Promptly Speaking

Promptly Speaking is your guide to navigating the AI revolution without losing your mind—or your job. We bridge the gap between complex technology and real-world application for professionals, creatives, and business leaders. If you are asking questions like: 🤔 "Will AI replace my job?" 🤔 "Is AI making us dumber?" 🤔 "How do I lead a team through this disruption?" ...then this channel is for you. We move beyond the "Tool of the Week" to provide deep dives into AI Strategy, Cognitive Offloading, AI Ethics, and the Future of Work. Whether you are a corporate executive, a solopreneur, or a parent concerned about screen time, we provide the frameworks you need to stay relevant and resilient. New episodes every Tuesday.

Promptly Speaking is a business podcast hosted by Unknown Host, with 0 episodes on record and a Required Pod Score of 80.

Unknown Host hosts Promptly Speaking, a business show with 0 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  Episode #23

  Inside the Heated Debate Over AI on College Campuses

  Sep 29, 202639 minS1

  Universities are basically small cities, and getting everyone to agree on AI is nearly impossible. Beth Myers, CIO at the University of Colorado Denver, joins Sara and Dan to talk about rolling out AI across a massive, opinionated institution. She covers the heated debates between faculty and students, why some disciplines are all in while others resist, what the early research says about AI and learning, the mental health concerns showing up on campus, and why she still worries about the environmental cost of it all. Connect with Beth Myers: https://www.linkedin.com/in/beth-myers/ Follow Sara & Dan: Sara: https://www.linkedin.com/in/saralynneroberts/ Dan: https://www.linkedin.com/in/danroberts27/ Email the show: hello@promptlyspeakingpod.com 00:00 Cold open, AI and complex organizations 00:54 Beth's title and 27 years at CU 01:31 What a vice chancellor actually does 02:11 Why bringing AI to a university is complex 04:11 Losing the ability to have hard conversations 04:31 Who gravitates toward AI, who resists 05:43 Talking to the AI student society 06:36 The computer lab techs' hesitancy 07:23 How heated does it get 09:21 How AI is changing how people learn 11:32 Why students need clearer AI guidelines 11:54 AI and entrepreneurship in students 14:13 The risks of vibe coding without knowing security 15:47 AI literacy and parenting teenagers 17:15 The parental controls Beth actually uses 19:56 AI, loneliness, and student mental health 21:08 Bringing AI into a university's shared governance 23:08 Why the ChatGPT rollout didn't go smoothly 24:10 Required training before getting AI access 26:14 Students who don't want AI in their education 27:22 What early research says about learning and AI 33:39 The environmental cost of AI 35:52 AI subsidies and what happens when prices rise 41:26 Closing thoughts and thanks

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  Episode #22

  The AI Habit That's Quietly Wrecking Customer Success Teams

  Sep 15, 202656 minS1

  A fluent AI answer isn't the same thing as a correct one, and that gap is costing companies more than they realize. Andrew Marks, co-founder of Success Hacker, joins Sara and Dan to unpack why AI's confident tone tricks even smart people into skipping the fact-check. They dig into persona validation, confidence calibration, and why Andrew's team built their own small language model instead of leaning on a chatbot. Along the way: why customer success teams are selling every day whether they admit it or not, why "easy button" layoffs are a mistake, and how to actually put a number on value. Key Takeaways: AI sounds confident even when it's wrong, and that fluency is exactly what makes it dangerous to trust blindly Persona validation (feeding AI a stakeholder's real background) surfaces angles a person might miss Confidence calibration forces AI to rate its own certainty, which helps catch hallucination before it spreads Customer success teams often assume customers understand the value they're getting, when they don't Value looks different depending on who you're talking to: end user, middle manager, or C-suite Customer success professionals are selling constantly (renewals, expansions, retention) even when they resist the label Cutting customer-facing teams because AI can "do it all" is a mistake companies will regret Small, domain-specific language models may end up mattering more than giant general-purpose ones Real value has to be translated into numbers stakeholders care about, like budget or revenue impact 00:00 Cold open: the easy button myth 00:43 Welcome and introducing Andrew Marks 01:10 Success Hacker's accreditation and university ties 02:11 What customer success actually is 04:34 Defining value across stakeholders 06:23 The biggest AI mistake teams make 07:19 AI hallucinations in the real world 08:23 What persona validation really means 09:08 Using AI on a real RFP response 13:27 A better way to prompt and iterate 17:32 Building a knowledge graph and trust layer 19:16 Four years building an AI platform 21:25 Who actually owns customer value 23:43 How this reshapes the customer journey 25:11 Naming "bot shitting" 26:10 Why layoffs based on AI are a mistake 27:58 AI should work with you, not for you 29:28 Teaching critical thinking in the AI era 32:47 Small language models vs. large ones 36:39 What conventional CS wisdom got wrong 39:10 The $150 million case for selling 42:04 Why comp models haven't caught up 44:41 Making value measurable and portable 48:35 The Project Lead the Way story 50:51 Advice for ethical AI adoption 53:52 What to do with 30 minutes and AI References & Links: Project Lead the Way, STEM curriculum nonprofit (www.pltw.org) Success Hacker's AI for Customer Success training program (www.successcoaching.co/ai-for-customer-success) University of San Francisco School of Executive Management (www.usfca.edu/management/programs/executive-education)

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  Episode #21

  The Internet Is Crumbling And AI Is Speeding It Up

  Sep 1, 202652 minS1

  He helped rebrand Mark Cuban's network, managed bands in the 90s, and produced the Jackass guys. Now Tim Glomb spends his days as an AI transformationist, and he's not selling hype. In this episode, Tim joins Sara and Dan to talk about what actually happens when a company adopts AI seriously (spoiler: it's not "slap it on top"), why the open web's foundation is quietly crumbling, and how a small bar owner turned empty seats into free beer and $200 nights using a simple text campaign. We also get into his dad's tear-jerking ChatGPT moment, AI-generated music, and why he worries more about social media than about any AI model. Key takeaways: Most companies are putting "AI paint" on broken processes instead of rebuilding the foundation The open-source code holding up the entire internet is maintained by a shrinking handful of people Small, local businesses can scale further and faster than ever using AI plus real business acumen A simple photo-and-text workflow turned empty bar seats into real revenue Context is everything when prompting AI, vague questions get vague, even misleading answers Tim's dad had an emotional breakthrough using ChatGPT to redesign his bathroom Suno.com lets anyone turn a memory or a person into an original song in minutes Nuclear energy, especially microfusion, may be the real answer to AI's energy demands Some questions (therapy, sensitive personal decisions) simply aren't ones you should hand to AI alone 00:00 Cold open 00:46 Meet Tim Glomb 01:50 The biggest AI misconception execs have 03:15 "AI paint" on a junk car 04:31 Where human glue lives in a business 07:16 Becoming the operator, not getting replaced 09:02 Code review bottlenecks from AI-written code 10:48 The internet's crumbling open-source foundation 13:27 His dad's ChatGPT bathroom breakthrough 15:50 A resurgence for local economies 18:43 One small business, one big AI use case 21:02 Turning a bar's empty seats into $200 25:15 Advice for kids choosing a career path 29:14 The therapy question you shouldn't ask AI 32:10 Why context changes everything you ask AI 36:03 Scanning food with the Yuka app 38:09 Estrogenic compounds, wastewater, and AI research 40:04 AI's real climate cost 41:07 Betting on nuclear fusion energy 44:08 Making AI-generated songs with Suno 48:09 Why he blames the music industry, not AI Connect with Tim Glomb: https://www.linkedin.com/in/timglomb/ Follow Sara: https://www.linkedin.com/in/saralynneroberts/ Follow Dan: https://www.linkedin.com/in/danroberts27/ Email the show: hello@promptlyspeakingpod.com

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  Episode #20

  The Product Leader's Case for Napping Through Big Decisions

  Aug 18, 202637 minS1

  AI can build almost anything now, so what's actually left for a product manager to do? Cliff Barrett, who has scaled product teams at Mailchimp, ChowNow, and Iterable, joins Sara and Dan to unpack why judgment, not tooling, is becoming the real differentiator in product leadership. We talk about a CNN test that 20 million users ignored, why "bring a prototype, not a presentation" is the new standard, the fatigue PMs feel from constant AI-powered output, and how Cliff built his own personal accountability agent to track his fitness journey. It's a grounded, practical look at leading through the AI shift. Key takeaways: Judgment, not data access, is what separates a good product decision from an obvious one A CNN customization feature that tested well in feedback flopped with 20 million real users "You don't bring a presentation anymore, you bring a prototype" is becoming the new baseline PMs are experiencing a new kind of fatigue: constant bombardment with fast AI-built options Curiosity, more than credentials, is what Cliff screens for when hiring product people Demo days and hackathons help channel company-wide building without losing focus Cliff built his own AI accountability agent to track workouts, meditation, and eating patterns Stepping away from screens, and away from AI itself, is still essential to good thinking 00:00 Cold open: judgment over AI hype 00:50 Meet Cliff Barrett 01:05 What a product manager actually does 01:51 The Airbnb product management debate 03:07 Biggest risk: trusting AI's "right" answer 03:26 The CNN newsfeed test that flopped 04:42 How Iterable used AI for marketers 05:45 Why you still need to ask "why" 06:50 Market analysis, data, and stakeholder input 07:25 PM fatigue and decision overload 08:01 The case for thinking time and naps 09:33 Skills for the next generation of PMs 10:22 The Nokia to Apple mobile shift 11:02 Prototypes over presentations 11:27 Building HTML sites at Glean 12:00 Everyone adopts AI at a different pace 13:29 Discernment: what actually matters in a demo 14:16 Step one for product leaders right now 15:19 When everyone can build, how do you focus 16:20 Running successful demo days 18:10 What makes Cliff want to join a company 19:36 Agents marketing to agents 21:08 Why product managers still matter 22:00 Cliff's personal AI accountability agent 24:01 What the historical look-back actually reveals 26:34 How Cliff screens for curiosity in hiring 28:40 Avoiding burnout as a builder 31:00 Using AI to simplify information overload 32:03 AI as a thinking partner, not therapy 34:07 Final advice for product leaders Follow Sara & Dan: Sara: https://www.linkedin.com/in/saralynneroberts/ Dan: https://www.linkedin.com/in/danroberts27/ Email the show: hello@promptlyspeakingpod.com

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  Episode #19

  He Builds AI Learning Tools for Students... Here's What Worries Him

  Aug 4, 202650 minS1

  Can AI make kids better learners, or just more dependent? An educator's honest answer. For our first ever in-person guest, we sat down with Larame Spence, who has spent years tutoring, running a private school, and building AI learning tools. His take flips the usual fear: the most powerful use of AI in education right now isn't sitting a kid in front of a chatbot, it's using AI as the source a parent, tutor, or teacher works through with the student, so the human stays in the loop. Key takeaways: Why AI works best as the tutor's source material, not the tutor The MIT study where feedback labeled "human" beat identical feedback labeled "AI" Building a whole curriculum around one kid's obsession (the all-golf student) The calculator question, and what we lose and gain with every new tool "Confidently wrong" AI, and teaching kids to check their resources How a vetted library plus retrieval makes AI answers more trustworthy The privacy trade-off of an AI that learns exactly how your child thinks Why struggle, not ease, is where the real learning lives This one will change how you think about AI and your kids. Connect with Larame Spence: https://www.linkedin.com/in/laramespence/ Follow Sara & Dan: Sara: https://www.linkedin.com/in/saralynneroberts/ Dan: https://www.linkedin.com/in/danroberts27/ Email the show: hello@promptlyspeakingpod.com 00:00 The scary parts of offloading to AI 01:30 Our first in-person guest 02:30 How education is going to change 03:30 AI as the source, not the tutor 05:30 Tutoring Algebra 2 with an AI 07:30 The MIT human vs AI feedback study 10:30 Spotting AI-generated content 12:00 Helping kids across a language barrier 14:00 The Dominican Republic email workflow 16:30 Will we still learn other languages? 18:30 Tailoring the lesson to each student 21:30 Asking questions without feeling dumb 24:00 Rethinking how we assess students 26:00 The calculator question 29:00 The brain is a muscle 31:30 Advice for nervous parents 33:00 The all-golf student 36:00 Personalizing a lesson by interest 38:30 Measuring student confidence 40:30 Confidently wrong: the star ceiling 43:30 Teaching kids to check their resources 46:00 Cutting hallucinations: tools and retrieval 49:30 How the teacher's role changes 53:00 Does AI help long-term recall? 55:30 Why they built the interactives first 58:30 The privacy trade-off for kids 60:30 Higher ed and the path to a job 63:30 The God code and earned struggle 66:30 Brandon Sanderson and the experience of a book 69:00 Sycophantic AI and why struggle matters 73:00 One takeaway, and don't underestimate Nano Banana

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