Beyond Coding

Jeroen Gordijn and Jeroen Dee: two frontrunners who stopped writing code months ago and say software development is already solved. Typing code is no longer necessary, but what matters more now? If you're an engineer that loves coding, you're in a tougher spot than you might realize.In this video, we cover:- Why writing code is "solved" but engineering isn't- Spec-driven development and how to get it started in your team- The "Dark Factory" and why code review is a huge bottleneck- Model vs harness: what matters more, and why- The unhealthy side of agentic codingIf you write software for a living and you're trying to work out what your job becomes next, start here.Timestamps:00:00:00 - Coding Is No Longer Necessary00:00:43 - Why "Software Development Is Already Solved"00:02:57 - Should You Even Read the AI's Code?00:05:05 - What Is a "Dark Factory"?00:06:52 - If You Can Regenerate It, Why Care About Quality?00:07:49 - Spec-Driven Development Explained00:11:32 - Adopting Specs Without Starting From Scratch00:13:23 - Model vs Harness: What Matters More?00:17:27 - Is Your Harness the New IDE?00:20:18 - Why Everyone Plateaus (and the Innovation Token)00:22:50 - Where to Actually Spend Your Time00:24:57 - The Unhealthy Side: "It's Free Cocaine"00:28:00 - Is This Sustainable, or Just Subsidized?00:30:33 - Should You Run Models Locally?00:34:31 - Looping, Scale, and Automating Review00:37:53 - What's Left for Engineers to Do?00:39:13 - If You Love Writing Code, You're in Trouble00:41:18 - Why Teams Are Getting Smaller00:43:03 - What an "Agentic Company" Looks Like00:46:25 - How to Start: Find Your Spark00:50:13 - The One Habit That Keeps You AheadGuests: Jeroen Gordijn: https://www.linkedin.com/in/jeroengordijnJeroen Dee: https://www.linkedin.com/in/jeroendee#AgenticEngineering #SoftwareEngineering #Agents

AI generates 10x more code, but your senior engineers still review it by hand and it's burning them out. Even Google admits code review is now the bottleneck nobody knows how to solve.Florian Buetow, AI engineer at Xebia, has been running experiments to eliminate the human from the review loop entirely, and what he found changes where engineers should focus their effort.In this episode, we cover:Why "stop doing code reviews" is a serious answer (and what replaces them)The guardrails that gave the most value: Semgrep rules, architectural unit tests, and stop hooksWhy your harness matters more than the modelHow Amazon and Google police AI-generated code with policiesAI burnout, cognitive debt, and "cognitive surrender": what stays your responsibilityStep one for adopting agentic software engineering in your team this weekWhether you're an individual developer drowning in AI-generated PRs or driving AI adoption across a large engineering org, you'll leave with concrete experiments to run.More from Florian:https://cracking-ai-engineering.comTimestamps:00:00:00 - Intro00:00:40 - Code Review Is Software Engineering's Biggest Bottleneck00:01:57 - How Amazon and Big Tech Police AI-Generated Code00:02:55 - Horizontal vs Vertical Scaling of AI Engineering00:04:37 - Why "No Code Reviews" Might Be the Answer00:05:22 - Engineering Environments That Give Agents Feedback00:06:46 - Why the Harness Matters More Than the Model00:07:21 - When Spec-Driven Development Failed and TDD Worked00:10:06 - Stop Hooks, Ralph Loops, and Automated Feedback00:11:30 - The Guardrails That Gave the Most Value00:14:00 - Architectural Constraints That Keep AI Code Sane00:15:07 - What Remains a Human Responsibility00:17:33 - Why All the Hard Work Moves Upfront Now00:18:47 - The Incredible Skill Junior Engineers Should Learn00:20:26 - AI Burnout: Why Engineers Are Exhausted00:22:42 - Cognitive Surrender: Letting the Agent Take Over00:23:25 - The Hand Grenade Problem with AI at Work00:24:08 - Outsourcing Code Review to AI Itself00:26:39 - Teams That Fully Adopted Spec-Driven Development00:29:01 - Can You Rebuild Software From Tests Alone?00:30:27 - How to Experiment and Stay Ahead00:33:15 - Spying on What Subagents Tell Each Other00:33:59 - Step One: How to Start with Guardrails00:36:08 - Data Mining Your Session Logs for Patterns00:37:00 - Stuck With One Harness? Here's What to Do00:38:28 - The One Experiment to Run This Week#softwareengineering #aicoding #codereview

Most engineers are using AI coding tools without understanding what they actually are and it's costing them. Microsoft Certified Trainer Rob Bos has trained thousands of engineers on AI tooling, and he sees the same gaps in fundamentals show up again and again, regardless of seniority. This is what you need to know:What an LLM actually is (and why understanding this changes how you use it)Why prompt engineering isn't optionalHow AI magnifies your existing technical debt instead of fixing itThe 6-month learning curve nobody warns you aboutWhy your role as an engineer was never about writing codeThe environmental cost behind every promptWhether you're skeptical of AI tools or already living in agent mode, these are the fundamentals that separate engineers who get real value from those who get burned by the hype.Connect with Rob:https://www.linkedin.com/in/bosrobReferences:Token tracker: https://marketplace.visualstudio.com/items?itemName=RobBos.copilot-token-trackerDev survey: https://www.activestate.com/wp-content/uploads/2019/05/ActiveState-Developer-Survey-2019-Open-Source-Runtime-Pains.pdfTimestamps:00:00:00 - Intro00:00:43 - The #1 Thing Engineers Get Wrong About AI00:02:09 - How Much LLM Theory Do You Actually Need?00:03:58 - Why Pair Programming Is Still the Best Way to Learn AI00:05:26 - Why Rob Skips Tab Completion and Lives in Agent Mode00:07:03 - The "AI Doesn't Increase Productivity" Debate00:08:29 - Why Your Real Job Was Never Writing Code00:09:14 - The 2-Hours-of-Coding Problem No One Talks About00:11:02 - More Code = More Pressure on Your Review Process00:12:21 - Why AI Magnifies Existing Technical Debt00:13:39 - The Customer Who Couldn't Start AI With Developers Yet00:15:11 - The Future Engineer: Reviewer, Not Writer00:17:00 - Convincing the AI Skeptic Who Tried It Years Ago00:19:17 - LLMs Explained Without Visuals (Attention & Semantics)00:22:41 - Why Prompt Engineering Actually Matters00:24:20 - From Zero to Hero: The 6-Month Learning Curve00:26:18 - Is This Confrontational for 20-Year Veterans?00:29:30 - Becoming a Better Engineer by Thinking in Systems00:31:26 - Will AI Stop Working as Innovation Slows?00:34:26 - The Lost Art of Pair Programming with AI00:35:44 - Tribalism in AI Tools (And Why It's Pointless)00:37:33 - Tool Agnostic: Start With the Foundations00:39:40 - Is the IDE Still Relevant?00:40:50 - The Bluescreen Story That Changed His Mind00:41:47 - The Hidden Environmental Cost of AI Coding00:44:15 - 36 Million Tokens in 30 Days: What Does It Mean?00:45:47 - Running LLMs at the Edge to Cut the Footprint00:46:48 - Why You Should Be Allowed to Wait Five Minutes Longer00:47:05 - Outro#githubcopilot #aicoding #softwareengineering

Most engineers approach open source the wrong way. They write code, open a PR, and wonder why it never gets merged. Bruno Schaatsbergen, Terraform core contributor and ex-HashiCorp engineer, breaks down the real craft behind contributions that actually land, and why AI is quietly breaking the ecosystem we all depend on.In this episode, we cover:Why pull requests get ignored (and the counterintuitive fix)How AI slop is killing open source from the insideUsing AI agents without losing your identity as an engineerWhy open source beats a tailored resume in today's marketHow consistent contributions can reshape your entire careerIf you've ever wanted to contribute to open source but didn't know where to start, this episode gives you a clear perspective from someone who's been on both sides.Connect with Bruno:https://www.linkedin.com/in/bschaatsbergenOUTILNE00:00:00 - Intro00:01:04 - How Open Source Shaped My Entire Career00:02:14 - Why I Take Pride in Every PR I Write00:03:16 - Open Source vs Personal Projects: The Real Difference00:04:18 - Why Your PRs Get Ignored (And How to Fix It)00:05:41 - Know Your Audience: The Counterintuitive PR Hack00:06:35 - Dealing With Imposter Syndrome as a Contributor00:07:10 - Read Code Like a Writer Reads Books00:09:31 - My First Contribution (And How It Changed My Career)00:10:51 - Should You Contribute to Open Source Early in Your Career?00:12:46 - The Dark Side: When Contributions Become Noise00:13:44 - Killed With Kindness: The AI Slop Problem00:16:17 - How Maintainers Are Fighting AI Slop00:18:02 - How I Actually Use AI Agents in My Workflow00:19:11 - Don't Outsource Your Thinking to AI00:20:11 - Who's Liable for AI-Generated Code?00:21:16 - Earned Rights: Why Trust Matters in Open Source00:22:52 - How to Approach People at Tech Conferences00:24:52 - Open Source Is Not a Democracy00:26:04 - Why Open Source Beats a Tailored Resume00:27:12 - Never Contribute With the Goal of Getting Hired00:28:38 - The Real Reason Consistency Pays Off00:29:30 - Admitting I'm a University Dropout00:30:42 - Why I Haven't Contributed in Weeks (And That's Okay)00:32:07 - The Trap of Chasing Contributor Rankings00:34:32 - Open Source Lets You Work With Anyone in the World00:35:52 - Final Advice: Don't Let AI Steal Your Identity

What separates software that survives from software nobody wants to touch? Nico Krijnen has spent 30 years building systems, coaching teams, and learning why some projects thrive while others quietly become the legacy code everyone avoids. In this episode, he shares why the real work starts after you ship, what actually turns a system into legacy, and why the knowledge in your team's heads matters more than the code itself.In this episode, we cover:Why production is where the real learning beginsThe team composition that consistently delivers resultsPeter Naur's Theory Building and why documentation alone falls shortHow knowledge leaving your team turns working systems into legacyWhy assuming you're wrong leads to better architectureWhether you're a senior engineer rethinking how you build or earlier in your career trying to understand what really matters, this episode will change how you think about software that lasts.Connect with Nico: https://realworldarchitect.devTIMESTAMPS00:00:00 - Intro00:01:17 - Why He Keeps Choosing Engineering Over Management00:04:01 - Three Seniors Solved in Three Weeks What Management Couldn't00:05:14 - The Signals You Miss When You're Not in the Team00:06:26 - The #1 Skill Behind Every Successful Project00:08:04 - Why Production Is the Starting Line, Not the Finish00:10:13 - The Habit Most Teams Skip After Deploying00:11:28 - Why the Best Teams Mix Designers and Engineers00:14:36 - Finding the Right People for the Job at Hand00:17:01 - What Juniors Bring That Seniors Can't00:20:57 - How to Handle Ideas You Disagree With as a Senior00:24:21 - A Simple Technique to Surface Everyone's Best Ideas00:27:09 - What Makes a System Survive Long-Term00:30:53 - What Actually Makes a System "Legacy"00:35:01 - The Knowledge That Keeps Software Alive00:36:06 - Peter Naur's Theory Building: Why Documentation Isn't Enough00:40:06 - How Knowledge Loss Is Killing Your Codebase00:42:42 - The Hidden Risk of AI Tools for Team Knowledge00:48:14 - Why You Should Assume Everything You Build Is Wrong00:51:31 - Make Hard Things Easy to Change#SoftwareEngineering #SystemDesign #TechPodcast

Most senior engineers don't realize they're stuck until it's too late. The longer you stay, the more people around you have already decided who you are and what you're for. Ian Miell, CTO at Container Solutions, breaks down why this happens and how understanding the system around you is the first step to growing beyond it.In this episode, we cover:Why staying too long gets you put in a box (and how to escape it)How your software architecture is shaped by money flowsThe 30% rule: why you should feel uncomfortable at work and what it means if you don'tHow to pitch to senior leadership and actually get buy-inWhy AI makes distribution the real challenge, not buildingIf you're a senior engineer trying to grow beyond your current ceiling, this one is worth your time.Timestamps:00:00:00 - Intro00:00:42 - How to Pitch to Senior Leadership and Get Buy-In00:03:26 - Why You Should Feel Uncomfortable 30% of the Time00:06:33 - How to Break Through a Seniority Ceiling00:08:24 - The Burden of Context: Why Being the Go-To Person Traps You00:10:16 - How Ian Became CTO Without Trying To00:13:40 - Why a CTO's Job Is Mostly Coaching Now00:18:20 - Understanding Incentives: The Key to Navigating Any Org00:23:08 - Startups vs. Large Companies: Completely Different Rules00:25:00 - Why AI Makes Distribution the Real Problem, Not Building00:28:16 - The Hidden Maintenance Risk of Vibe-Coded Software00:30:13 - Security and Compliance: More Nuanced Than Engineers Think00:36:54 - Where "Architecture Follows the Money" Came From00:42:36 - The Wrong Number of Customers: A Systems Thinking Story00:47:23 - Why Engineers Think Individually Instead of Systemically00:51:53 - How to Start Thinking in Systems00:57:50 - How to Create Cross-Pollination in Consulting Teams00:59:39 - What CTOs Actually Look for When Hiring01:00:34 - Outro#softwareengineering #systemsthinking #careergrowth

Most architects stop coding... and that's exactly where they lose their edge. Dennis Doomen has been a hands-on coding architect for 30 years, and his take is blunt: if you're not in the code, you can't make good architectural decisions. Period.In this episode, we get into the real causes of codebase rot, why dogmatic pattern-following destroys teams, how Dennis uses AI tools to build open source projects without compromising his standards, and why documentation and decision records might be the most underrated investment a software team can make.This one is for software engineers and architects who want to stay sharp, stay relevant, and build systems that actually last.00:00:00 - Intro00:01:05 - Why Dennis Refuses to Stop Coding (After 30 Years)00:02:54 - The Only Way to Be an Effective Software Architect00:04:43 - What Happens When Teams Copy Patterns Without Understanding Them00:06:23 - Software Engineering Is About Battling Complexity00:08:20 - When to Break Consistency to Reduce Complexity00:09:24 - The Problem with Overzealous SOLID Principles00:11:06 - The Future Where We Don't Care About Code Anymore00:12:07 - How Dennis Built an Open Source Library with GitHub Copilot00:14:18 - Accepting AI-Generated Code That Doesn't Meet Your Standards00:16:39 - How to Use AI Without Losing Code Quality00:17:41 - The Execution Is Accelerating — What Actually Matters Now00:20:19 - Why Tests Are Your Safety Net in an AI-First World00:23:44 - Lessons Learned from Letting AI Run Unsupervised00:26:46 - Should Teams Standardize Which AI Tool They Use?00:27:32 - Junior Devs and AI: Learning Skills vs. Speed00:29:21 - How to Stay Curious and Critical in an AI-Assisted Team00:33:43 - How to Build a Software Engineer from Scratch Today00:34:38 - Dennis's Emoji-Based Pull Request Review System00:36:45 - What AI Still Can't Do: Holistic Architectural Thinking00:38:38 - Why Your Git History Is More Valuable Than You Think00:40:44 - Decision Records: The Architecture Investment That Pays Off00:43:16 - When Documentation Saved Dennis from a Bad Management Decision00:44:47 - The Tailwind Layoffs and the Open Source Business Model Crisis00:46:27 - Guidelines for Consuming Open Source Responsibly00:49:51 - Why You Should Open Source Your Own ProjectsGuest: Dennis Doomen - Microsoft MVP, open source creator (FluentAssertions and more), and coding architect at Aviva Solutions.#softwaredevelopment #softwarearchitecture #softwareengineering

Sendil Nellaiyapen, Engineering Manager at Uber, has built systems that scale to millions of users. In this episode he shares what most engineers get wrong about both system design and the move into engineering managementIn this episode, we cover:Ingredients for designing systems that scale to millions of usersHow to know when to compromise on architectureThe trade-offs of going from IC to engineering manager and why the role is harder than it looksHow to handle opinionated engineers, set team guardrails, and build high-performing engineering cultureWhether you're a senior engineer weighing the move into management, or already leading teams and looking to sharpen your system design thinking, this one's for you.OUTLINE:00:00:00 - Intro00:01:05 - The Ingredients for Building Systems at Scale00:02:23 - When to Compromise on Your Foundation00:03:42 - Scaling from 2,000 to 5 Million Users00:06:37 - Why Clarity Beats Seniority Every Time00:08:27 - The Danger of Muscle Memory in Engineering00:10:25 - MVP Mindset: What You Can and Can't Compromise00:13:22 - How High-Performing Teams Handle Growing Complexity00:15:04 - Who Owns the Assumptions? Shared Team Responsibility00:17:04 - Building Open Frameworks Instead of Closed Rules00:19:53 - Latency Is Overrated (Here's Why)00:22:52 - Recipes for Disaster: The Biggest System Design Pitfalls00:24:17 - The Scala Horror Story: When Elegance Kills Velocity00:26:52 - How to Handle Opinionated Engineers on Your Team00:29:03 - Setting Guardrails: The Manager's Design Responsibility00:32:01 - The Hardest Trade-Off Going from IC to Engineering Manager00:34:35 - Should Great Engineers Stay IC or Go into Management?00:37:11 - BFS vs DFS Engineers: Which Type Makes a Better Manager?00:39:05 - The Real Cost of Becoming a Manager (And Why It's Worth It)00:41:52 - Outro#systemdesign #engineeringmanager #softwareengineering