Ask Us Anything: Early Career Choices, the War for Talent and the Rise of AI
Matt Kirchner - Host & Melissa Martin - Producer of The TechEd Podcast
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You asked...we answered!
In this first-ever “Ask Us Anything” episode, producer Melissa Martin flips the script and poses your biggest questions to host Matt Kirchner. The result is a candid, wide-ranging conversation that covers career decisions, workforce challenges, and the future of artificial intelligence.
From elementary classrooms to C-suite hiring struggles to the role of AI in disrupting education, this episode explores the most pressing questions in STEM and technical education today. Matt and Melissa share real-world stories, practical advice, and unfiltered takes that every educator, employer, and student will find valuable.
Listen to learn:
- Why career interests start forming as early as elementary school, and what kind of exposure matters most
- How young people can sort through post-secondary options without feeling trapped by a single choice
- The interview strategies that stand out to CEOs after thousands of candidate meetings
- What manufacturers are getting right (and wrong) in the race to attract new talent
- How AI is reshaping education, and why human relationships matter more than ever in the age of disruption
3 Big Takeaways from this Episode:
1. Early exposure changes student trajectories. Students begin shaping career perceptions as early as elementary school; use age-appropriate experiences to put advanced manufacturing and STEM on the radar. Matt traces his own path back to a fifth-grade plant tour - watching a vibratory deburring bowl - showing how simple, vivid experiences stick for years.
2. Talent pipelines are a long game. Employers that show up consistently, serve on advisory boards, visit classes often, bring students on site, even offer “pizza Tuesdays”, win attention and hires. Culture and first impressions matter on tours: clean, organized facilities and engaged employees signal a place students want to join, now and later.
3. AI elevates personalization and demands new pedagogy. Shift essay-style tasks toward live, in-class dialogue and reflection to reduce easy generative-AI shortcuts and increase real learning. Use data-informed, asynchronous pathways so learners who need time can take it, and those ready to advance aren’t held back.
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