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 platform
• How the best architects act more like scouts than cartographers
• Why "simple is complicated enough" beats clean code dogma at scale
• How to design systems that evolve instead of trying to predict 10 years out
• What junior engineers should actually do in the age of AI agents

For software engineers who want to think clearer, build better, and grow into the kind of engineer companies can't replace.

Timestamps:

00:00:00 - Intro

00:00:17 - Why You Should Increase Your Breadth, Not Just Focus

00:02:16 - The Only Skill That Survives Every Tech Cycle

00:04:14 - Buzzwords Are Just Old Ideas in New Clothes

00:05:26 - What Clients Say vs What They Actually Want

00:06:45 - The Bad Architects Are Easier to Spot

00:08:50 - Why Good Engineers Use Boring Technology

00:11:40 - Stop Building for 100x Scale on Day One

00:13:13 - The Dogma of Clean Code Is Hurting You

00:15:15 - Simple Is Complicated Enough at Scale

00:16:28 - Design Only for the Next Order of Magnitude

00:18:19 - How to Talk Tech with Non-Technical Stakeholders

00:19:30 - The $50,000-Per-Hour Container Terminal Lesson

00:22:11 - Architects Are No Longer Cartographers, They're Scouts

00:25:18 - Start with a Question, Not an Answer

00:26:49 - Junior to Senior in the Age of AI Agents

00:27:29 - Don't Be a Fool with a Tool

00:29:43 - From Explicit to Implicit Knowledge Economy

00:30:38 - Use AI to Validate, Not to Generate

#softwareengineering #engineeringcareer #softwarearchitecture

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 engineers
• Why juniors learning with AI have an edge over 20-year veterans
• The future of writing code by hand (and why fulfillment is shifting)
• Vibe coding, security holes, and what happens after 6 months
• The brutal reality of layoffs, gap years, and AI-driven hiring

If 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 engineers

Timestamps:

00:00:00 - Intro

00:00:54 - How to Become Technically Cracked in 2026

00:05:35 - 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 Disaster

00:15:04 - Why Leaders Demand Screen Sharing on Incident Calls

00:17:34 - "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 Era

00:32:15 - Are Most Programmers Actually Bad?

00:34:58 - Should You Take a Gap Year After a Layoff?

#softwareengineering #aicoding #techcareers

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 optional
• How AI magnifies your existing technical debt instead of fixing it
• The 6-month learning curve nobody warns you about
• Why your role as an engineer was never about writing code
• The environmental cost behind every prompt

Whether 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/bosrob

References:Token tracker: https://marketplace.visualstudio.com/items?itemName=RobBos.copilot-token-tracker
Dev survey: https://www.activestate.com/wp-content/uploads/2019/05/ActiveState-Developer-Survey-2019-Open-Source-Runtime-Pains.pdf

Timestamps:

00:00:00 - Intro

00:00:43 - The #1 Thing Engineers Get Wrong About AI

00:02:09 - How Much LLM Theory Do You Actually Need?

00:03:58 - Why Pair Programming Is Still the Best Way to Learn AI

00:05:26 - Why Rob Skips Tab Completion and Lives in Agent Mode

00:07:03 - The "AI Doesn't Increase Productivity" Debate

00:08:29 - Why Your Real Job Was Never Writing Code

00:09:14 - The 2-Hours-of-Coding Problem No One Talks About

00:11:02 - More Code = More Pressure on Your Review Process

00:12:21 - Why AI Magnifies Existing Technical Debt

00:13:39 - The Customer Who Couldn't Start AI With Developers Yet

00:15:11 - The Future Engineer: Reviewer, Not Writer

00:17:00 - Convincing the AI Skeptic Who Tried It Years Ago

00:19:17 - LLMs Explained Without Visuals (Attention & Semantics)

00:22:41 - Why Prompt Engineering Actually Matters

00:24:20 - From Zero to Hero: The 6-Month Learning Curve

00:26:18 - Is This Confrontational for 20-Year Veterans?

00:29:30 - Becoming a Better Engineer by Thinking in Systems

00:31:26 - Will AI Stop Working as Innovation Slows?

00:34:26 - The Lost Art of Pair Programming with AI

00:35:44 - Tribalism in AI Tools (And Why It's Pointless)

00:37:33 - Tool Agnostic: Start With the Foundations

00:39:40 - Is the IDE Still Relevant?

00:40:50 - The Bluescreen Story That Changed His Mind

00:41:47 - The Hidden Environmental Cost of AI Coding

00:44:15 - 36 Million Tokens in 30 Days: What Does It Mean?

00:45:47 - Running LLMs at the Edge to Cut the Footprint

00:46:48 - Why You Should Be Allowed to Wait Five Minutes Longer

00:47:05 - 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 inside
• Using AI agents without losing your identity as an engineer
• Why open source beats a tailored resume in today's market
• How consistent contributions can reshape your entire career

If 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/bschaatsbergen

OUTILNE

00:00:00 - Intro

00:01:04 - How Open Source Shaped My Entire Career

00:02:14 - Why I Take Pride in Every PR I Write

00:03:16 - Open Source vs Personal Projects: The Real Difference

00:04:18 - Why Your PRs Get Ignored (And How to Fix It)

00:05:41 - Know Your Audience: The Counterintuitive PR Hack

00:06:35 - Dealing With Imposter Syndrome as a Contributor

00:07:10 - Read Code Like a Writer Reads Books

00:09:31 - 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 Noise

00:13:44 - Killed With Kindness: The AI Slop Problem

00:16:17 - How Maintainers Are Fighting AI Slop

00:18:02 - How I Actually Use AI Agents in My Workflow

00:19:11 - Don't Outsource Your Thinking to AI

00:20:11 - Who's Liable for AI-Generated Code?

00:21:16 - Earned Rights: Why Trust Matters in Open Source

00:22:52 - How to Approach People at Tech Conferences

00:24:52 - Open Source Is Not a Democracy

00:26:04 - Why Open Source Beats a Tailored Resume

00:27:12 - Never Contribute With the Goal of Getting Hired

00:28:38 - The Real Reason Consistency Pays Off

00:29:30 - Admitting I'm a University Dropout

00:30:42 - Why I Haven't Contributed in Weeks (And That's Okay)

00:32:07 - The Trap of Chasing Contributor Rankings

00:34:32 - Open Source Lets You Work With Anyone in the World

00:35:52 - 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 begins
• The team composition that consistently delivers results
• Peter Naur's Theory Building and why documentation alone falls short
• How knowledge leaving your team turns working systems into legacy
• Why assuming you're wrong leads to better architecture

Whether 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.dev

TIMESTAMPS

00:00:00 - Intro

00:01:17 - Why He Keeps Choosing Engineering Over Management

00:04:01 - Three Seniors Solved in Three Weeks What Management Couldn't

00:05:14 - The Signals You Miss When You're Not in the Team

00:06:26 - The #1 Skill Behind Every Successful Project

00:08:04 - Why Production Is the Starting Line, Not the Finish

00:10:13 - The Habit Most Teams Skip After Deploying

00:11:28 - Why the Best Teams Mix Designers and Engineers

00:14:36 - Finding the Right People for the Job at Hand

00:17:01 - What Juniors Bring That Seniors Can't

00:20:57 - How to Handle Ideas You Disagree With as a Senior

00:24:21 - A Simple Technique to Surface Everyone's Best Ideas

00:27:09 - What Makes a System Survive Long-Term

00:30:53 - What Actually Makes a System "Legacy"

00:35:01 - The Knowledge That Keeps Software Alive

00:36:06 - Peter Naur's Theory Building: Why Documentation Isn't Enough

00:40:06 - How Knowledge Loss Is Killing Your Codebase

00:42:42 - The Hidden Risk of AI Tools for Team Knowledge

00:48:14 - Why You Should Assume Everything You Build Is Wrong

00:51:31 - Make Hard Things Easy to Change

#SoftwareEngineering #SystemDesign #TechPodcast

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 entirely
• The counterintuitive research showing junior engineers adopt AI faster than seniors
• "Coding is cheap, software is expensive" and what that means for your career
• How the boundary between product and engineering is disappearing
• Why most AI coding tools are 80% the same and what to focus on instead

Whether 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 - Intro

00:01:15 - Is AI Productivity the Whole Story?

00:03:26 - Why Outcomes Matter More Than Code Output

00:04:13 - The Real Value Was Never in the Coding

00:06:06 - The Product-Engineering Boundary Is Disappearing

00:07:37 - Why Junior Engineers Are Actually in High Demand

00:09:41 - Research Says Juniors Adopt AI Faster Than Seniors

00:11:31 - The Rise of Comb-Shaped Engineers

00:12:32 - The Energy Juniors Bring That Teams Need

00:14:06 - How Seniors Codify Knowledge for Agents and Humans

00:16:35 - Advice for Early Career Engineers Right Now

00:19:04 - Old Principles Getting a New Polish

00:21:13 - Coding Is Cheap, Software Is Expensive

00:22:52 - 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 Content

00:30:12 - Why Your AI Output Needs a Human Value Add

00:32:12 - Is Open Source at Risk Because of AI?

00:35:09 - When Your Favorite Tool Doesn't Follow You to the Next Job

00:36:45 - Most AI Coding Tools Are 80% the Same

00:38:15 - What Engineering Leaders Should Enable Beyond Licensing

00:42:58 - Should You Leave If Your Company Won't Let You Experiment?

00:45:16 - Platform Engineering as the Foundation for AI Adoption

Guest: Suzanne Daniels
https://www.linkedin.com/in/suzannedaniels

#SoftwareEngineering #AICoding #BeyondCoding

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 it
• How to prove feature parity between legacy and modern systems
• Why vibe coding without architecture knowledge gives you zero control
• The shift from execution-focused engineering to orchestration
• Why Dennis worries about the next generation of engineers

Whether 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 - Intro
00:00:51 - Dennis's Early AI Engineering Assignments
00:02:23 - Side Projects: Reviving a 20-Year-Old Game in Rust
00:04:36 - Why Vibe Coding Without Fundamentals Fails
00:05:15 - The Fundamentals You Need for Code Migration
00:06:45 - Proving Feature Parity with Automated Testing
00:08:12 - Writing Tests First as Risk Mitigation
00:10:13 - How Much Should You Care About Code Structure?
00:11:18 - Migrating in Small Pieces of Value
00:12:26 - 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 Painful
00:16:12 - Prompting as the New Bottleneck
00:17:23 - Parallelizing Work Across Projects
00:19:08 - Why System Design Is the #1 Audience Demand
00:20:19 - AI as a Differentiator for Strong Architects
00:21:11 - Why the New Generation Should Worry
00:23:01 - Are Bootcamps Still Worth It?
00:25:15 - The Shift from Collaboration to Business Understanding
00:27:56 - Infrastructure as a Core Competency Bet
00:30:15 - Deterministic vs Non-Deterministic Code Generation
00:32:16 - Can This Approach Scale to Million-Line Codebases?
00:34:20 - Why a Finger-Snap Migration Would Scare You
00:37:01 - Where to Start with Your Own Legacy Codebase
00:38:43 - Which Languages Do AI Models Struggle With?
00:40:24 - Building Around Hallucination with Scaffolding
00:42:30 - Spec-Driven Development as the Future Way of Working
00:43:30 - Turning a Non-Technical Colleague into a "Developer" in an Hour
00:46:21 - When the House Is on Fire, That's When You Need Real Engineers

Projects we discussed:
Agent designer - hurozo.com
Game project - Zorlore.com (https://github.com/zorlore/)
Vibe coded solar system simulation - spacehaste.com

#SoftwareEngineering #SystemDesign #AIEngineering

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 flows
• The 30% rule: why you should feel uncomfortable at work and what it means if you don't
• How to pitch to senior leadership and actually get buy-in
• Why AI makes distribution the real challenge, not building

If you're a senior engineer trying to grow beyond your current ceiling, this one is worth your time.

Timestamps:

00:00:00 - Intro

00:00:42 - How to Pitch to Senior Leadership and Get Buy-In

00:03:26 - Why You Should Feel Uncomfortable 30% of the Time

00:06:33 - How to Break Through a Seniority Ceiling

00:08:24 - The Burden of Context: Why Being the Go-To Person Traps You

00:10:16 - How Ian Became CTO Without Trying To

00:13:40 - Why a CTO's Job Is Mostly Coaching Now

00:18:20 - Understanding Incentives: The Key to Navigating Any Org

00:23:08 - Startups vs. Large Companies: Completely Different Rules

00:25:00 - Why AI Makes Distribution the Real Problem, Not Building

00:28:16 - The Hidden Maintenance Risk of Vibe-Coded Software

00:30:13 - Security and Compliance: More Nuanced Than Engineers Think

00:36:54 - Where "Architecture Follows the Money" Came From

00:42:36 - The Wrong Number of Customers: A Systems Thinking Story

00:47:23 - Why Engineers Think Individually Instead of Systemically

00:51:53 - How to Start Thinking in Systems

00:57:50 - How to Create Cross-Pollination in Consulting Teams

00:59:39 - What CTOs Actually Look for When Hiring

01:00:34 - 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 - Intro

00:01:05 - Why Dennis Refuses to Stop Coding (After 30 Years)

00:02:54 - The Only Way to Be an Effective Software Architect

00:04:43 - What Happens When Teams Copy Patterns Without Understanding Them

00:06:23 - Software Engineering Is About Battling Complexity

00:08:20 - When to Break Consistency to Reduce Complexity

00:09:24 - The Problem with Overzealous SOLID Principles

00:11:06 - The Future Where We Don't Care About Code Anymore

00:12:07 - How Dennis Built an Open Source Library with GitHub Copilot

00:14:18 - Accepting AI-Generated Code That Doesn't Meet Your Standards

00:16:39 - How to Use AI Without Losing Code Quality

00:17:41 - The Execution Is Accelerating — What Actually Matters Now

00:20:19 - Why Tests Are Your Safety Net in an AI-First World

00:23:44 - Lessons Learned from Letting AI Run Unsupervised

00:26:46 - Should Teams Standardize Which AI Tool They Use?

00:27:32 - Junior Devs and AI: Learning Skills vs. Speed

00:29:21 - How to Stay Curious and Critical in an AI-Assisted Team

00:33:43 - How to Build a Software Engineer from Scratch Today

00:34:38 - Dennis's Emoji-Based Pull Request Review System

00:36:45 - What AI Still Can't Do: Holistic Architectural Thinking

00:38:38 - Why Your Git History Is More Valuable Than You Think

00:40:44 - Decision Records: The Architecture Investment That Pays Off

00:43:16 - When Documentation Saved Dennis from a Bad Management Decision

00:44:47 - The Tailwind Layoffs and the Open Source Business Model Crisis

00:46:27 - Guidelines for Consuming Open Source Responsibly

00:49:51 - Why You Should Open Source Your Own Projects

Guest: 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 management

In this episode, we cover:

• Ingredients for designing systems that scale to millions of users
• How to know when to compromise on architecture
• The trade-offs of going from IC to engineering manager and why the role is harder than it looks
• How to handle opinionated engineers, set team guardrails, and build high-performing engineering culture

Whether 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 - Intro

00:01:05 - The Ingredients for Building Systems at Scale

00:02:23 - When to Compromise on Your Foundation

00:03:42 - Scaling from 2,000 to 5 Million Users

00:06:37 - Why Clarity Beats Seniority Every Time

00:08:27 - The Danger of Muscle Memory in Engineering

00:10:25 - MVP Mindset: What You Can and Can't Compromise

00:13:22 - How High-Performing Teams Handle Growing Complexity

00:15:04 - Who Owns the Assumptions? Shared Team Responsibility

00:17:04 - Building Open Frameworks Instead of Closed Rules

00:19:53 - Latency Is Overrated (Here's Why)

00:22:52 - Recipes for Disaster: The Biggest System Design Pitfalls

00:24:17 - The Scala Horror Story: When Elegance Kills Velocity

00:26:52 - How to Handle Opinionated Engineers on Your Team

00:29:03 - Setting Guardrails: The Manager's Design Responsibility

00:32:01 - The Hardest Trade-Off Going from IC to Engineering Manager

00:34:35 - 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

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 early
• How to identify and remove friction points in the software development lifecycle
• The reality of using AI agents in production and who is actually responsible for the code

If 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-635013100

Timestamps:

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