Beyond Coding

Episodes

• 
  AWS Veteran: How Real Engineering Teams Run Agents 22.07.2026 1h 53m

  "I need to stop using Opus. This doesn't work." That was Heitor Lessa's conclusion after a refactor cost him 200 million tokens, and it forced him to rebuild the entire agent workflow now used across 1,400 engineers. Heitor spent 11 years at AWS, built Lambda Powertools to 230 billion API calls a week, and in this episode he walks through the full SDLC workflow on screen, from discovery to merge check.In this episode, we cover:The product loop: discovery, whiteboarding, and the /roadmap commandSpec-driven development with Open Spec and why vanilla setups failThree model tiers: SOTA for planning, mid-tier for implementation, cheap models for reviewsMerge checks with adversarial reviewers and attestations that catch agents fabricating test resultsThe /retro command: using the Socratic method to make your workflow more deterministicIf you're an engineer figuring out how to work with agents at team scale without losing trust in your codebase, this is the workflow to steal. This is also the first Beyond Coding episode with visuals on screen, so let me know what you think of the format.Timestamps:00:00:00 - The Math Doesn't Add Up00:00:43 - Amazon Hypergrowth: 11 Years, 8 Different Roles00:03:29 - Learning From the Trenches as a Technical Account Manager00:08:38 - Developer Identity and the Birth of Lambda Powertools00:10:20 - The Hard Parts of Working in Public00:13:12 - How Powertools Hit 230 Billion API Calls a Week00:16:42 - Career Advice: Learn Adjacent Roles, Not More Tech00:19:37 - When Leadership Decisions Don't Make Sense to You00:23:21 - The Product Loop Starts With Discovery00:25:22 - From Whiteboard to /roadmap00:27:37 - Why Humans Plan First and Agents Come Second00:30:33 - Commands vs Skills Across 32 Different Models00:33:38 - Adversarial Reviewers on Every Plan00:36:07 - The Socratic Method, Explained00:40:29 - Why He Only Takes Paper Notes00:44:43 - The Five-Line Paper Trick for High-Stakes Meetings00:48:18 - /new-work: Capturing Scope Creep Without Derailing00:54:03 - The Dev Loop Begins: Open Spec Explore00:56:34 - Three Model Tiers: SOTA, Mid, Cheap00:57:43 - The $5,000/Month Per Engineer Question00:58:57 - Guardrails vs Autonomy for 1,400 Engineers01:04:22 - Auto-Sizer: Does This Task Even Need a Spec?01:07:26 - Decision Fatigue and Why Frameworks Win01:09:10 - The Plan Phase: Specs, Design, Formal Verification01:13:07 - The Refactor That Cost 200 Million Tokens01:15:11 - When Agents Forge Evidence They Ran Your Tests01:17:27 - Local-First Architecture Explained01:23:04 - The Apply Phase: Fully Autonomous Loops01:24:30 - Coding Was Never the Bottleneck01:26:39 - Why This Workflow Is an Investment01:27:39 - Decision Logs and the /onboarding Command01:29:06 - Running Agents Locally With Enterprise Governance01:32:42 - Hooks: Making Quality Gates Deterministic01:36:02 - Merge Checks: 15 Adversarial Reviewers Per Change01:38:30 - /retro: Interviewing Yourself to Improve the Loop01:43:12 - Trust, Loss of Trust, and Recovery With Agents01:48:02 - Experience, Scars, and Critical Thinking01:49:32 - Why Right Now Is the Time to Experiment01:52:04 - Conviction Comes From Being in the Loop#softwareengineering #aiagents #aws
• 
  What Senior Engineers do Differently (Vercel VP) 15.07.2026 28m

  What senior engineers do differently has less to do with output than most career ladders suggest, and Lindsey Simon, VP of Engineering at Vercel, has watched the distinction sharpen as everyone in the valley becomes a "member of technical staff." From why new grads with hackathon years might out-prepare engineers with six years on the job, to what happens when PR throughput stops being your lever, this is a conversation about what earns seniority now.In this episode, we cover:Why engineering roles are consolidating into "member of technical staff"How to ask agents first and frame better questions to humansThe scope-of-impact ladder and what the best engineers systematizeLearning how to learn: closing gaps to 100% understandingWhy writing is the skill that scalesIf you're wondering whether your years of experience still compound, or you're early-career and tired of the "woe is the juniors" narrative, this one reframes both.TIMESTAMPS00:00:00 - Impact the Business00:00:31 - FOMO all the time: The 2006 Google Interview00:01:52 - Engineering Roles Are Consolidating00:02:52 - The "Member of Technical Staff" trend in SF00:03:33 - Interns Demo to the CTO00:04:33 - How New Grads Out-Prepare Senior Engineers00:06:10 - Ask Your Agent Before You Ask a Human00:08:01 - Digging Backwards Into Fundamental Understanding00:09:22 - "We're All Junior Engineers Again"00:10:22 - Management Is Not Leadership00:12:04 - Losing PR Throughput as Your #1 Lever00:13:11 - Fulfillment Beyond Shipping Features00:14:32 - Building for Fickle Engineers: Telemetry Beats Opinions00:16:11 - Watching Users Struggle With Your Product00:18:12 - Have Expectations for Seniors Actually Changed?00:19:57 - Claude Says a Month, It Takes Two Hours00:20:33 - What the Best Engineers Do Differently00:21:30 - How Vercel React Skill Came to Be00:22:23 - Why Conference Conversations Hit Different00:23:35 - Learning How to Learn: Close Gaps to 100%00:25:41 - The Case for Liberal Arts in Tech00:27:03 - Get Feedback Early, Don't Hide in the CaveGuest - Lindsey Simon, VP of Engineering at Vercel:https://www.linkedin.com/in/lindseysimon#softwareengineering #ai #careergrowth
• 
  Why the Fastest Engineers Are Falling Behind 09.07.2026 40m

  The fastest engineers are falling behind, and Kitze was one of them. He built his reputation on raw coding speed, then realized his coding wasn't competing with anyone's coding anymore, it was competing with their setups. Wake-up call for developers: Kitze now runs 140 projects solo with agent loops, and in this episode he breaks down what separates the engineers pulling ahead from the ones getting left behind.In this episode, we cover:Vibe coding vs vibe engineering, and how to get better results from your agentsPolice files: Self-correcting loops that end every agent turn with zero errorsWhy teams of 10 are collapsing into teams of 2, and who survivesThe rude awakening coming for engineers who refuse to adaptThe number one advice to stay on track and fight FOMOFor individual contributors, tech leads, and principal engineers who don't plan on falling behindTIMESTAMPS:00:00:00 - Intro00:00:40 - Vibe Coding vs Vibe Engineering: The Real Difference00:02:16 - Police Files: The Self-Correcting Loop on Every Turn00:05:23 - Capture Every Frustration as a Rule00:06:53 - Why Being the Fastest Coder Stopped Mattering00:09:45 - Problem Solver vs Problem Lover: Pick One00:10:43 - The Rude Awakening Engineers Don't Want00:12:05 - Why Teams of 10 Become Teams of 200:13:09 - Loop Engineering: The Edge Anyone Can Build00:16:08 - Why No Agent Orchestrator Works Yet00:17:07 - Starting a Fresh Codebase: What Kitze Transfers00:19:14 - No Sidebars: Inventing an Agentic OS00:21:07 - How Kitze Shipped 300 Changes Across 200 Repos00:23:40 - We Are Becoming the Bottleneck00:24:25 - Why Leadership Must Give Engineers Room to Experiment00:26:16 - The Token Divide: Not Everyone Can Compete00:27:41 - Learn Now or Lose Access Later00:29:33 - The Culling: Coasting Is Going Away00:30:45 - Why LLM Code Reviews Beat Tired Seniors00:33:21 - Solo Engineers With Agent Swarms vs Teams00:34:53 - Agents Climbing the Org Chart to CEO00:36:03 - What Distinguishes the Best Engineers: Unblocking00:36:50 - Ego Is the Real Bottleneck00:37:55 - Kitze's #1 Advice: Stick to One Model
• 
  AI Cloud CTO: Which Engineering Skills Are Most In-Demand Right Now 01.07.2026 58m

  Danila Shtan runs engineering at Nebius, one of the biggest AI clouds in the world, and he told me exactly which engineers he hires on the spot. There are only hundreds of people on the planet with the skill he wants most, and it is not the one you are grinding on. We get into which engineering skills are actually scarce and well paid today, and which ones are quietly on the way out.In this episode we cover:The engineering skills in highest demand right now and which ones are on the way outWhy an AI cloud CTO restricts Claude Code inside his own companyDan's rule for merging any AI-written code into productionWhy working with an agent is like managing a junior engineerThe interview question that surfaces top tier engineer qualitiesWhy he still runs algorithm interviews todayIf you are an engineer trying to work out where the value sits now that agents write the easy code, this is a straight answer from the person building the infrastructure underneath all of it.Timestamps:00:00:00 - AI Agents doing everything is a lie00:00:44 - What Nebius Actually Does00:04:31 - The Engineers In Highest Demand Right Now00:06:58 - Inside the Hiring Process00:08:12 - The Bootcamp: You Join the Company, Not a Team00:10:51 - Why You Can't Use AI in Their Interviews00:16:31 - Why He Banned the Word "Headcount"00:22:25 - Why a CTO Is Not a Technical Role00:24:49 - The One Skill Every Manager Needs00:25:48 - Why Smart People Fail at This00:28:17 - "The Promise of Agents Is Bullshit"00:31:39 - How AI Multiplies Your Baseline Skill00:35:32 - Why an AI Agent Is Just a Junior Engineer00:36:57 - Why He Won't Let His Team Use Claude Code00:37:46 - His Rule for Merging AI-Written Code00:40:28 - The Interview That Predicts Great Engineers00:42:32 - From T-Shaped to Round-Shaped Engineers00:44:30 - Is There Still a Path for Juniors?00:45:28 - Why Hard Skills No Longer Matter00:47:11 - The Engineers Who Will Become Obsolete00:50:04 - The Real Reason People Stay at Banks00:52:26 - Where AI Agents Actually Help00:54:40 - Why He Still Uses Algorithm Interviews00:56:05 - Tech Enthusiasts vs. Real Engineers#AIEngineering #TechCareers #SoftwareEngineering
• 
  Career Expert: Why Applying to Jobs No Longer Works 24.06.2026 46m

  120,000 tech workers have been laid off in 2026, yet there are 60,000 open roles. Engineers applying are sending out 100 applications for zero replies. Former Reddit, Uber and Disney Plus recruiter Keki Mwaba breaks down why the market broke, why every resume now looks identical, and what gets you hired when yours looks like everyone else's.In this video, we cover:Why 120,000 layoffs and 60,000 open roles don't add upWhy CVs have become too good and it's no longer enoughHow to treat LinkedIn as a platformGetting into companies like OpenAI and AnthropicHow to reach out to people without seeming fakeIf you're a software engineer trying to stand out in the most competitive tech market in years, this is the playbook.Timestamps:00:00:00 - Intro00:00:35 - How bad is the tech job market in 2026?00:02:38 - 120,000 laid off, 60,000 jobs open: the math is not mathing00:04:05 - LinkedIn isn't a CV, it's a platform00:08:30 - The underrated move: comment your way into a job00:10:48 - Is AI ruining LinkedIn?00:13:50 - Never feel safe: how to prepare before a layoff00:15:34 - What layoffs do to the people who stay00:17:03 - "Did I just automate myself out of a job?"00:18:48 - Why every resume now looks the same00:20:11 - Why referrals beat applications00:22:13 - Do software engineers still have a future?00:23:32 - The staff engineer who wants to quit for plumbing00:26:16 - Patrick on his own job security00:30:21 - 70% of job descriptions now demand AI skills00:31:34 - Is middle management disappearing?00:33:53 - The impossible ask: stay current, deliver, and not burn out00:37:02 - How to get hired at OpenAI or Anthropic00:39:18 - How to message someone without seeming fake00:41:42 - Build a portfolio that shows your thinking00:45:12 - Your personal branding plan for the next few weeksGuest: Keki Mwaba, career and recruitment expert:https://www.linkedin.com/in/keki-mwaba#techjobs #softwareengineering #careeradvice
• 
  Why the Frontrunners Say Coding Is Solved BUT Engineering is Not 17.06.2026 51m

  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
• 
  Why The Best Software Engineers Are Solving Code Review Bottlenecks Now 10.06.2026 40m

  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
• 
  Google DeepMind Lead: The New Rules of Software Engineering 03.06.2026 23m

  Are you ready to adapt to the rapidly evolving rules of software development? In this deep dive, Logan Kilpatrick, Director and Engineer at Google DeepMind, breaks down how AI agents, advanced model-product symbiosis, and tools like Gemini 3.5 Flash are fundamentally shifting the engineering bottleneck. Learn how to maintain your competitive advantage by moving beyond the keyboard to focus on problem-solving, architectural taste, and system understanding.In this video, we cover:The changing role of the IDE and the rise of agent managers in code generation.Overcoming team bottlenecks in code review and CI/CD test execution execution loops.Why "agent coverage" and context integration are the next big tech stack metrics.Building a bulletproof software portfolio through permissionless open-source contributions.The critical difference between outsourcing intelligence versus outsourcing understanding.This episode is for software engineers, tech leads, and computer science students looking to future-proof their careers and reset their ambitions in the era of autonomous engineering agents.Timestamps: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 #AIAgents #GoogleDeepMind
• 
  Addy Osmani: Top Tier Software Engineers vs. AI Agents. The Mindset You Need 28.05.2026 17m

  As AI agents transform software engineering, how do you leverage them without losing your coding skills or risking production disasters? In this episode, Google Cloud AI Director Addy Osmani breaks down the shift from babysitting basic models to mastering advanced agent harnesses.Discover how to safely delegate complex technical tasks while maintaining your human engineering identity and setting up secure boundaries for your AI.In this episode, we cover:Human Identity vs. Machine Identity: How to avoid the trap of "cognitive surrender" and keep your critical thinking sharp.Stopping the AI "Babysitting" Cycle: How to transition from constant manual oversight to secure agent governance.Rising Abstractions: Why agent harnesses (like Claude Code and Antigravity) are changing how software is built.The Verification Bottleneck: Why coding is easy, but verifying that your agent didn't ruin production is the real challenge.This episode is a must-watch for software engineers and tech leaders looking to integrate AI agents into their workflows safely and effectively. You’ll walk away with actionable frameworks to boost your development velocity without letting your own technical edge rot.Guest:Addy Osmani is a Director at Google Cloud AI, famous for his work on Google Chrome and focused on AI agents in software engineering.Timestamps:00:00:00 - Intro 00:00:45 - The Reality of "Babysitting" Your AI Agent Setup 00:01:16 - How to Stop Babysitting and Build Secure AI Agents 00:02:36 - The Dangerous Mistakes of Uncontrolled AI Experiments 00:03:39 - Rising Abstractions: From Code to Agent Harnesses 00:05:18 - Why You Should Delegate Technical Tasks to AI 00:07:05 - How to Choose the Best AI Agent Harness 00:08:31 - How to Manage Your Developer Innovation Budget 00:10:17 - Are We Losing Pair Programming to AI Agents? 00:12:14 - Cognitive Surrender: The Hidden Threat of Generated Code 00:13:40 - The Verification Bottleneck: How to Trust AI Code 00:15:59 - How to Safely Scale Your Personal AI Bandwidth#AIAgents #SoftwareEngineering #DeveloperProductivity
• 
  What World Class Software Engineers Do That You Don't 20.05.2026 32m

  After 250 episodes of Beyond Coding, a pattern shows up again and again: the engineers who thrive aren't the ones chasing the newest tool or the cleanest code. They're the ones who learn fast, keep things simple, and understand the business they're building for. This special pulls the sharpest moments from recent guests into one conversation about what actually makes a great software engineer in 2026.We cover:Why learning is the only skill that outlives every tool, language, and platformHow the best architects act more like scouts than cartographersWhy "simple is complicated enough" beats clean code dogma at scaleHow to design systems that evolve instead of trying to predict 10 years outWhat junior engineers should actually do in the age of AI agentsFor software engineers who want to think clearer, build better, and grow into the kind of engineer companies can't replace.Timestamps:00:00:00 - Intro00:00:17 - Why You Should Increase Your Breadth, Not Just Focus00:02:16 - The Only Skill That Survives Every Tech Cycle00:04:14 - Buzzwords Are Just Old Ideas in New Clothes00:05:26 - What Clients Say vs What They Actually Want00:06:45 - The Bad Architects Are Easier to Spot00:08:50 - Why Good Engineers Use Boring Technology00:11:40 - Stop Building for 100x Scale on Day One00:13:13 - The Dogma of Clean Code Is Hurting You00:15:15 - Simple Is Complicated Enough at Scale00:16:28 - Design Only for the Next Order of Magnitude00:18:19 - How to Talk Tech with Non-Technical Stakeholders00:19:30 - The $50,000-Per-Hour Container Terminal Lesson00:22:11 - Architects Are No Longer Cartographers, They're Scouts00:25:18 - Start with a Question, Not an Answer00:26:49 - Junior to Senior in the Age of AI Agents00:27:29 - Don't Be a Fool with a Tool00:29:43 - From Explicit to Implicit Knowledge Economy00:30:38 - Use AI to Validate, Not to Generate#softwareengineering #engineeringcareer #softwarearchitecture
• 
  What Separates Cracked Software Engineers From Everyone Else 06.05.2026 38m

  Reddit Reacts is back. I'm taking the most controversial takes on software engineering from Reddit and giving you my unfiltered perspective on what's happening, from juniors leveraging AI tools, to the culling of engineers who refuse to adapt, to whether you should take a gap year after a layoff.In this episode, we cover:How to become technically "cracked" and what really separates great engineersWhy juniors learning with AI have an edge over 20-year veteransThe future of writing code by hand (and why fulfillment is shifting)Vibe coding, security holes, and what happens after 6 monthsThe brutal reality of layoffs, gap years, and AI-driven hiringIf you're an engineer trying to figure out where this industry is going and how to stay competitive, this one is for you.Mentioned in the episode:⁠ADP List⁠ - free mentorship from senior engineersTimestamps:00:00:00 - Intro00:00:54 - How to Become Technically Cracked in 202600:05:35 - Will Juniors Who Only Code with AI Get Stuck?00:09:26 - Will Senior Engineers Stop Writing Code By Hand?00:11:11 - I Vibe Coded for 6 Months and It's a Disaster00:15:04 - Why Leaders Demand Screen Sharing on Incident Calls00:17:34 - "I Don't Do Anything and Still Get Promoted"00:20:33 - Have the Best Engineers Stopped Applying?00:25:39 - The Future of Software Engineering in the AI Era00:32:15 - Are Most Programmers Actually Bad?00:34:58 - Should You Take a Gap Year After a Layoff?#softwareengineering #aicoding #techcareers
• 
  How Elite Software Engineers Are Using Agents to Get Sh*t Done 29.04.2026 47m

  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
• 
  Why World Class Engineers Get Jobs on Easy Mode 22.04.2026 37m

  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
• 
  Veteran Architect: How To Design And Build Systems That Survive 15.04.2026 53m

  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
• 
  Top Microsoft Advisor: "Coding Is Cheap, Software Is Expensive." You're Focused on the Wrong Thing 08.04.2026 46m

  Suzanne Daniels is a Top Microsoft Advisor who works with CTOs and engineering leaders across EMEA on developer productivity, GitHub, and AI adoption. Her take: the industry is obsessing over coding speed, but that was only ever level one. The real shift is in who defines the solution, not who writes the code.In this episode, we cover:Why the "55x faster coding" marketing misses the point entirelyThe counterintuitive research showing junior engineers adopt AI faster than seniors"Coding is cheap, software is expensive" and what that means for your careerHow the boundary between product and engineering is disappearingWhy most AI coding tools are 80% the same and what to focus on insteadWhether you're early in career and struggling to land a role, or a senior engineer rethinking where your value lies, Suzanne breaks down what actually matters when the coding part becomes cheap.Timestamps:00:00:00 - Intro00:01:15 - Is AI Productivity the Whole Story?00:03:26 - Why Outcomes Matter More Than Code Output00:04:13 - The Real Value Was Never in the Coding00:06:06 - The Product-Engineering Boundary Is Disappearing00:07:37 - Why Junior Engineers Are Actually in High Demand00:09:41 - Research Says Juniors Adopt AI Faster Than Seniors00:11:31 - The Rise of Comb-Shaped Engineers00:12:32 - The Energy Juniors Bring That Teams Need00:14:06 - How Seniors Codify Knowledge for Agents and Humans00:16:35 - Advice for Early Career Engineers Right Now00:19:04 - Old Principles Getting a New Polish00:21:13 - Coding Is Cheap, Software Is Expensive00:22:52 - Will Agentic Development Change Your Programming Language?00:24:53 - What Even Is an Application in the Agent Era?00:28:34 - The Authenticity Paradox of AI-Written Content00:30:12 - Why Your AI Output Needs a Human Value Add00:32:12 - Is Open Source at Risk Because of AI?00:35:09 - When Your Favorite Tool Doesn't Follow You to the Next Job00:36:45 - Most AI Coding Tools Are 80% the Same00:38:15 - What Engineering Leaders Should Enable Beyond Licensing00:42:58 - Should You Leave If Your Company Won't Let You Experiment?00:45:16 - Platform Engineering as the Foundation for AI AdoptionGuest: Suzanne Danielshttps://www.linkedin.com/in/suzannedaniels#SoftwareEngineering #AICoding #BeyondCoding
• 
  AI Expert: Most Software Engineers Aren't Ready for What's Coming 01.04.2026 47m

  The role of the software engineer is shifting from execution to orchestration, and it's happening faster than most of us realize. Dennis Vink, Principal Consultant at Xebia, breaks down how he approaches code modernization with AI, why fundamentals and system design matter more now than ever, and what the engineering role is actually becoming.In this episode, we cover:Why you need to mature your old codebase before you can migrate away from itHow to prove feature parity between legacy and modern systemsWhy vibe coding without architecture knowledge gives you zero controlThe shift from execution-focused engineering to orchestrationWhy Dennis worries about the next generation of engineersWhether you're sitting on legacy code at work or wondering how your role as an engineer is evolving, this conversation will make you think about where you need to invest your time next.Timestamps:00:00:00 - Intro00:00:51 - Dennis's Early AI Engineering Assignments00:02:23 - Side Projects: Reviving a 20-Year-Old Game in Rust00:04:36 - Why Vibe Coding Without Fundamentals Fails00:05:15 - The Fundamentals You Need for Code Migration00:06:45 - Proving Feature Parity with Automated Testing00:08:12 - Writing Tests First as Risk Mitigation00:10:13 - How Much Should You Care About Code Structure?00:11:18 - Migrating in Small Pieces of Value00:12:26 - Will Engineers Still Find Fulfillment in Building?00:14:01 - How to Actually Start Side Projects (ADHD Brain)00:15:34 - Why Pivoting Is No Longer Painful00:16:12 - Prompting as the New Bottleneck00:17:23 - Parallelizing Work Across Projects00:19:08 - Why System Design Is the #1 Audience Demand00:20:19 - AI as a Differentiator for Strong Architects00:21:11 - Why the New Generation Should Worry00:23:01 - Are Bootcamps Still Worth It?00:25:15 - The Shift from Collaboration to Business Understanding00:27:56 - Infrastructure as a Core Competency Bet00:30:15 - Deterministic vs Non-Deterministic Code Generation00:32:16 - Can This Approach Scale to Million-Line Codebases?00:34:20 - Why a Finger-Snap Migration Would Scare You00:37:01 - Where to Start with Your Own Legacy Codebase00:38:43 - Which Languages Do AI Models Struggle With?00:40:24 - Building Around Hallucination with Scaffolding00:42:30 - Spec-Driven Development as the Future Way of Working00:43:30 - Turning a Non-Technical Colleague into a "Developer" in an Hour00:46:21 - When the House Is on Fire, That's When You Need Real EngineersProjects we discussed:Agent designer - hurozo.com Game project - Zorlore.com (https://github.com/zorlore/)Vibe coded solar system simulation - spacehaste.com #SoftwareEngineering #SystemDesign #AIEngineering
• 
  Veteran CTO: How to Think About Your Software Engineering Career 25.03.2026 1h

  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
• 
  Top Tier Architect: Software Engineering Is About Battling Complexity 18.03.2026 52m

  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
• 
  Uber Engineering Manager: Why Clarity Beats Seniority 11.03.2026 44m

  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
• 
  Lead Software Engineer: Why You Can Write the Code in a Day but Ship in a Month 04.03.2026 39m

  Are you over-engineering for a future that might never come? In this episode, we explore why "future-proofing" often leads to wasted time and sunk costs, and how shifting your mindset from opinions to hypotheses can drastically improve your Developer Experience (DevEx).In this episode, we cover:The trap of complex architecture decisions like Hexagonal Architecture too earlyHow to identify and remove friction points in the software development lifecycleThe reality of using AI agents in production and who is actually responsible for the codeIf you are a software engineer or tech lead tired of the "Sacred Cloud Committee" and slow processes, this deep dive into DevEx is for you.Connect with Bas de Groot:https://www.linkedin.com/in/bas-de-groot-635013100Timestamps: 00:00:00 - Intro 00:01:00 - The Danger of "Future-Proofing" Your Architecture 00:03:18 - Why You Should Use Hypotheses Over Opinions 00:05:32 - "Shift Left Until There's Only Sh*t Left" 00:08:19 - At What Size Do You Need a DevEx Team? 00:11:02 - How to Measure Developer Friction Effectively 00:15:43 - Using Data to Fix Slow CI/CD Pipelines 00:17:26 - Why Surveys Beat DORA Metrics for Context 00:19:52 - The "Sacred Cloud Committee" Blocking Deployments 00:24:51 - How to Get Buy-In for DevEx Initiatives 00:28:56 - The Role of Hands-On Coding in DevEx 00:31:47 - Will AI Agents Fix Bad Processes? 00:34:44 - You Are Still Responsible for AI-Generated Code#developerexperience #softwarearchitecture #techlead