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 skills
• Are digital skills now a soft skill?
• What employers really mean when they say they want drive, work ethic, and teamwork
• How MAGMA has figured out how to successfully re-skill the current workforce
• How technical careers are shifting from narrow expertise to systems thinking

3 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

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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 risk
• Why 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 decline
• The 9 daily factors that may matter more than any miracle supplement or trend  
• How AI is enabling faster research and more personalized intervention
• A roadmap for accessible tests + personalized recommendations for a healthier brain

3 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/

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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 well
• What the EU AI Act reveals about where regulation can quickly become burdensome
• Why adding AI without a clear value proposition is becoming an expensive mistake
• All about new ISO standards for AI
• How bias, de-identification, and prompt injection are reshaping AI risk

3 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 LinkedIn
• ISO 42001 - AI Management Systems

More links & resources on the episode page: https://techedpodcast.com/sullivan/

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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 risks
• Why your professional network is probably bigger than you think
• The "soft skills" issue and why employers are actually hurting themselves by asking educators to teach them
• Rapid-fire real examples of AI being used in business

3 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 Remake
• Oppenheimer movie
• Developing an AI Strategy: Best Practices for Business Leaders - Todd Wanek, CEO of Ashley Furniture Industries
• Using AI to Build Better Relationships with Your Network - Canay Deniz, CEO of Ren

More notes & resources on the episode page!

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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 realize
• The hidden risk inside CAD and design-heavy technical pathways
• How students are using AI to troubleshoot equipment faster than faculty expect
• Why the “trades are safe from AI” narrative may be dangerously simplistic
• Why competency-based education might be a better model in this AI-driven world

3 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 Schumer
• Jensen Huang (NVIDIA) CES Keynote
• Six Days in China: The Speed, Scale and Strategy Outpacing U.S. Innovation - Todd Wanek, CEO of Ashley Furniture
• Try Google's NotebookLM

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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 hiring
• What separates a participation badge from a legally defensible certification
• How micro-credentials create flexibility without sacrificing rigor
• How “exit value” changes the way we think about graduation
• Why performance-based assessment strengthens workforce confidence

3 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

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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

View more resources on the episode page!

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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

See more on the episode page!

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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 on the episode pa

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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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