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 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