The Pluralsight Podcast

Josh Burkhead
  • 5.0 (12)
  • Business
  • Updated Weekly

The Pluralsight Podcast is a storytelling platform exploring the rapidly evolving world of technology and learning. Each episode features authentic, human-centered conversations with leaders, luminaries, and changemakers who are shaping the future of tech, guiding organizational transformation, and advancing their own skills and careers.

  1. Sep 29

    Prove Learning ROI Like a Regulator | Matt Lloyd Davies

    "Budget tells me what you intended to do. Activity tells me what people did. But neither tells me whether the organization is now more capable."  Before he built offensive security courses at Pluralsight, Matt Lloyd Davies regulated the UK civil nuclear sector — the skeptical stakeholder whose job was deciding whether the capability an organization claimed was really there. In this episode, we apply that standard of proof to L&D.  We cover why the easiest things to measure are the least useful, the three questions that turn learning into a business case, how to answer the "correlation isn't causation" objection, why the "train them and they leave" fear gets it backwards, and how to get executives to define the standard of proof up front.  Matt Lloyd Davies is a Principal Security Author at Pluralsight. He holds a PhD in mathematical chemistry and worked in explosives safety research, London 2012 Olympic security, and UK civil nuclear regulation before moving into learning.  Chapters: 01:22 From Chemistry to Nuclear Regulation to Pluralsight 03:15 What "Proof of Capability" Means to a Regulator 06:48 Why Proving L&D ROI Feels So Hard 08:32 Start With the Business Problem, Not the Program 11:19 Three Questions That Prove Learning ROI 14:34 Handling the "Correlation Isn't Causation" Objection 17:12 "What If We Train Them and They Leave?" 18:21 Hands-On Labs as the Evidence Layer 19:28 Winning Executive Buy-In Before the Program Is Built 23:56 Security as the ROI Wedge 25:16 Measurement Cadence and Course Corrections 29:24 Two Practical Changes to Make Right Now Connect with Matt Lloyd Davies on Linkedin: https://www.linkedin.com/in/matt-lloyddavies/  Pluralsight courses: https://www.pluralsight.com/authors/matthew-lloyddavies How to measure and prove upskilling ROI (Youtube): https://www.youtube.com/watch?v=TLs1F7Ydn-E  Stay up to date on everything happening in cloud, AI, and security. Sign up for our weekly newsletter: https://www.pluralsight.com/technews/ #PluralsightPodcast #Pluralsight #AI #Upskilling #LearningAndDevelopment

    Prove Learning ROI Like a Regulator | Matt Lloyd Davies

  2. Sep 15

    L&D Doesn't Drive Learning. Leaders Do | Alice Meredith

    Why do learning programs stall even after the licenses are bought, the announcement is made, and people start completing courses? In this episode, Josh sits down with Alice Meredith, culture strategist, Pluralsight author, and certified change management instructor, to answer a question every L&D leader eventually faces: we have the platform, so why isn't it working? Alice's answer is direct. The platform is infrastructure. What's missing is the humanness behind it, and the single biggest factor is the direct leader. In her words: a leader drives learning, period. L&D does not drive those KPIs. The conversation is packed with usable ideas. Why every learning rollout is really a change management project, and what change exhaustion demands of leaders when pulling back isn't an option. LQ, the learning quotient, and why Alice argues it now matters more than IQ or EQ. Her GAS framework for low engagement numbers: give grace, assume positive intent, seek to understand. And a reality-sorting exercise that separates facts from emotional statements like "no one values training." A must-listen for any L&D leader staring at flat utilization numbers and wondering what to change first. Chapters:   01:02 Why Learning Programs Stall 03:30 "We Need to Better Utilize What We Have" 04:58 Where Change Management Fits In 08:04 Change Exhaustion Is Real (No Excuses) 15:22 LQ: The Learning Quotient 20:21 How to Assess Your Team's LQ 29:08 Culture of Learning: The Spa Metaphor 31:35 Why Mandated Learning Hours Backfire 33:15 Inclusivity, KPIs & the GAS Framework 37:21 Three Factors of a Successful Learning Initiative 40:31 Advice for L&D Teams: Grace & Reality Sorting 48:30 Two Practical Changes to Make This Quarter Connect with Alice Meredith: LinkedIn: https://www.linkedin.com/in/alicemeredith/  Pluralsight courses: https://www.pluralsight.com/authors/alice-meredith  Stay up to date on everything happening in cloud, AI, and security. Sign up for our weekly newsletter: https://www.pluralsight.com/technews/   Music licensed through Soundstripe. Code: X0JKGEVCYRFIALUO

    L&D Doesn't Drive Learning. Leaders Do | Alice Meredith

  3. Sep 1

    GitHub Unleashed: LLMs on Guard | Tim Warner

    What happens when you don't just ask one LLM to check your work, but three, and then make them vote? In this episode of The Pluralsight Podcast, we sit down with Tim Warner, Principal Pluralsight Author, Microsoft MVP, and author of more than 200 Pluralsight courses, to talk about what it takes to stay current through three decades of tech disruption, and why gen AI is just the latest wave to ride rather than fear. Tim breaks down what technology and L&D leaders get wrong in the AI gold rush, why shadow AI is the new shadow IT, and how to pair training with guardrails and sandboxes your teams will actually use. Then Tim takes us inside GitHub for a live demo: a GitHub Actions workflow that hands agent and skill definitions to three different LLMs, which scan for prompt injection and other vulnerabilities, then vote on a verdict through a simple quorum mechanism. It's a practical look at defense in depth for AI-assisted development, explained in plain language. Chapters:   01:42 Eternally curious: 30 years in IT 05:07 Know yourself, do your best 07:11 The eternal student persona 09:04 Learning in public 10:57 Underestimated fundamentals and agentic AI risk 13:00 AI councils, not fear-based reactivity 15:24 Shadow AI is the new shadow IT 17:09 Closing the upskilling gap 19:41 The skills leaders underestimate 21:05 Prompt vs. context engineering 22:29 What GitHub actually is 26:17 GitHub Actions explained 29:32 Tim's multi-LLM research workflow 32:53 When LLMs disagree 35:15 Multi-model on a budget 38:30 Is on-prem AI coming back? 39:52 Getting started responsibly 43:38 Demo: LLM quorum security scanning in GitHub 53:29 Security risks and data handling 56:14 Enterprise guardrails and orchestration 59:47 Advice: curiosity over fear 1:02:06 Where to find Tim Connect with Tim Warner:TechTrainerTim LinkedIn: https://www.linkedin.com/in/timothywarner/ Website: https://techtrainertim.com Pluralsight courses: https://app.pluralsight.com/profile/author/tim-warner  Stay up to date on everything happening in cloud, AI, and security. Sign up for our weekly newsletter: https://www.pluralsight.com/technews/

    GitHub Unleashed: LLMs on Guard | Tim Warner

  4. Aug 18

    Customer Spotlight | SEB

    One leads technology. One leads learning. Same bank, same transformation. In this episode of The Pluralsight Podcast, Josh sits down with Kimberly Lejonö, technology leader inside SEB's corporate credit process, and Gabriela Almonacid, L&D Partner for Global Business Services, to trace how two functions inside one of the largest banks in the Nordics are shaping the same AI transformation from entirely different vantage points. What surfaces is a series of connections neither had fully drawn before: where their work already overlaps, where old assumptions don't hold up, and where the real opportunity sits waiting between tech and L&D. We explore: Why 80 to 90 percent of an AI transformation is people work, not tech work, and what that demands from leaders on both sides of the business The calendar move that put a weekly learning hour in front of 3,500 employees at once, and why it had to clear four boards to happen SEB's step-by-step path to AI fluency for non-technical roles: Tech Foundations, hands-on workshops, ideation labs, and a role-based AI Academy How a developer with zero agent experience shipped to production in one month, and why your first use case should be finishable, not flashy Why manager engagement in learning nearly tripled in three years (hint: people don't listen to HR, they listen to their manager) What tech leaders and L&D leaders consistently miss, and why consensus culture pays back ten times at the end   Connect with Kimberly Lejonö: https://www.autogram.id/kimberly Connect with Gabriela Almonacid: https://www.autogram.id/gabriela?card=open   Chapters: 02:02 Meet Kimberly and Gabriela of SEB 05:32 Two roles, one goal: democratizing technology 09:17 The hardest part of scaling AI is people 12:31 Automating the credit process 14:18 A learning hour in 3,500 calendars 19:21 From proof of concept to production 21:39 Skills planning for 20,000 employees 24:04 Ideation labs and the first agents shipped 27:06 Building AI fluency step by step 28:56 What we wish we'd known about AI adoption 34:00 The future workforce 36:13 Will we lose the basic skills?   40:23 Logged hours vs. real learning 42:52 Why manager engagement nearly tripled 44:59 Risk, experimentation, and intentional mistakes 49:05 The Tech Foundations story 52:32 Consensus culture and the mirror exercise 56:20 Leading distributed teams through change 1:00:55 What tech and L&D misunderstand about each other 1:04:47 Measuring what matters 1:07:29 What winning looks like   Stay up to date on everything from AI and cloud to cybersecurity with our weekly newsletter: https://www.pluralsight.com/technews/   #PluralsightPodcast #Pluralsight #AI #Upskilling #LearningAndDevelopment

    Customer Spotlight | SEB

  5. Aug 4

    Certified Doesn't Mean Qualified | Andru Estes

    We've seen this movie before. The FOMO, the holdouts, the surprise bills. In this episode of The Pluralsight Podcast, Josh sits down with Andru Estes, Pluralsight author and cloud architect, to unpack why today's AI gold rush looks so much like the early days of cloud adoption, and how to avoid repeating the same expensive mistakes. We explore: Why so many AI projects fail in the planning phase, and the first question every team should ask: do we even need this tool? Where AI and cloud costs spiral unexpectedly (hint: it's all about data), and how a FinOps mindset with real-time visibility keeps experimentation governed instead of gated Why being certified doesn't mean being qualified, and the hands-on habits that actually close the gap The hidden cost of AI coding tools: skill atrophy, senior engineers stuck babysitting, and the vibe coding cleanup Andru sees coming Common AWS design mistakes, from lift-and-shift bill shock to skipping the planning phase entirely The builder's mindset: discipline over motivation, failure as one of the best teachers, and why there's no such thing as a dumb question Connect with Andru Estes: https://www.linkedin.com/in/andru-estes/ Explore Andru's courses on Pluralsight: https://www.pluralsight.com/resources/blog/blog-author/andru-estes Stay up to date on everything from AI and cloud to cybersecurity with our weekly newsletter: https://www.pluralsight.com/technews/ Check out more episodes and subscribe: https://www.pluralsight.com/resources/podcasts/the-pluralsight-podcast Questions or comments? podcast@pluralsight.com    Chapters:  1:55 Why the AI wave feels like early cloud adoption 4:13 Repeating old mistakes: do you even need the tool? 6:07 What leaders miss: governance, security, and infrastructure 8:38 Signals you're adopting AI the right way 11:36 Where costs spiral: data, FinOps, and guardrails 14:34 Certified doesn't mean qualified 16:41 Becoming capable, not just credentialed 19:29 Splitting time between certs and stretch projects 20:57 AI coding tools, skill atrophy, and tech debt 24:17 The coming vibe coding cleanup 25:17 Common AWS design mistakes 26:32 What a successful planning phase looks like 29:57 Overengineering vs. smart future-proofing 32:00 Staying current with the KISS approach 33:19 The Kubernetes hot take 34:15 Mindset advice for cloud engineers 35:58 Failing in production: a story 39:32 Connect with Andru

    Certified Doesn't Mean Qualified | Andru Estes

  6. Jul 22

    Inside the 100% AI Agent Company | Matt Kropp

    What actually happens when you try to run a company with zero humans? Matt Kropp, Senior Partner and Chief AI Officer at BCG X, is finding out firsthand. His experiment, Vessica Labs, is a company where AI agents set the strategy, write the code, design the brand, and run the operations. Matt's role? The agents dubbed him "the governor." We dig into what the experiment has revealed so far, including the moment his sales agent declared its pronouns were "he" because "men are closers," and what that says about bias hiding in the systems enterprises are deploying right now. We cover the BCG research behind "AI brain fry," why framing AI as an "employee" measurably degrades human performance, and the coaching model that actually gets skeptical teams to adopt AI, when training alone fails. In this episode: The Vessica Labs experiment: what a zero-human company can and can't do Why BCG's research says you should not have "AI employees" Bias in AI systems: how to measure it, baseline it, and monitor it before it scales AI brain fry: the new cognitive risk emerging in agent-heavy workflows Why tool rollouts and training fail without coaching, and what to do instead The "barbell" talent strategy: why some CEOs are doubling down on entry-level hires Minimizing toil and maximizing joy when redesigning work around AI Connect with Matt on LinkedIn: https://www.linkedin.com/in/matt-kropp/   Follow the Vessica Labs experiment on Matt's Substack: https://substack.com/@mattkropp Read Matt's "AI Brain Fry" article on Harvard Business Review: https://hbr.org/2026/03/when-using-ai-leads-to-brain-fry    Chapters: 1:45 Who is BCG X, and what does a Chief AI Officer do? 3:06 Do consultants just mean headcount cuts? 4:55 Why LLMs didn't replace consultants 7:52 Vessica Labs: the 100% AI agent experiment 9:02 The 1,000-manager study: why you should not have "AI employees" 11:59 Meet the agents: Apex, Muse, Echo, Nova, and Forge 14:42 What the governor actually does: the taste problem 18:53 "Men are closers": when bias pops right out 21:56 How to measure, baseline, and monitor bias 23:42 Who profits from a 99% AI-run company? 25:20 AI brain fry: the new cognitive overload 29:00 Accountability: a human must own agent decisions 31:33 Avoiding brain fry: build in breaks 32:52 The state of enterprise AI: from 1,000 flowers to big rocks 37:05 Do SMBs have an AI advantage? 38:39 Why tool rollouts fail: the coaching model 42:33 Identity threat and the mindset flip 44:49 Skills that matter next, and the atrophy problem 46:49 Layoffs and AI: correction or cover story? 49:21 The barbell talent strategy 51:22 Gen Z and the messaging problem 53:19 Messaging AI adoption: good and bad examples 55:26 The environmental question 57:38 Advice for leaders: minimize toil, maximize joy 1:00:00 Where to follow Matt + closing thoughts

    Inside the 100% AI Agent Company | Matt Kropp

  7. Jul 8

    Why 'AI-First' is Wrong | Bipasha Ghosh

    Every company wants to announce it's "AI-first" — but what does that actually signal to the customers and employees you depend on? In this episode of The Pluralsight Podcast, Bipasha "B.G." Ghosh — business school professor, C-suite advisor, and community educator who demystifies AI for boardrooms, classrooms, and towns alike — makes the case that "AI-first" is the wrong North Star, and that building an effective learning culture is what actually separates the organizations that adopt AI well from the ones that stall. Put your customers first, she argues, treat AI as the thing that lets you serve them in ways you couldn't before, and invest in the people expected to make it all work. B.G. sits at a rare intersection of academia, enterprise advisory, and public education, and she uses all three to spot the same pattern everywhere: someone builds the AI, someone else lives with it, and trust breaks down in the gap between them. We dig into why trust — not tooling — is the real moat, and why so many transformations stall not because the technology is hard, but because the human side never gets managed. B.G. is direct about what leaders keep getting wrong: treating AI adoption as a technology project instead of a people project, buying the latest tools while skipping the change management, rolling out agentic systems before anyone's been trained to use them safely, and rewarding the old ways of working while asking for new ones. Her antidote is a genuine culture of learning — one where AI literacy means judgment and data fluency rather than clever prompting, where education is ongoing and curated to how people actually learn, and where leaders create enough psychological safety that experimentation is allowed instead of punished. Topics covered: → Why "AI-first" is the wrong message — and why "customer-first, powered by AI" builds more trust → Why AI adoption is a people project, not a technology project — and where change management breaks down → Why AI literacy is not prompting — and what a real culture of learning looks like → The accountability gap in agentic AI: who owns it when an agent goes wrong → How individuals stay relevant — domain expertise, adaptability, and connecting the dots Chapters:    02:00 Demystifying AI for Boardrooms, Classrooms, and Communities 05:43 The Expectation Gap: Where Trust Breaks Down 09:20 Tech Layoffs: Is AI Really the Reason? 12:43 The Coinbase Example: AI Isn't the Whole Story 13:54 AI Meets Blockchain and IoT 15:40 Losing the Trust of the People Who Stay 18:28 Advice for the People in the Middle 21:27 Preparing for Hybrid Teams: Humans and AI Agents 24:16 The Entry-Level Jobs Question 26:07 What Leaders Need to Understand (Without Coding) 28:51 Building AI Literacy Across the Organization 30:36 The Center of Experimentation 31:19 Psychological Safety, Incentives, and Gen Z Pushback 33:53 What to Look for in a Learning Solution 35:08 Start with Data: The Foundation of AI Literacy 37:34 Trust Is the Moat 38:22 Agentic AI and the Accountability Gap 43:09 What Doing AI Adoption Right Looks Like 44:38 Stop Saying You're AI-First 47:18 Where to Find B.G. 47:44 Rapid Fire: Myths, Confessions, and Hope Stay up to date on everything happening in cloud, AI, and security — subscribe to our weekly newsletter at https://www.pluralsight.com/technews/ Connect with Bipasha: LinkedIn: Bipasha Ghosh | LinkedIn  Questions or comments? podcast@pluralsight.com  www.pluralsight.com

    Why 'AI-First' is Wrong | Bipasha Ghosh

  8. Jun 24

    AI Threat Detection Is Broken | Zack Korman

    Everyone is selling AI security — so when the threats are AI-generated and never look the same twice, can the tools built to match known attacks even see them? In this episode of The Pluralsight Podcast, Zack Korman — co-founder of AI-native security startup Embroidery and former CTO — argues that the answer is no, and that most of what's being sold to close that gap doesn't work the way the marketing claims. Zack spends much of his time proving, hands-on, what AI agents can be tricked into doing, which makes him unusually clear-eyed about what actually protects an organization and what just looks like it does. From a law degree to leading security tech and product teams, he's built a following on a simple habit: cutting through the hype to find what's real. We dig into why defending against AI-driven attacks requires AI-native detection, and why a system prompt is not a security control — you can't write your way to safety with a stern enough prompt when an agent is running with credentials it should never have had. We also take a hard look at what leaders are getting wrong right now: assuming they have visibility into their AI agents when the audit logs barely exist, handing agents their own operator credentials instead of least privilege, and trusting vendor claims that fall apart the moment you follow the incentives behind them. Topics covered: Why AI-driven threats outpace signature-based detection — and what AI-native detection actually requires The Microsoft Copilot audit-log gap and why most organizations have far less visibility than they think How to tell genuine AI security from "AI-washed" tools and vendor hype How to weigh risk when deploying AI agents — and what responsible deployment looks like How to build and lead a security team ready for the AI era Chapters:   00:01:14 Welcome & Why a Skeptic Founded an AI Security Company 00:04:25 "Also Me Being Mad" 00:07:00 What AI-Native Threat Detection Actually Means 00:11:10 An AI-Native Threat in Practice: Hide the Vulnerability 00:13:42 "Our Product Uses AI": Marketing Claim vs. Reality 00:16:21 The Microsoft Copilot Audit-Log Discovery 00:20:10 Visibility, Confidence, and Evaluating Agentic AI 00:24:43 The Limits of Sandboxing 00:26:50 Pulling Back the Curtain on the Vendor Space & MCP 00:31:12 Running Agents in Production & What a Ready Team Looks Like 00:34:29 Where Veteran Security Leaders Fit in an AI-First World 00:36:49 Skills, Hiring, and Where to Start 00:43:01 Rapid Fire 00:45:15 What Zack Is Building Toward & Closing Takeaway   Stay up to date on everything happening in cloud, AI, and security — subscribe to our weekly newsletter at https://www.pluralsight.com/technews/ Connect with Zack Korman: LinkedIn: https://www.linkedin.com/in/zacharyakorman/ YouTube: https://www.youtube.com/@ZackKorman X: https://x.com/ZackKorman Questions or comments? podcast@pluralsight.com  www.pluralsight.com

    AI Threat Detection Is Broken | Zack Korman
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The Pluralsight Podcast is a storytelling platform exploring the rapidly evolving world of technology and learning. Each episode features authentic, human-centered conversations with leaders, luminaries, and changemakers who are shaping the future of tech, guiding organizational transformation, and advancing their own skills and careers.

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