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 culture
• How pandemic disruptions affected professional social development
• Why virtual meeting norms have outsized cultural impact
• What “delegating up” reveals about accountability and ownership
• A structured approach for restoring workplace standards without alienating newer employees

Resources in this Episode:
Read the article in Products Finishing: "Relearning Common Courtesies in the Workplace"

Follow Matt on LinkedIn

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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

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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

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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 matter
• Why data centers are becoming “intelligence factories” — and what that changes about how AI scales
• The truth about rare earth minerals — (why they aren’t actually "rare") and why processing is the real bottleneck
• The nuclear energy race with China — and why speed, not discovery, is the deciding factor
• Where the real career opportunities are emerging — far beyond software, deep into energy, minerals, and infrastructure

Resources in this Episode:

Visit the U.S. Department of the Interior

More resources from this episode:

• Bureau of Indian Education
• Theodore Roosevelt Presidential Library

More notes & resources on the episode page! https://techedpodcast.com/burgum2

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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-in
• Why “trust is the currency of culture,” and how to build it in everyday leadership moments
• The cultural mapping basics: formal vs. informal leaders, a five-point commitment scale, and understanding how influence flows throughout your organization
• The 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 momentum

3 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

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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 policy
• How to make transfer predictable and student-friendly without lowering academic standards
• Why stackable credentials and credit for prior learning matter more as learners move in and out of education
• How to get around the red tape that has traditionally prevented colleges and universities from creating streamlined transfer pathways
• What higher education leaders should do next if they want to build the new model in their own region

3 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/

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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 speed
• What actually happens inside the RME apprenticeship, from 12 weeks of training to 2,000 hours of structured mentorship
• Why durable skills like troubleshooting, analytics, and system connectivity matter more than any specific technology
• How data, AI, and predictive maintenance are reshaping the technician’s role
• What technical educators should teach now to prepare learners for next-generation automation careers

3 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

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With states stepping directly into the venture capital arena, a major shift is underway in how early-stage companies are funded—and where the next generation of innovation will be built.

In this episode of The TechEd Podcast, host Matt Kirchner dives into this emerging movement with Pete Martin, Director of Portfolio Management at the MSU Research Foundation, and Alison Todak, Vice President of Entrepreneurship & Innovation at the Michigan Economic Development Corporation. Together, they unpack why states like Michigan are deploying public capital into startups, how PitchMI became one of the largest pitch competitions in the country, and what this means for founders, investors, educators, and the broader innovation economy.

From filling early-stage capital gaps to catalyzing private investment, Michigan is using public VC models to strengthen its entrepreneurial ecosystem—and the results are showing. Pete and Alison detail the strategy behind PitchMI, the sectors driving the next decade of growth, the role of universities in spinning out new technologies, and how public and private capital partners are increasingly collaborating rather than competing.

Listen to learn:

• Why states are stepping into early-stage VC and where private capital is falling short
• How PitchMI became a $2M competition drawing 375 statewide applicants
• The sectors Michigan is betting on—from mobility to clean tech to AI and health innovation
• Why founding teams matter more than anything else at the pre-seed stage
• How public VC and private VC now work together to accelerate growth rather than compete

3 Big Takeaways from this Episode:

1. States are stepping into early-stage VC because private capital isn’t meeting the needs of pre-seed founders. Michigan’s earliest-stage companies often start in a funding vacuum, and state-backed dollars are designed to close that first-capital gap. The PitchMI model shows how public investment can de-risk companies enough for private VCs to participate later.  

2. PitchMI is creating a statewide pipeline of founders, companies, and investors. The competition drew 375 applicants in two weeks and activated partners across smart zones, universities, investors, and the private sector. Even companies that didn’t win are already raising capital, hiring talent, and gaining visibility through the program.  

3. Public and private VC are becoming collaborators in building regional innovation economies. Founders backed by public funds gain access to non-dilutive programs, state networks, and industry connections, while private firms gain earlier access to high-potential deals. This shared model is shaping how capital formation and startup ecosystems will evolve over the next decade.

Resources in this Episode:

• Learn more about PitchMI: https://msufoundation.org/pitchmi/
  • MSU Research Foundation
  • Michigan Economic Development Corporation (MEDC)

Find more on the episode page: https://techedpodcast.com/msuresearch/

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With the pace of change in technology, geopolitics, infrastructure, and the economy, what should technical educators and workforce leaders be watching most closely in 2026?

In this year’s annual Predictions episode, host Matt Kirchner shares the fifth edition of a listener-favorite tradition, scoring last year's predictions and looking ahead to the trends and technologies that will shape Tech Ed in 2026.

What's in store for 2026? Energy, defense, materials, biomimicry, AI, smart tech, humanoids, design...and the future of technical education. Listen to the whole episode to hear about these and more!

Full show notes, links & resources on the episode page: https://techedpodcast.com/predictions26

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Watch the episode on Youtube: https://youtu.be/f5gWUVQI0jI

Melissa Martin and Matt Kirchner are back to answer your questions, covering everything from university curriculum design, to AI in the classroom, to what employers actually expect when they invest in education.

This one moves fast, but it’s focused: how do you build programs that truly prepare students for modern work? How do you keep education from falling behind as technology accelerates? Along the way, Matt and Melissa break down what universities need to change, how to raise the bar in the age of generative AI, why ethics can’t be an afterthought, and how to help HR teams understand the value of credentials and new pathways.

Listen to learn:

• What university programs should teach (in one course) to better prepare grads for modern manufacturing work
• How educators can help students identify when AI is wrong and why we need to level-up our homework in the age of AI
• The role of ethics in modern CTE
• The five components of a world-class, modern advanced manufacturing high school program
• How educators can measure program effectiveness and show ROI to industrial partners
• What HR teams need to understand about changing credentials, degrees, and how to evaluate technical candidates

3 Big Takeaways from this Episode:

1. have to teach applied industrial skills, not just theory. Matt argues that a four-year program can cover a lot of “cool stuff in the lab,” but it still needs authentic manufacturing equipment and technology so graduates understand what they will actually see in industry. He frames this as an employer expectation problem: even when budgets are tighter at the four-year level, universities still need to build around the same core technologies students will encounter on day one in manufacturing. 

2. AI changes the standard for student work and makes ethics a core requirement. Melissa and Matt point out that AI is designed to produce an answer even when it doesn't know (causing a 'hallucination'), which means students must learn to question outputs and verify accuracy instead of treating AI as a sole source of truth. From there, the conversation moves from classroom integrity into broader ethics: what it means to do original work, and how humans should think and behave as AI becomes more capable and more embedded in decision-making. 

3. Industry and HR and educators must understand each other's needs to build a successful partnership. Education and Industry both have a responsibility to do their part in a partnership. HR departments must understand the changing landscape of certifications, 3-year degrees and other credentials that students are gaining to demonstrate their technical competency. Likewise, educators must adopt industry practices of tracking metrics to show employer partners the ROI of their investments in the program.

Access tons of links & resources on the episode page: https://techedpodcast.com/askusanything-122025/

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