I Have Some Questions...
Most people know the headline of a leaderās story. Few know the path it took to get there. This podcast goes beyond titles, book launches and business wins, to explore the lived journey behind the thought leader.
Through deep, unhurried conversations, we uncover the moments that shaped themāthe doubts, pivots, convictions, and quiet breakthroughs that built their body of work.
Each episode features authors, coaches, executives, and bold thinkers who have forged their own path. Instead of rehearsed talking points, theyāre invited into a space where thoughtful questions unlock something more human. The result is a layered conversation that reveals not just what they preach, but how they became the kind of person who can teach it.
Because we believe the best stories arenāt always toldātheyāre revealed. And when brilliant people are given the right questions and the room to answer them fully, what emerges is insight you can feel, frameworks you can apply, and a deeper understanding of what it truly takes to lead, create, and contribute at a meaningful level.
I Have Some Questions...
225: "Is AI Literacy Missing From Classrooms While Work Is Being Redefined?" ft. Asher Albertini
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Asher Albertini, an 18-year-old high school senior and former LearnAir intern, shares what AI has changed for him in school, friendships, and career thinking, and how his generation should prepare for a future where entry-level work gets redefined.
š§ Conversation Highlights
- AI detectors and grading: detectors are often inaccurate and only really target essay-style work, while better approaches include timed writing and drafts/version history.
- Entry-level roles are changing: Asher sees AI taking āmundaneā tasks and raising the bar for critical thinking, strategy, and communication.
- AI literacy training is a missed step: companies often buy tools and say āgoā without training, which creates wild west adoption.
- The future of work requires a new ladder: apprenticeship and mentorship models may replace some āentry-level hiring,ā and students need to start adapting earlier.
š” Key Takeaways
- AI skills are not just subscriptions and prompts. They are about using AI to clarify thinking, do heavy lifting, and then adding human judgment.
- Detectors create fairness problems when they punish good writing or skilled students. Process-based grading can be more reliable.
- The workforce is being redefined faster than education is. Turning a blind eye in schools is a training gap, not a moral victory.
- If entry-level roles compress, the new advantage comes from earlier, real-world apprenticeship-like learning and peer-to-peer education.
ā Questions That Mattered
- Are AI detectors a fair way to grade student work, or do they misclassify genuine writing skill?
- Does using AI for research and drafting reduce critical thinking, or can good prompting and evaluation make thinking stronger?
- When leaders roll out AI without training, what failure mode does that create for employees and adoption?
- If entry-level jobs disappear, what should replace the traditional ladder for talent formation?
š£ļø Notable Quotes
- āI think the detectors are not very accurate⦠Iāve seen Shakespeare⦠being detected as 100% AI.ā
- āI hope in five years that all employers are training their employees on this.ā
- āShort term, it sounds great⦠but what does that do for us? Iām entering the workforce youāre setting up.ā
- āStart considering it⦠your job is not gonna look just like your mom or your dadās job. Itās unrealistic.ā
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