprenticeship builds internal talent, increases employee retention, and prepares the workforce for future technology needs. With industry certifications, structured mentorship, and extensive hands-on training, the program creates a sustainable pipeline of highly skilled technicians. 3. Durable skills prepare learners for technologies that don’t exist yet. Troubleshooting methods, programming fundamentals, data analytics, and understanding how systems interconnect form the foundation technicians will rely on as automation accelerates. As AI, predictive maintenance, and IoT devices expand, adaptability and analytical reasoning will matter more than the specific robots or tools a technician first learned on. Resources in this Episode: Learn more about Amazon Reliability & Maintenance Engineering Learn more about the Amazon RME Mechatronics & Robotics Apprenticeship program Find more resources on the episode page! https://techedpocdast.com/amazon We want to hear from you! Send us a text. Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn