The Pluralsight Podcast

Josh Burkhead

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. Why 'AI-First' is Wrong | Bipasha Ghosh

    1 day ago

    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

    52 min
  2. AI Threat Detection Is Broken | Zack Korman

    24 Jun

    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

    47 min
  3. Why I Stopped Writing Code | Wayne Hoggett

    10 Jun

    Why I Stopped Writing Code | Wayne Hoggett

    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

    39 min
  4. The Human Edge in Cloud Infrastructure | Ned Bellavance

    27 May

    The Human Edge in Cloud Infrastructure | Ned Bellavance

    What does it mean to be irreplaceable on a cloud infrastructure team when AI can write your Terraform, parse your logs, and troubleshoot your architecture — all before your second cup of coffee?   In this episode of The Pluralsight Podcast, Ned Bellavance — infrastructure engineer, Pluralsight author, and host of the Day 2 DevOps podcast — argues that the answer isn't about the tools you know. It's about the judgment, institutional knowledge, and operational experience that no model can replicate. From scripting VMware deployments on a three-person IT team to building reusable Terraform libraries across cloud clients, Ned traces how infrastructure as code evolved and why understanding what's happening underneath the tools has never mattered more.   We dig into where AI genuinely accelerates infrastructure work and where it introduces serious risk — overprivileged credentials, non-deterministic pipelines, and assumptions that only fail once you're in production. We also take a hard look at what leaders are getting wrong right now: cutting junior engineers to offset AI investment costs, undervaluing institutional knowledge that doesn't show up on a balance sheet, and handing AI agents access they were never designed to have responsibly.   Topics covered: Infrastructure as code fundamentals and why declarative thinking changes everything How Terraform shifted Ned's approach to infrastructure work Where AI helps in IaC workflows — and where it creates real risk Why LLMs should never run your deployment pipeline The principle of least privilege applied to AI agents Why institutional knowledge is the hardest thing to replace and the easiest to lose The junior engineer pipeline problem leaders aren't seeing yet Skills to prioritize right now: networking, identity, storage, compute, security, and observability Chapters:   00:02:08 What Is Infrastructure as Code?  00:04:52 From Consulting to IaC: Building Reusable Libraries  00:07:09 Terraform and the Declarative Shift  00:13:05 Where AI Helps (and Doesn't) in IaC Workflows  00:22:53 The Real Risk: AI Agents and Overprivileged Credentials  00:25:59 Why LLMs Should Never Run Your Deployment Pipeline  00:27:02 Infrastructure Engineers as Decision Makers  00:29:28 The Value of Institutional Knowledge  00:31:16 What Leaders Risk When They Cut Experienced Engineers  00:34:43 The Junior Engineer Pipeline Problem  00:41:58 Opportunities in AI Infrastructure for Early-Career Engineers  00:45:11 The IaC Landscape: Terraform, OpenTofu, and What's Coming  00:50:51 Skills to Prioritize Right Now  00:51:49 Final Question: AI Doing More with a Smaller Team  00:52:38 Closing Takeaway 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/ Ned Bellavance on Pluralsight - https://www.pluralsight.com/authors/edward-bellavance  Connect with Ned on LinkedIn: https://www.linkedin.com/in/ned-bellavance/ Check out the Day 2 DevOps Podcast: https://packetpushers.net/podcast/day-two-devops/  Questions or comments? podcast@pluralsight.com  www.pluralsight.com

    54 min
  5. What Good Instruction Really Looks Like | Amy Coughlin

    12 May

    What Good Instruction Really Looks Like | Amy Coughlin

    What does good instruction really look like? Amy Coughlin has authored nearly 50 courses on Pluralsight covering Azure, AI, and cloud architecture — and she's spent years figuring out exactly what makes technical training land versus what makes learners tune out.   In this episode, Amy pulls back the curtain on her approach to course design: why storytelling and real-world experience beat slide decks every time, what organizations consistently get wrong when they try to build training in-house, and why the best instruction is always built around the problem, not the tool.   She also makes a sharp distinction that every L&D and technology leader should hear: AI chat tools are task tools, not learning tools. And confusing the two has consequences.   In this episode: What separates instruction that sticks from training that gets forgotten Why themes, stories, and even corny puns make technical content more effective The hidden risks of pulling your best SMEs to run internal training What AI sycophancy means for developers who rely on it too heavily Why focusing on the problem, not the tool, is the future of content design   Chapters: 2:03 — Amy's unconventional path into tech 7:13 — From data platform architect to course author: how Amy found her calling 9:52 — Making complex cloud topics relatable: themes, storytelling, and board games 12:19 — Real-world examples and the value of learning from mistakes 14:15 — What makes good technical content stick (and what falls flat) 18:25 — The human touch in learning: why podcasts and infotainment still win 21:23 — Hands-on labs and why doing beats reading 22:37 — Why organizations struggle when they try to build training in-house 25:48 — Hidden risks of using internal SMEs as instructors 28:08 — Tech debt, vibe coding, and the real cost of underskilled teams 30:24 — Is AI a legitimate learning tool? The sycophancy problem explained 34:55 — The future of content delivery: problem-focused, short-form, and refreshable 37:26 — Advice for parents opening doors to tech careers for their kids 41:11 — Closing thoughts and how to find Amy on Pluralsight 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/ Amy Coughlin on Pluralsight - https://www.pluralsight.com/authors/amy-coughlin  Connect with Amy Coughlin on LinkedIn: https://www.linkedin.com/in/amy-coughlin-07300b44/  Questions or comments? podcast@pluralsight.com  www.pluralsight.com

    42 min
  6. Foundations for AI Success | Faye Ellis

    28 Apr

    Foundations for AI Success | Faye Ellis

    Most organizations are excited about AI. Far fewer are actually ready for it. In this episode of The Pluralsight Podcast, host Josh Burkhead sits down with Faye Ellis — AWS Hero and Pluralsight Author Fellow, cloud architect turned educator, and AI upskilling strategist — to talk about what separates organizations that are stuck in AI curiosity mode from those that are building real, measurable capability. Faye brings a practitioner's perspective to some of the most pressing questions in L&D and technology leadership today: How do you close skills gaps when the technology keeps moving? How do you bring non-technical teams along without losing them? And why are 80% of AI pilots still failing to reach production — even as investment in AI continues to climb? Whether you're leading an L&D function, managing a technology team, or trying to figure out where to even start with AI upskilling, this conversation is packed with frameworks and honest perspectives you can take back to your team. In this episode: Why fear is not an AI strategy — and what to do instead How to move from AI curiosity to a skills-first, outcome-driven program The case for AI literacy at every level of the organization, not just technical teams What a successful upskilling program actually looks like in practice Why the organizations getting it right treat learning as a continuous journey, not a project   Chapters: 00:01:08 — From Data Centers to AI: Faye's Career Journey 00:04:07 — What Got Her Hooked on Teaching 00:05:41 — The AI Curiosity Trap: Why Organizations Stay Stuck 00:09:21 — What It Looks Like When Strategy Clicks 00:12:53 — Running a Skills Gap Analysis in a Moving Target Environment 00:15:13 — Including Non-Technical Teams in the Talent Pipeline 00:18:31 — Building a Program That Actually Works 00:21:07 — Connecting Learning to Business Outcomes 00:26:13 — Designing for Confidence, Not Just Competence 00:31:22 — Scaling a Learning Culture Without Letting It Fizzle 00:37:00 — Trust as the Hidden Driver of Upskilling Success 00:41:02 — What Leaders Are Still Getting Wrong About AI Literacy 00:44:20 — Rapid Fire: Myths, Hard Truths, and One Thing in Common 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/ Connect with Faye Ellis on LinkedIn: https://plrsg.ht/420lS3W  Questions or comments? podcast@pluralsight.com  www.pluralsight.com

    46 min
  7. Your AI Needs a Reviewer | Maaike Van Putten

    15 Apr

    Your AI Needs a Reviewer | Maaike Van Putten

    What does it take to write code that's actually ready for an AI-powered world — and what happens when it isn't? In this episode of The Pluralsight Podcast, Maaike Van Putten — software developer, Pluralsight author, and instructor known for making technical concepts genuinely approachable — makes the case that clean code has never mattered more than it does right now. Not because the standard has changed, but because AI can generate bad code faster than ever before, and someone has to catch it. Maaike traces that argument back to a practical reality: as AI takes on more of the writing, the job of the developer increasingly becomes the job of the reviewer. From there, she breaks down why functions that do too many things are the silent killer of maintainable codebases, what the "driving fast" analogy reveals about the relationship between speed and code quality, and why AI should be treated as a teammate — not an authority — before you let it anywhere near data you can't afford to lose. We also get into why the entry bar for junior developers has shifted dramatically, how a brag document can be a genuine defense against imposter syndrome, and what scheduling "tech dates" actually looks like when you're trying to protect learning time in a world that never stops demanding more of it. If you're early in your development career, leading a team of developers, or just trying to figure out how to work alongside AI without letting it work against you — this conversation is a grounded, practical look at the habits and mindsets that hold up across every wave of change.   Chapters: 03:12 Why the Entry-Level Developer Market Is Struggling Right Now  05:51 Clean Code: Why Small Habits Make or Break a Developer  08:40 Why Code Quality Matters More in the AI Era  10:21 What Happens When a Team Isn't Aligned on Standards  11:16 AI as a Teammate, Not an Authority: Lessons from a Hard Drive Wipe  13:09 What Leaders Should Consider Before Deploying AI in Development  14:15 Vibe Coding vs. Agentic Coding: Is There a Difference?  14:34 Why Reading Code Is Now More Valuable Than Writing It  16:20 How to Schedule and Protect Learning Time (Tech Dates)  18:33 How to Ask Your Manager for Learning Time  19:30 Beating Information Overload: Focus on Fundamentals  21:47 The Brag Document: Fighting Imposter Syndrome with Evidence  24:51 How to Share Your Work Without Feeling Exposed  26:35 What Motivated Maaike to Start Teaching and Creating Content  27:58 Skills Young Developers Are Overlooking Right Now  30:03 Maaike's 2026 Goals & Upcoming Book: *Illustrated Python*  📖 Illustrated Python by Maaike Van Putten — available now on Amazon: https://a.co/d/0dSvCYrR 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/ Connect with Maaike Van Putten on LinkedIn: https://www.linkedin.com/in/maaikevanputten/ Questions or comments? podcast@pluralsight.com  www.pluralsight.com

    33 min
  8. Skills First, Roles Second | Jose Ramirez

    1 Apr

    Skills First, Roles Second | Jose Ramirez

    What if the reason your AI adoption isn't working has nothing to do with the technology — and everything to do with how you prepared your people? In this episode of The Pluralsight Podcast, Jose Ramirez — L&D strategist and former research analyst who spent a decade advising CIOs on building high-performing tech teams — makes the case that most organizations are solving the wrong problem. It's not a tools problem. It's a skills problem. And until leaders make learning part of the job instead of a break from it, no amount of AI investment will move the needle. Jose traces that argument back to a simple but powerful reframe: the difference between building AI tool adopters and building AI value creators. From there, he breaks down why a skills-first approach makes teams more resilient than role-based hiring, how the best tech leaders use storytelling to win over skeptical stakeholders, and why handing employees a new AI tool without context or strategy is one of the most expensive mistakes a leader can make right now.   We also get into how to measure the real impact of upskilling beyond completion rates, why career mobility is the most overlooked metric in any L&D program, and what it looks like when a learning culture is actually working.   If you lead technology teams, learning programs, or both — this conversation is a practical and honest look at what it takes to close the skills gap before it's too late.   Chapters: 00:57 Welcome & guest introduction 01:43 Jose's career as an industry analyst 02:48 What CIOs still misunderstand about skill strategy 03:32 Skills first, roles second: the puzzle piece analogy 06:58 Where organizations stumble adopting a skills-first approach 08:49 Aligning a learning culture to specific outcomes 11:14 Storytelling as a core leadership competency 13:05 Anatomy of a persuasive story: the hook and the transformation 15:26 How leading with data derails a good strategy 16:43 Preparing people, not just systems: AI literacy 18:43 The risk of handing out AI tools with no strategy 20:42 Work redesign and employee autonomy 22:53 Sharing success stories to drive adoption 25:31 Modernizing legacy systems without losing critical knowledge 27:54 Career portfolios over career ladders 28:38 Building internal capabilities as AI reshapes skills 33:34 Measuring real business impact beyond usage metrics 39:18 Career mobility and connecting talent to business outcomes 39:54 Closing questions: what's top of mind for 2026 40:54 Wrap-up & where to find Jose   Want more insights on Security, Cloud, and AI? Subscribe to our newsletters: https://plrsg.ht/3MZ78ya Connect with Jose Ramirez on LinkedIn → https://www.linkedin.com/in/joseramirez5/ Questions or comments? Email → podcast@pluralsight.com Website → https://plrsg.ht/4rlhB5m Subscribe to our channel and hit the notification bell to stay up to date with the latest tech career and interview insights from Pluralsight → https://plrsig.ht/subscribe

    42 min
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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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