Beyond Coding

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