Beyond Coding

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

The difference between a junior and a senior engineer isn't coding speed, it's knowing when to say "no."

"The best code you can write is the code you don't write." In this episode, I sit down with Alessandro Mautone (Senior Software Engineer at Aquablu, ex-WeTransfer) to discuss the reality of engineering at a scale-up: how do you maintain technical excellence when the business demands speed?

We break down why delivering features "fast" pays your salary, but how to negotiate deadlines so you don't drown in technical debt later. If you want to move from writing code to owning product decisions, this conversation is for you.

In this episode, we cover:

- How to push back on features and negotiate deadlines without upsetting stakeholders

- Why chasing "perfect code" can hurt a company in growth mode

- The Generalist vs. Specialist career path: Which one is right for you?

- The potential pitfalls of using AI for unit tests without proper oversight

Timestamps:

00:00:00 - Intro

00:01:06 - Balancing Technical Excellence With Delivery Speed

00:04:11 - Why Delivering Features Pays Your Salary

00:06:51 - The Importance of Ownership and "Skin in the Game"

00:08:59 - Leaving WeTransfer: When Company Direction Shifts

00:11:49 - The Generalist vs. Specialist Career Path Debate

00:16:46 - How to Attract Top Engineering Talent to Your Team

00:18:50 - Is LeetCode the Right Way to Hire for Scale-Ups?

00:23:16 - Learning to "Say No" is a Sign of Seniority

00:25:17 - Negotiating Scope Without Burning Bridges

00:26:02 - When AI Generates Bad Unit Tests

00:28:14 - Never Compromise on Tests, Even in "Code Red"

00:33:59 - Communicating Technical Concepts to Non-Tech Stakeholders

00:35:35 - The Never-Ending Battle Against Complexity

00:37:26 - When to Build for the Future vs. Ship Now

00:42:30 - A Real-World Example of Refactoring for Simplicity

00:46:48 - The Skill That Will Be Make or Break for Engineers

#SoftwareEngineering #ScaleUp #TechnicalDebt

We are at a unique point in history where there is finally an alternative to human coding. If AI can write the code effectively, what is left for the software engineer?

In this episode, Joris Conijn (AWS CTO at Xebia) argues that the era of "just coding" is over. We discuss why senior developers are safe (for now), why juniors are at risk of never learning the fundamentals, and how "Shadow AI" is forcing companies to change their security strategies.

Most importantly, we break down the difference between a "Programmer" and a "Software Engineer" with the introduction of agentic tools. If you want to future-proof your career and move from writing lines of code to designing systems, this conversation is for you.

In this episode, we cover:

• Why banning AI at work actually increases your security risk
• How to use AI to automate the boring parts of the SDLC (requirements & user stories)
• The critical difference between "Coding" and "System Architecture"
• Why you should check your AI Agents into your Git repository
• The 20-year problem: what happens when engineers never learn the fundamentals?

Connect with Joris Conijn:

https://www.linkedin.com/in/jorisconijn

TIMESTAMPS

00:00:00 - Intro

00:01:11 - What Keeps a CTO Excited About Tech?

00:02:58 - Stop Being the "Department of No" in Security

00:05:28 - The Real Risk of Banning AI at Work

00:06:32 - When Developers Hold the Organization Hostage

00:08:14 - The Hidden Dangers of Instant AI Code Fixes

00:09:50 - Will Future Devs Understand Object Oriented Programming?

00:11:36 - Using AI to Accelerate Learning vs Copy-Pasting

00:13:17 - Why Testing Matters More When AI Writes Code

00:16:42 - Automating the Boring Parts of the SDLC

00:19:06 - How to Turn Meeting Transcripts into User Stories

00:21:36 - The Critical Skill of Making Implicit Knowledge Explicit

00:23:10 - Why You Should Stop Obsessing Over Story Points

00:27:46 - The "A-Team" Approach to High-Trust Development

00:29:54 - Running Parallel Workflows with AI Agents

00:33:34 - Pro Tip: Check Your AI Agents into Git

00:35:52 - Balancing Autonomy and Governance in Large Teams

00:39:19 - There Is Finally an Alternative to Human Coders

00:41:07 - Programmer vs Software Engineer: What is the Difference?

00:44:45 - How to Teach Software Engineering in the AI Era

#SoftwareEngineering #SystemDesign #AIAgents

Is your internal developer platform actually improving velocity, or is it a bottleneck? We discuss why platform teams building "cool" abstractions is a red flag, and you should aim to create the best platform for software engineers.

In this episode, we cover:

• Why "Golden Paths" can turn into roadblocks for developers.
• The danger of Shadow IT and why it’s a symptom of a failed platform.
• How to measure if your platform is saving time.

Connect with Adnan Alshar:

https://www.linkedin.com/in/adnanmalshar92

Connect with Jelmer de Jong:

https://www.linkedin.com/in/jelmerdejong-xebia

00:00:00 - Intro

00:00:54 - Is DevOps Dead? The Truth About Platform Engineering

00:03:07 - Why Developers Are Drowning in Complexity Today

00:04:37 - Why Having No Platform Is Better Than a Bad Platform

00:07:20 - Treating Software Engineers as Customers of the Platform

00:11:26 - The Exact Moment You Should Start Building a Platform

00:14:18 - Who Should Be on Your First Platform Team?

00:17:33 - Turning Your Angriest Developers Into Platform Evangelists

00:18:57 - Key Metrics: How to Measure Platform Engineering Success

00:21:01 - Why 60% of Companies Don't Measure Platform Success

00:23:35 - Why No Metrics Is the Biggest Red Flag

00:25:23 - The Disconnect Between Executives and AI Readiness

00:31:34 - Integrating AI Tools and Large Language Models Securely

00:34:22 - Shadow IT: The Symptom of a Broken Platform

00:38:03 - How to Scale Without Becoming a Bottleneck

00:41:45 - Don’t Forget the Business Side of Platform Engineering

#PlatformEngineering #DevOps #DeveloperProductivity

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 practice
• The "Golden Handcuffs": Why high salaries keep engineers in toxic jobs
• How to transition into leadership without waiting for a title

Timestamps

00:00:00 - 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