Beyond Coding

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

Engineering hasn't become easier, writing code has just become faster. Time to stop fighting symptoms and start thinking in systems. In this Q&A, I break down the career advice I'd give to any engineer, from mastering architecture to knowing when to quit a high-paying job.In this episode, we cover:How "Systems Thinking" can be applied in practiceThe "Golden Handcuffs": Why high salaries keep engineers in toxic jobsHow to transition into leadership without waiting for a titleTimestamps00:00:00 - Intro 00:00:58 - How to innovate in stubborn legacy companies 00:04:49 - The "Golden Handcuffs": Money vs. Mental Health 00:07:27 - Stop solving symptoms: Systems Thinking explained 00:13:10 - Transitioning from Senior Engineer to Solutions Architect 00:15:08 - Communicating technical risks to non-technical bosses 00:17:48 - Proving leadership before you have the title 00:22:25 - My strategy for dealing with Imposter Syndrome 00:26:12 - Creating a "Zettelkasten" to retain technical knowledge 00:29:12 - The mindset that makes me stress-proof at work 00:33:10 - Learning to code with a product/design background 00:38:40 - Working with international remote teams 00:40:35 - Career Pivot: Software Engineering to Cyber Security 00:43:20 - Solopreneur opportunities in the "Education Gold Rush" 00:51:50 - Future Predictions: Vibe Coding vs. Vibe Engineering#SoftwareEngineering #CareerAdvice #SystemsThinking

"Architects shouldn't try to be the smartest people in the room, they should make everybody else smarter."In this episode, Gregor Hohpe (ex-Google & AWS, author of "The Software Architect Elevator") breaks down exactly how to transition from software engineer to architect. He shares the mental models used at Big Tech to handle complexity, visualize systems, and navigate office politics without losing your technical edge.We cover:- Why "lowering risk" is the architect's real value proposition- The "Phantom Sketch Artist" technique to visualize unclear requirements- How to gain "political capital" to push back on bad decisions- Why simple architectures are often the hardest to buildIf you want to move beyond just writing code and start designing systems that scale, this conversation is for you.Connect with Gregor:https://www.linkedin.com/in/ghohpe00:00:00 - Intro 00:01:15 - How to Spot Bad Architects vs. Great Amplifiers 00:03:44 - Why Architects Are Actually Risk Managers in Disguise 00:06:13 - The Truth About Complexity and Simplicity at Scale 00:09:55 - How to Resolve Technical Disagreements Without Arguments 00:13:57 - Why You Should Use Pen and Paper for Architecture 00:17:24 - Mastering the Left-Right Brain Ping Pong Technique 00:20:42 - The "Architect Elevator": Connecting Code to Strategy 00:23:06 - The Rubber Duck Test: Are You a Good Architect? 00:25:41 - The "Phantom Sketch Artist" Method for System Design 00:30:37 - Stop Being a Cartographer, Start Being a Scout 00:34:47 - How to Keep Your Technical Skills Sharp as an Architect 00:44:37 - Navigating Office Politics using the "Court Jester" Strategy 00:48:08 - How to Earn and Spend Political Capital Wisely 00:53:17 - Why the "Big Ball of Mud" Might Be a Good Architecture 00:57:08 - How Executives Spot Gaps in Your Technical Logic 01:00:00 - Why Using AI for Architecture is a Dangerous Trap#SoftwareArchitecture #SystemDesign #SeniorDeveloper

Software engineers often think adding AI is just a simple API call, but moving from a Proof of Concept to a stable production system requires a completely different mindset. Maria Vechtomova breaks down the harsh reality of MLOps, why rigorous evaluation is non-negotiable, and why autonomous agents are riskier than you think.In this episode, we cover:The essential MLOps principles every software engineer must learnHow to bridge the gap between a demo and a production-grade solutionStrategies for evaluating agents and detecting model driftThe security risks of customer service agents and prompt injectionPractical tips for using AI tools to boost your own productivityConnect with Maria:https://www.linkedin.com/in/maria-vechtomovaTimestamps: 00:00:00 - Intro 00:01:25 - Why the AI Hype Was Actually Good for Monitoring 00:03:07 - Real-World AI Use Cases That Deliver Actual Value 00:05:16 - MLOps Basics Every Software Engineer Needs to Know 00:08:08 - The Hidden Complexity of Deploying Agents to Production 00:12:02 - Minimum Requirements for Moving from PoC to Production 00:15:41 - Step-by-Step Guide to Evaluating AI Features Before Launch 00:18:08 - How to Handle Data Labeling and Drift Detection 00:21:55 - Why You Likely Need Custom Tools for Monitoring 00:24:56 - Why Engineers Build AI Features They Don't Need00:26:01 - How Software Engineers Can Learn Data Science Principles 00:31:36 - The Dangerous Security Risks of Autonomous Customer Service Agents 00:34:44 - Why Human-in-the-Loop is Essential for Avoiding Reputational Damage 00:36:18 - Boosting Developer Productivity with Opinionated AI Prompts 00:39:20 - Using Voice Notes and AI to Organize Your Life#MLOps #SoftwareEngineering #ArtificialIntelligence

Tools change and frameworks die, but your career doesn't have to. Marijn Markus joins the show to explain why "Don't be a fool with a tool" is the single most important piece of advice for modern software engineers and data professionals.In this episode, we cover:The "Meta-Skill" of learning how to learn new technologiesWhy real innovation often originates in "dark" industries like crime and warfareHow to future-proof your career against AI agents and automationWhy understanding the business problem is more valuable than writing the codeThis conversation is essential for engineers who want to move from memorizing syntax to mastering the skills that actually last.Connect with Marijn Markus:https://www.linkedin.com/in/marijnmarkusTimestamps:00:00:00 - Intro00:01:01 - Realizing That Data Science Can Actually Save Lives00:04:36 - Predicting Refugee Movements With Hamburger Prices00:07:05 - Why You Should Try Different Roles Early in Your Career00:12:37 - Learning in Banking to Eventually Help Non-Profits00:15:38 - Why Certifications Are Compensation for Lack of Experience00:18:36 - The Single Most Important Skill in the Tech Field00:21:39 - "If They Understood the Problem, They Wouldn't Hire You"00:25:48 - Why Innovation Comes From War, Crime, and Adult Industries00:31:16 - The Danger of AI Agents and Automated Social Engineering00:35:03 - Focus on Skills That Do Not Have Expiration Dates00:39:47 - How to Navigate Truth in the Era of Deepfakes00:41:30 - Don't Be a Fool With a Tool (The Selenium Trap)00:45:25 - Rising Above the Tools to Become an Expert#SoftwareEngineering #CareerAdvice #Technology

Traditional software engineering job listings have dropped by 70%, yet Forward Deployed Engineer (FDE) roles have exploded by over 800% this year. We sit down with Mo Fagir, Principal Technical Consultant at ServiceNow, to break down exactly why this shift is happening and how you can pivot your career to ride this AI adoption wave.In this episode, we cover:The massive market shift: Why "pure coding" jobs are declining while FDEs are booming.The exact technical stack and soft skills required to land these high-paying roles.How to overcome imposter syndrome and build a portfolio that gets you hired, even as a junior.Why this isn't just a trend, but the future of how engineering delivers value.Connect with Mo Fagir:https://www.linkedin.com/in/mo-nour-tarigTimestamps:00:00:00 - Intro00:01:14 - Why software jobs dropped 70% while FDEs grew over 800%00:02:55 - Why companies can't implement AI without Forward Deployed Engineers00:05:36 - Is this career path safe for traditional software engineers?00:07:54 - The exact technical stack you need to master today00:10:48 - Moving from engineering scope to product centric thinking00:16:15 - Can juniors and early career devs get hired as FDEs?00:19:12 - How to build a portfolio that gets you hired00:22:17 - Why passion and attitude beat experience in the AI era00:24:33 - How to train yourself to have a sense of urgency00:29:05 - Can introverts succeed in client facing engineering roles?00:32:17 - Lessons learned from interning at NASA and researching AI00:35:09 - Are we in an AI bubble that will burst soon?00:40:34 - Does becoming an FDE risk vendor lock-in for your career?00:43:36 - Final advice for engineers entering the 2025 job market#ForwardDeployedEngineer #FDE #SoftwareCareers

What if you could build a multi-million dollar software company where only 10% of your employees are developers? AFAS, a company with hundreds of millions in revenue, does exactly that with a lean team of just 70 engineers. In this episode, Engineering Manager Michiel Overeem pulls back the curtain on their unconventional strategies for achieving massive productivity with a surprisingly small team.In this episode, we cover:Why standardization is their secret weapon for efficiency.How they thrive without traditional Scrum ceremonies.The two distinct types of engineers they hire for success.The surprising details of their 4-day work week (paid for 5).This video is for engineering leaders and software developers who want to learn proven, counter-intuitive strategies to build hyper-effective teams and get more done, regardless of team size.Connect with Michiel:https://www.linkedin.com/in/movereemTimestamps:00:00:00 - Intro00:01:22 - The "10% Engineering" Paradox at a €100M+ Company00:03:20 - How Standardization Allows a Small Team to Do More00:04:27 - The Two Types of Engineers Every Successful Company Needs00:06:46 - Why Feeling Responsible is More Powerful Than Being Responsible00:09:33 - The Secret Sauce of High-Performing Engineering Teams00:11:52 - A Simple Method to Keep Engineers Connected to Customers00:14:22 - What We Look For When Hiring New Engineers00:17:09 - The #1 Red Flag That Will Get You Rejected in an Interview00:19:33 - Why We Don't Use Scrum (And What We Do Instead)00:22:51 - The Power of Strong, Decisive Leadership00:24:13 - How Our 4-Day Work Week Actually Works00:26:55 - Our Approach to Adopting AI Tools like Copilot00:28:19 - Final Advice: The Best Way to Grow Your Career#EngineeringCulture #Productivity #SoftwareDevelopment