Root Cause

About Root Cause

Everyone talks about the future of tech. Few talk about the consequences. ROOT CAUSE brings together senior operators. Engineers, DevOps leaders, founders, former CTOs. To dissect the real stories behind big technical decisions. What happens after the migration? After the pivot? After the AI integration? Our show is dedicated to answering what nobody tells you about scaling systems, what nobody tells you about leadership or the vicious hype cycles. If you’ve built, broken, fixed, and rebuilt systems at scale, this show is for you. Let’s root cause this.

Publisher

Nune

Category

business · technology

Language

en

Explicit

No

First episode

11 May 2026

Latest episode

27 Oct 2026

Latest episodes

11 episodes in the feed.

1. 

   27 Oct 2026

   Adopting Kubernetes, Then AI: Who Ends Up Running It?

   Before you let anyone talk you into changing your whole SDLC, ask whether you really need Kubernetes. Your own team is probably the one that will have to take care of it. In this episode of Root Cause I sit down with Markus Döpke, senior solutions architect at AWS in Germany, who helps software companies build their SaaS offerings and adopt Kubernetes. We get to the root cause of what happens when an organization adopts a technology it will have to run itself, and why AI is following the same pattern. Markus explains when Kubernetes is justified: scaling a SaaS business, entering a new region, experimenting faster. He also tells the story of when it wasn't, at a small software company that a delivery partner talked into it. Two years later they went back to virtual machines. We then get into platform engineering through Team Topologies. Stream-aligned teams create the value, and every other team exists to remove their bottlenecks. We sort out the terminology: stream-aligned teams, platform teams, pizza-size teams, you build it, you run it. Markus shares a story from his time as a CTO, when outages came from mental load, not missing access rights. We also ask whether a platform team has to create a knowledge gap, how to keep it from becoming a magnet for work nobody wants, and how to justify a team that doesn't ship features. The same mental model applies to AI. We talk about why buying Claude Code subscriptions isn't adoption, and why to start with AI in the places you already understand. We cover Markus's idea of a driving license for AI agents in production, why learning matters more now, and what happens to juniors and the value of human work when nobody hires them. We close with why achievements deserve to be celebrated, even the small ones inside a large company. 00:00 Introduction of the Episode and the Guest 02:23 Day Zero: Why Enterprises Adopt Kubernetes 04:30 Who Decides? Business Goals vs Resume-Driven Development 05:34 When You Don't Need Kubernetes: Two Years In, Then Back to VMs 08:06 Kubernetes as a Platform for Experimentation 10:28 Do You Need a Platform Team? 11:21 Team Topologies: Four Team Types 13:43 Stream-Aligned Teams and Their Satellites 15:18 You Build It, You Run It: Mental Load, Not Access Rights 18:52 Do Platform Teams Create Knowledge Gaps? 22:33 Is the AI Knowledge Gap Actually New? 25:56 It's a Platform Group, Not a Team 28:44 Justifying Platform Teams to Management 30:19 AI Raises the Stakes: Systems That Manipulate State 32:38 "We Bought Claude Code Subscriptions": Is That Enough? 33:57 From AI in the IDE to Pipelines That Build Software 36:48 A Driving License for AI Agents in Production 38:51 What Happens to Juniors? 40:59 Data Privacy and Sovereign Cloud in the German Market 43:54 Recap 44:37 Book Recommendations 47:48 Question from John Gallagher: The Most Powerful Emotion 50:26 Why Achievements Deserve to Be Celebrated 53:07 Question for the Next Guest and Closing Find Markus at: LinkedIn - https://www.linkedin.com/in/m9e/ (https://www.linkedin.com/in/m9e/) Find me (Nune) at: LinkedIn: https://www.linkedin.com/in/nisabek/ (https://www.linkedin.com/in/nisabek/) Substack: https://www.thoughtfultechnologist.com/ (https://www.thoughtfultechnologist.com/)

2. 

   13 Oct 2026

   If everyone can build software, what decides who survives?

   If everyone can build software now, what actually decides who survives? John Gallagher, Principal Engineer at Dynatrace and author of Software Design Simplified, says culture. In this episode of Root Cause we get to the root cause of what that word actually means, and why AI just made it ten times more important. John has spent over 20 years in software, from assembly on microcontrollers to a decade of Ruby on Rails in production, and he lived through the incident we have all had: the app is down, the people who could help are asleep in another time zone, and the logs tell you nothing. He spent the next 18 months changing how his team saw its own system. Downtime dropped 98%. Then he cut the observability bill the new enthusiasm had created. We dig into why 2,000 engineers with AI still move like 2,000 engineers (Conway's law did not get repealed), the anti-pattern that refuses to die ("we know what the customer wants, we built it"), and the paradox of founders: selfish enough to start a company, humble enough to remember you are solving somebody else's problem. John makes the case that a software company is not a factory stamping out features, and that if you deleted 80% of the features in most products, the software would get better. We get nostalgic about a 2 MB Amiga game on a 1.5 MB machine and what that obsession taught him about debugging, why group think starts with an emotion, and his three ingredients for learning critical thinking if nobody taught you as a kid: obsession, a small feedback loop, and for goodness sake, don't read a book. Plus the book recommendation he refused to tell me before we hit record. 00:00 Introduction of the Episode and the Guest 02:49 Is the AI SRE Market Flooded Because of AI or Because of OpenTelemetry? 07:46 Big Vendors Move Fast Now Too: Can Startups Still Compete? 13:46 Bureaucracy Is Not Good or Bad, It Is the Nature of the Beast 17:48 The Anti-Pattern That Never Dies: "We Know What the Customer Wants" 21:34 Founder Ego: Selfish Enough to Start, Humble Enough to Listen 25:14 Culture Is Now 10x More Important (and the Best Product Does Not Win) 29:11 A Software Company Is Not a Feature Factory 31:36 Rework: Just Let Me Use the Software 36:37 From Floppy Disks to AI: Is This the Same Kind of Revolution? 38:16 Hired Guns on a 1.5 MB Amiga: One Book, No Internet, Pure obsession 47:24 Neither Skeptic Nor Enthusiast: Subsidized Tokens and the Coming Shock 49:53 All Priors Are Gone: Relearning Everything After 20 Years 53:07 Did We Waste a Year Tinkering With AI Tools? 57:31 Invest in Things That Don't Change: Feedback Loops All the Way Down 01:01:51 "It's Definitely a Race Condition in Redis": How Engineers Handle Being Wrong 01:04:36 How to Learn Critical Thinking: Obsession, a Small Feedback Loop, and Don't Read a Book 01:07:57 The Painting Class and the Tennis Court: Emotions as a Feedback Loop 01:10:18 Group Think Starts With an Emotion, and Many More Much Smaller Steps 01:14:30 Book Recommendation: The Psychology of Software Teams 01:19:22 Question from Tamanna Haque and Question for the Next Guest 01:26:24 Closing Find John at: Joyful Programming: https://www.joyfulprogramming.com (https://www.joyfulprogramming.com) LinkedIn: https://linkedin.com/in/synapticmishap (https://linkedin.com/in/synapticmishap) Find me (Nune) at: LinkedIn: https://www.linkedin.com/in/nisabek/ (https://www.linkedin.com/in/nisabek/) Substack: https://www.thoughtfultechnologist.com/ (https://www.thoughtfultechnologist.com/)

3. 

   24 Aug 2026

   Root Cause of Visibility in the Age of AI

   What is Generative Engine Optimization (GEO), and does it replace SEO? In this episode of Root Cause we get to the root cause of what happens to being findable when people stop Googling and start asking ChatGPT, Gemini or Perplexity. With search engines, a human picks from a list of results. With AI search, the model gives one answer and one recommendation, and if you are not in it, you are not in the consideration set. That shift is what GEO (also called AI search optimization or AI visibility) is trying to address. We cover GEO vs SEO and why good SEO is only a subset of AI visibility; the what, where and how of AI-readable content (which topics, which sites like Reddit, G2 and Capterra AI trusts, which formats); whether GEO feeds the AI slop machine (AI-generated content is no more readable to LLMs than human writing, and three purposeful articles beat ten); how fast-changing models affect what you optimize; why millennials using ChatGPT as a search engine and Gen Z using it as a companion are two different problems for a brand; B2B vs B2C vs creator use cases; and the fairness question of manufacturing a persona that ranks above the better product. Then the technical part: how you get a deterministic, credit-score-style AI visibility score out of non-deterministic LLMs, why the LLM should be a data extractor and never a grader, and practical GEO advice for content creators (know your proposition, get cited where AI trusts, transcribe your videos, and yes, bring back the blog). My guest is Tamanna Haque, mathematician, lead data scientist with a decade of production AI on real customer data, and co-founder of GenSight.AI (http://GenSight.AI), a GEO platform she built in her personal time with her husband Jonas. This is her first public conversation about it, and I came in openly skeptical. 00:00 Introduction of the Episode and the Guest 02:56 Why Build a GEO Product in the Evenings: Eating Your Own Dog Food 06:08 What Is Generative Engine Optimization? 07:21 GEO vs SEO: Being an Option vs Being the Answer 10:48 The What, the Where and the How of Being Visible to AI 11:51 Does GEO Feed the AI Slop Machine? 15:05 Models Change Fast: Optimize Once or Forever? 17:02 Millennials Search, Gen Z Chats: Two Different Problems 20:46 B2B vs B2C vs Creators: Who Benefits Most? 22:35 Manufacturing a Persona: Who Deserves the Top Spot? 26:58 Deterministic Scores from Non-Deterministic Models 29:39 The LLM as Data Extractor, Never a Grader 31:44 Free Advice for Creators: Know Your Proposition, Bring Back the Blog 36:09 Book Recommendation: Harry Potter 38:05 Question from Fraser Merrifield: Top Movies 39:46 Question for the Next Guest: Which Pet Would You Have? 40:38 Closing Find Tamanna at: GenSight.AI (http://GenSight.AI) - https://gensight.ai (https://gensight.ai) Find me (Nune) at: LinkedIn: https://www.linkedin.com/in/nisabek/ (https://www.linkedin.com/in/nisabek/) Substack: https://www.thoughtfultechnologist.com/ (https://www.thoughtfultechnologist.com/)

4. 

   10 Aug 2026

   The Root Cause of Not Getting Hired

   In this episode of Root Cause we sit down with Fraser Merrifield, founder of FORM Careers in Glasgow and the self-described craft brewer of digital recruitment, to get to the root cause of the gap between what the hiring market says it wants and what it actually rewards. Fraser spent over a decade placing engineers in oil and gas, then bet on software in his late 30s, went fully solo, and now runs deliberately small on what he calls bullshit-free recruitment. He barely reads CVs anymore, and he'll tell you why a perfect one makes him suspicious. We dig into why AI has made both hiring and getting hired harder while most of the horror stories stay myths: his clients average two interview stages, and the CV-rejecting AI mostly doesn't exist. Fraser explains the 12-month window on the "AI-native engineer" hype, what happens when an engineer burns through more in tokens than their salary, and why leaning on senior hires is the same mistake that left oil and gas with a talent shortage. And the story that sums up the whole market: 200 applications for one graduate role, one candidate picked up the phone, and he got the job, as the only person interviewed. Three years later he is still there. 00:00 Cold Open: Six Yes/No Claims About the Job Market 00:41 Introduction of the Episode and the Guest 03:35 Writing Like a Human: Pop Culture and Starting in Lockdown 05:56 Five Views or Five Million: How to Read Your LinkedIn Visibility 07:45 Everyone's CV Is Perfect Now, So What Stands Out? 09:23 The Online Mood Hoover: Positivity vs Ranting 12:22 The Blitz Round: Yes or No 13:06 Why AI Made Both Hiring and Getting Hired Harder 14:48 Just Another Hype Cycle? The 12-Month Window 16:11 When Engineers Burn More in Tokens Than Their Salary 17:53 Eight-Stage Interviews: Would You Even Want That Job? 20:36 Can Bullshit-Free Recruitment Scale? 22:06 CVs After AI: Rejecting the Quick-Appliers, Rewarding the Extra Mile 25:25 One of 200 Applicants Picked Up the Phone. He Got the Job 27:06 Glasgow AI and the Return of Offline Networking 29:10 The Undercurrent of Real People on LinkedIn 31:18 How Fraser Actually Uses AI (and How It Argued Back) 37:38 Fraser Flips the Script: The Most In-Demand Skill in Five Years 43:21 Juniors vs Seniors: The Oil and Gas Warning 46:11 Asking About Training Without Entitlement 47:17 Question from Evan Marshall: When Are We Getting Robots? 52:14 Question for the Next Guest: Top Five Movies 52:45 Movie Recommendations: Her, Ex Machina, Transcendence 54:24 Closing Find Fraser at: • LinkedIn - https://www.linkedin.com/in/fraser-merrifield-7b54524/ (https://www.linkedin.com/in/fraser-merrifield-7b54524/) • Form Careers - https://weformcareers.com/ (https://weformcareers.com/) • Glasgow AI Meetup - https://www.meetup.com/meetup-group-xnqxwqzu/ (https://www.meetup.com/meetup-group-xnqxwqzu/) Find me (Nune) at: LinkedIn: https://www.linkedin.com/in/nisabek/ (https://www.linkedin.com/in/nisabek/) Substack: https://www.thoughtfultechnologist.com/ (https://www.thoughtfultechnologist.com/) Envimate: https://envimate.com/ (https://envimate.com/)

5. 

   27 Jul 2026

   Root Cause of Where You Are on the AI Spectrum

   In this episode of Root Cause we sit down with Evan Marshall, co-founder and CTO of Ito.ai, to get to the root cause of where the honest answer sits on the AI adoption spectrum, somewhere between the teams that won't let AI near their codebase and the ones that let it ship with barely a human in the loop. Most of us are somewhere in the middle, moving around and quietly wondering if we've got it right. This conversation is meant to help you gauge where you actually are, and where you want to be. Evan studied computer science at MIT and spent four years building privacy infrastructure for zero-knowledge blockchains, where a slipped bug is a disaster. That experience pushed him toward quality: he now builds a QA agent that actually runs your application and checks the code before it merges. We dig into the pressure on Bay Area companies to claim a "software factory" while their engineers might still be shipping like everyone else, why free code generation can at most double you if coding was half your job (and it never was), and the plastic age of coding, where code is generated to be thrown away. Evan shares what a sane monthly AI spend actually looks like and his advice for integrating AI into your software development lifecycle: treat the SDLC as an optimization problem, because once generation is free, the bottleneck moves to verification and quality control. And when someone says "I can just do that with Claude Code", the work that follows is environments that have to heal themselves, caching that breaks on the next migration, and memory layers. As Evan puts it: we spent the tokens so you don't have to. 00:00 Pre-show Banter and the Cats 00:59 Introduction of the Episode and the Guest 03:00 Is the Bay Area Really an AI Echo Chamber? 05:45 The Pressure to Claim a Software Factory 07:36 How Much Does AI Actually Speed You Up? 10:23 How Ito Uses AI in Its Own Engineering 14:13 The Plastic Age of Coding 15:53 Can the Software Factory Be Productized? 18:39 Subscriptions vs API: The Real Cost of Tokens 20:19 Open Models and Switching Between Them 21:25 Are the Models Plateauing? 22:59 "I Can Just Use Claude Code": Where the Hard Parts Hide 26:19 The Bottlenecks You Don't See: Environments, Caching, Memory 28:55 Will QA Engineers Be Replaced? 31:39 Replicators, Waymos, and 3D Printers: Why Change Takes Time 36:49 Why SaaS Isn't Dead and How Much You Should Spend 39:23 Advice for Integrating AI into Your SDLC 42:50 Question from Barry O'Reilly: Building a Computer in 1822 44:31 Shared Reality, Social Media, and Cooperation 50:25 Book Recommendations 53:54 Question for the Next Guest and Closing Find Evan at: • LinkedId: https://www.linkedin.com/in/evan--marshall/ (https://www.linkedin.com/in/evan--marshall/) • his startup - https://www.ito.ai/ (https://www.ito.ai/) Find me (Nune) at: LinkedIn: https://www.linkedin.com/in/nisabek/ (https://www.linkedin.com/in/nisabek/) Substack: https://www.thoughtfultechnologist.com/ (https://www.thoughtfultechnologist.com/)

6. 

   13 Jul 2026

   Root Cause of Architectural Thinking

   In this episode of Root Cause we sit down with Barry O'Reilly, 25 years in software architecture, former chief architect at Microsoft, startup CTO, and the creator of Residuality Theory, to get to the root cause of what senior architects actually do when they say they run on gut feeling. When Microsoft asked Barry to teach junior architects how he did his job, he discovered he couldn't describe his own methods, and neither could any of the senior architects he asked. That frustration turned into two books and a PhD in complexity science. We dig into why a random simulation of stress produces architectures that survive events nobody predicted, why equirements and risk management quietly limit the very thinking they were supposed to support, why our industry spreads ideas through charisma instead of scientific proof, and whether an LLM can ever produce an architecture. If you've ever been told "that's just experience," this episode puts words on it. 00:00 Cold Open: The Architect vs the Implementer 02:06 Guest Introduction: Structuring the Magic 03:00 Pure Mathematics: Help or Trap? 06:20 Think Less, Do More? The Industry's Thinking Problem 09:09 Why Software Isn't Developing as a Science 12:26 Pop Culture, Gurus, and the Hype Machine 15:09 "My Industry Is Low Stakes": Why Quality Still Pays 17:54 Two Books That Decide If You're an Architect 22:09 Creativity vs Craft: Naming the Magic 25:39 Residuality Theory: The Marbles Analogy 31:59 How to Start: The Naive Architecture and Random Stress 36:35 Attractor States: Why Stressing Works 39:30 All Architecture Is Stress 44:14 The Trouble with Non-Functional Requirements 48:49 Should Architects Become Domain Experts? 52:02 Does This Apply to Small Systems and Startups? 57:36 Answering the Critics: "We've Always Done This" 01:01:28 Stressor Analysis: Architecture Never Stops 01:04:57 Shared Language and Reflective Practice 01:07:04 Has AI Made Code Cheaper? 01:12:54 Can LLM Agents Do Residuality? 01:18:43 The Walk Around the Problem Is the Point 01:20:40 First Steps into Residuality 01:25:18 Book Recommendations 01:29:39 A Benign Pride: Fly Fishing at 34 Meters 01:32:01 Question for the Next Guest and Closing Find Barry at: • LinkedIn: https://www.linkedin.com/in/barry-o-reilly-b924657/ (https://www.linkedin.com/in/barry-o-reilly-b924657/) • Barry’s first book: https://leanpub.com/residuality (https://leanpub.com/residuality) • Barry’s second book: https://leanpub.com/architectsparadox (https://leanpub.com/architectsparadox) • The intro talk you should watch: https://www.youtube.com/watch?v=_MPUoiG6w_U (https://www.youtube.com/watch?v=_MPUoiG6w_U) Find me (Nune) at: * LinkedIn: https://www.linkedin.com/in/nisabek/ (https://www.linkedin.com/in/nisabek/) * Substack: https://www.thoughtfultechnologist.com/ (https://www.thoughtfultechnologist.com/)

7. 

   29 Jun 2026

   Root Cause of a Healthy Team

   In this episode of Root Cause we sit down with Eric Lubow, a CTO who treats organizations like distributed systems, which means the root cause of a broken team is usually a design problem, not a people problem. Eric has spent more than 20 years building and repairing teams and platforms, from co-founding SimpleReach to running engineering through dozens of acquisitions at Thrasio, and he is now Chief Product and Technology Officer at Mapp. He is also a jiu-jitsu coach, and that shapes how he leads. We get to the root cause of what actually makes a team healthy, why becoming a manager means changing your definition of done, and why ceding control is the part nobody warns you about. We talk about leading AI agents the way you would lead a person, why silent heroes quietly turn into silent burnouts, and how to hire into a team instead of into a vacuum. Honest and specific, with none of the leadership-content platitudes, including the lonely parts of the job most people at the top never say out loud. 00:00 Introduction: What Makes a Healthy Team 03:05 Jiu-Jitsu, Languages, and a Healthy Ego 08:23 Martial Arts, Balance, and "Everything Is Maintenance" 13:12 Teams as Distributed Systems and Conway's Law 16:38 The IC-to-Manager Transition: Ceding Control 19:10 Delegation and a New Definition of Done 22:24 Giving Away Your Legos 23:49 Can You Learn to Be a Manager? 25:21 Don't Just Become the Opposite of Your Bad Manager 27:54 Leading AI Agents Like You Lead People 31:55 Will AI Replace People? Force Multiplier, Not Replacement 36:45 What Actually Makes a Team Healthy 38:56 Adoption Curves and Why Teams Mimic Leaders 42:06 A Culture of Sharing vs Shadow IT and Shadow AI 47:41 The Hero Problem: Silent Heroes, Silent Burnout 53:20 Burnout, Boundaries, and Trusting the Team 55:33 Hiring Into a Team, Not a Vacuum 1:02:15 The Loneliness of Leadership 1:06:48 Why "I Don't Know" Is a Sign of Strength 1:09:13 Book Recommendations: Sci-Fi and Leadership 1:13:49 What Eric Would Tell His Younger Self 1:15:45 The Most Benign Thing You're Proud Of Find Eric at: • Linkedin: https://www.linkedin.com/in/eblubow/ (https://www.linkedin.com/in/eblubow/) • His blog: https://eric.lubow.org (https://eric.lubow.org) (which heavily influenced this episode) • Beyond the Belt podcast: https://www.youtube.com/@beyondthebeltpod (https://www.youtube.com/@beyondthebeltpod) Find me (Nune) at: LinkedIn: https://www.linkedin.com/in/nisabek/ (https://www.linkedin.com/in/nisabek/) Substack: https://www.thoughtfultechnologist.com/ (https://www.thoughtfultechnologist.com/)

8. 

   22 Jun 2026

   Root Cause of Solopreneur Success: Before, During, and After AI

   In this episode of Root Cause we sit down with Orel Zilberman, the solo builder behind WriteStack, the biggest tool out there for Substack creators. Orel spent 599 days shipping around ten products that made zero dollars, then picked one thing, stuck with it for six months, and turned it into a six-figure business. He has lived three versions of solo building in three years: before the current AI tooling, as it arrived, and now. We get to the root cause of what AI actually changed for one-person companies and what it didn't. Building got faster, but knowing what to build, and sticking with it long enough to find out if it works, is exactly as hard as it always was. Honest and unfiltered, including the messy parts most "become an entrepreneur" content leaves out. 00:00 Introduction to Root Cause and Solo Building 04:57 The Journey of Building WriteStack 06:42 What is SubStack and WriteStack? 09:28 "Why Bother" if the platform / big players will replace you 13:14 "Why bother" if AI will replace all SaaS 14:46 Knowing WHAT to Build and How to Distribute 18:30 Finding the Right Idea to Stick With 23:22 Learning from Opportunities and Failures 26:10 Navigating the Cold Start Problem 28:10 Leveraging AI Tools for Productivity 30:49 The Future of Software Engineering in the Age of AI 33:53 Advice for Aspiring Entrepreneurs 37:20 Being Better Than Most 38:49 Book Recommendations and Lifelong Learning 41:04 Reflections on Education and Career Choices Find Orel at: • His product - https://www.writestack.io/ (https://www.writestack.io/) • His journey - https://theindiepreneur.substack.com/ (https://theindiepreneur.substack.com/) • Substack notes analysis - https://thewritingedge.substack.com/ (https://thewritingedge.substack.com/) • Substack profile - https://substack.com/@orelzilberman (https://substack.com/@orelzilberman) Find me (Nune) at: LinkedIn: https://www.linkedin.com/in/nisabek/ (https://www.linkedin.com/in/nisabek/) Substack: https://www.thoughtfultechnologist.com/ (https://www.thoughtfultechnologist.com/)

9. 

   9 Jun 2026

   The Root Cause of Wanting to Learn

   In this episode of Root Cause we sit down with Ia Mg - seasoned engineer, former CS and digital literacy teacher at the Free University of Tbilisi, and the author of the blog Bits Complicated - to get to the root cause of learning itself, and whether the machines we've built are about to make us better at it or worse. We dig into why everyone should understand technology even if they never write code, why domain knowledge has always mattered more than programmers wanted to admit, and what happens to learning when the answer is always one prompt away. Along the way: tech debt as a tax instead of a failure ("legacy as a service"), the "learning debt" that builds every time you accept a ready-made answer, why conversation-based coding is a process problem and not just an output problem, and why learning might be the most rebellious thing you can still do for yourself. 00:00 Guest intro and episode goal 02:45 Teaching Programming to Non-Coders 04:13 The Importance of Technology Literacy 09:41 AI and the Future of Programming 16:10 AI as a Teacher of Programming 22:16 Evaluating AI Responses in Learning 26:49 Concerns About the Next Generation 30:08 AI as an Abstraction in Programming 33:40 Conversational Development vs. Traditional Coding 37:34 Understanding Tech Debt 42:09 Learning Debt in the Age of AI 45:06 AI is the next social network? 46:47 Embracing the Chaos of Innovation 47:59 The Joy of Coding vs. AI 53:22 Navigating the Job Market in Tech 57:30 Book Recommendations 01:02:08 Summary of the Discussion 01:02:41 Learning as a Rebellious Act 01:04:09 Practical Recommendation on using AI consciously 01:06:21 Engineering is more than coding Find Ia at: Blog: https://iyamg.com/bitscomplicated/ (https://iyamg.com/bitscomplicated/) LinkedIn: https://www.linkedin.com/in/ia-mgvdliashvili-0b459768/ (https://www.linkedin.com/in/ia-mgvdliashvili-0b459768/) Find me (Nune) at: Blog: https://www.thoughtfultechnologist.com/ (https://www.thoughtfultechnologist.com/) LinkedIn: https://www.linkedin.com/in/nisabek/ (https://www.linkedin.com/in/nisabek/)

10. 

    26 May 2026

    The Root Cause of Never Learning

    In this episode of Root Cause we sit down with Adrian Hornsby — former AWS Principal Engineer, founder of Resilium Labs, and author of Why We Still Suck at Resilience — to get to the root cause of what's quietly breaking inside engineering organizations as AI absorbs more of the thinking. We dig into the gap between how we imagine our systems work and how they actually work, why that gap is where all the real learning lives, and what happens to a team when the thinking itself gets delegated to something that sounds confident but doesn't know which walls are load-bearing. 00:00 Pre-show Banter and the Dog 01:08 Introduction of the Episode and the Guest 05:00 What's Wrong with the Name of the Show 07:35 The Importance of Learning from Successes 09:53 Defining Work as Imagined and Work as Done 13:43 Leading vs Being Hands-On 28:49 Learning From the Gap 30:39 Chaos Engineering 31:31 Load Testing 32:50 Game Days 34:00 ORRs - Operational Readiness reviews 34:41 Learning From the Incident 36:25 How AI has Affected the Gap 41:57 Navigating the Complexity of AI Delegation 43:45 Skill Atrophy and the New Generation of Engineers 47:12 Building Tools That Keep You Smart 52:18 We Need a Crisis to Slow Down 58:30 Building Intuition in AI-Driven Systems 01:03:17 The Human Touch in Technology 01:07:32 Facing Fears and Embracing Change 01:16:28 Question for the Next Guest and Closing Adrian has generously decided to run a discount with the promocode “rootcausebynune” - for the first 30 copies you can buy his book for as low as 14.99 - that’s over 70% discount over the suggested price! https://leanpub.com/whywestillsuckatresilience/c/rootcausebynune (https://leanpub.com/whywestillsuckatresilience/c/rootcausebynune) Find Adrian at: Resilium Labs: resiliumlabs.com (http://resiliumlabs.com) LinkedIn: https://www.linkedin.com/in/adhorn/ (https://www.linkedin.com/in/adhorn/) Substack: https://newsletter.resiliumlabs.com/ (https://newsletter.resiliumlabs.com/) Find me (Nune) at: LinkedIn: https://www.linkedin.com/in/nisabek/ (https://www.linkedin.com/in/nisabek/) Substack: https://www.thoughtfultechnologist.com/ (https://www.thoughtfultechnologist.com/)

11. 

    11 May 2026

    Who's Speaking for the Experts?

    In this very first episode of Root Cause we sit down with Marc Babin - an award-winning digital marketing professional and creator of over a dozen of podcasts - to get to the root cause of personal branding - why it matters more than ever and how a busy professional who doesn't like the empty talks can survive the content noise and still make themselves visible. 00:00 Show and Guest Introduction 02:54 The Value of Authentic Content in a Noisy World 06:18 AI and Content: Good Authentic Content is King 09:47 Reel-Thinking vs Podcast Creation 13:57 Creating Engaging Content in Niche Markets 18:14 Sales vs. Marketing: Building Trust Through Content 22:02 The Long Game in Content Creation 25:48 Personal Branding in the Digital Age 28:28 Setting Up for Success in Content Creation 33:05 Overcoming Perfectionism in Content Creation 38:27 Embracing the Silence of Early Content 43:29 Navigating Privacy and Online Presence 48:36 The Discomfort of Starting 53:14 The Root Causes of Expert Silence 57:53 How to Start Creating Content 01:00:30 Question for the Next Guest and Closing Follow Marc Babin: LinkedIn - https://www.linkedin.com/in/babinmarc/ (https://www.linkedin.com/in/babinmarc/) The Podcast Blueprint Website - https://www.yourpodcastblueprint.com/ (https://www.yourpodcastblueprint.com/) The Podcast Blueprint LinkedIn Page - https://www.linkedin.com/company/podcast-blueprint/ (https://www.linkedin.com/company/podcast-blueprint/) Additional Material mentioned in the episode: The Podcast Consumer 2025 report from Edison Research - https://www.edisonresearch.com/wp-content/uploads/2025/07/The-Podcast-Consumer-2025-revised-FINAL.pdf (https://www.edisonresearch.com/wp-content/uploads/2025/07/The-Podcast-Consumer-2025-revised-FINAL.pdf) Read People Like a Book: How to Analyze, Understand, and Predict People’s Emotions, Thoughts, Intentions, and Behaviors By Patrick King - https://www.goodreads.com/en/book/show/56199402-read-people-like-a-book (https://www.goodreads.com/en/book/show/56199402-read-people-like-a-book)

Reach and audience

Public platform figures. Ratings count people who left a rating, not total listeners.

Apple Podcasts (US)

5.0 / 5

1 ratings

Contact Root Cause

Guest appearances

Books guests

Based on episode analysis; this does not confirm that the show is currently accepting guests.