The Pluralsight Podcast

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.

The Pluralsight Podcast is a business podcast hosted by Josh Burkhead, with 15 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Josh Burkhead hosts The Pluralsight Podcast, a business show with 15 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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  The Pluralsight Podcast

  Certified Doesn't Mean Qualified | Andru Estes

  Aug 4, 202642 min

  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

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  The Pluralsight Podcast

  Inside the 100% AI Agent Company | Matt Kropp

  Jul 22, 20261h 2m

  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 also 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

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  Why 'AI-First' is Wrong | Bipasha Ghosh

  Jul 8, 202652 min

  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

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  AI Threat Detection Is Broken | Zack Korman

  Jun 24, 202647 min

  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

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  The Pluralsight Podcast

  Why I Stopped Writing Code | Wayne Hoggett

  Jun 10, 202639 min

  Wayne Hoggett — prolific Pluralsight author of 40+ courses across cloud, Kubernetes, and AI — joins Josh Burkhead to talk about what changes when AI moves from a tool you reach for to something embedded in every part of how you work. Wayne shares a striking admission: despite a heavy cloud-engineering background, he hasn't written code by hand in nearly a year — and what that shift signals for the teams technology leaders are building today. We dig into how the engineering role is being redrawn around AI: why architecture, judgment, and business context are becoming the durable human skills, why cutting junior talent to offset AI spend quietly shuts down your future pipeline, and how leaders should rethink hiring and team design when everyone on the team can generate working code in minutes. Wayne makes the case for building automation-first, AI-first workflows — then deciding deliberately where humans still need to be in the loop. We also get practical on the harder questions: how to prove ROI on AI and L&D investment, how to surface and govern "Shadow AI" instead of banning it, and why self-deployed agentic AI raises the stakes on security, defense in depth, and how fast your team can patch critical systems. Whether you lead a technology org, own an L&D strategy, or are an engineer trying to stay valuable as AI absorbs more of the execution work, this conversation is a grounded look at where the work is actually heading. Topics covered: Redesigning teams and hiring for an AI-first world — and why architecture and business context are the skills that last The real cost of cutting junior talent to fund AI investment, and the talent-pipeline gap it creates Proving ROI on AI and L&D initiatives by starting with low-hanging-fruit workflows Governing "Shadow AI" — enabling the tools your people already use instead of blocking them Securing self-deployed agentic AI: defense in depth, automated patching, and responding fast to new vulnerabilities Chapters: 00:40 Welcome & Guest Intro 01:15 Inside Wayne's World: Learning, Building, Teaching 03:58 Is AI a Natural Fit or a Forced One? 04:39 Don't Skip the Fundamentals: Building T-Shaped Skills 07:01 Linux, Windows, and France's Government Switch 08:31 "I Haven't Written Code in a Year" 10:33 The Moment AI Changed How Wayne Works 12:05 Hiring Entry-Level Talent for Business Awareness 13:37 Fewer Developers? Where the Headcount Logic Breaks Down 14:44 Building Automation-First, AI-First Teams 15:25 What an "AI-First View" Actually Looks Like 16:17 When AI Code Creates More Work Than It Saves 18:38 Rethinking Cloud Expertise on Your Team 20:00 Why Self-Deployed Agentic AI Worries Wayne 21:23 Staying Valuable as an Engineer: Architecture & Patterns 22:32 The Return of the Business Analyst Mindset 25:35 How AI Is Reshaping Cloud Infrastructure Itself 27:19 Shadow IT to Shadow AI: Enable, Don't Block 28:36 Reliability, Determinism, and New Job Titles 32:32 Proving ROI: Start with Low-Hanging Fruit 34:09 Security & the Mythos Headlines: Defense in Depth 36:42 Giving Teams a Safe Sandbox to Experiment 37:59 Closing Thoughts Want more insights on AI, security, and cloud? Subscribe to our newsletters: https://plrsg.ht/3MZ78ya Follow Pluralsight on LinkedIn: https://www.linkedin.com/company/pluralsight/ Wayne Hoggett on Pluralsight - https://www.pluralsight.com/authors/wayne-hoggett Connect with Wayne on LinkedIn: https://www.linkedin.com/in/waynehoggett/ Questions or comments? podcast@pluralsight.com www.pluralsight.com

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