Beyond Coding

Latest Episodes:

Promotions, Salary & Leadership: I Answer Your Toughest Tech Career Questions Oct 29, 2025

Show notes

You asked, I answered. In this Q&A episode, I tackle the toughest career questions you submitted: from getting promoted when the process feels political, to negotiating salary, to leading projects as an IC.

In this episode, we cover:

* Holding peers accountable when you're not their manager

* Navigating promotions when the process is political or unclear

* Increasing your salary with strategic job offers

* Building real authority and getting noticed by leadership

* Staying relevant in the age of AI without burning out

This is for software engineers who want practical strategies to level up their careers, increase their earning potential, and make real impact without the fluff.

Join me at React Advanced and Tech Lead Conf in London:

https://ti.to/gitnation/react-advanced-london-2025/discount/CODING20

Timestamps:

00:00:00 - Intro

00:00:19 - Holding Peers Accountable When Managers Won't Help

00:03:58 - The Surprising Truth About Code "Quality"

00:05:43 - Scaling Accountability Across Large Teams

00:07:50 - When Climbing the Career Ladder Feels Political

00:12:37 - How to Stay Relevant in Tech Without Burning Out

00:14:49 - The Key to Learning Without Feeling Overwhelmed

00:15:18 - The Real Difference for Engineers Working Globally

00:17:44 - What to Do When You Get a Better Job Offer

00:20:51 - Finding Motivation Beyond a Higher Salary

00:21:41 - How to Build Real Credibility and Authority

00:25:31 - The Advice I'd Give My Junior Developer Self

00:29:05 - The Art of Effective Delegation

00:31:47 - Why Delegation Is Really an Act of Trust

00:32:21 - Team Player vs. Individual Star: A False Choice?

00:34:43 - The #1 Personal Development Skill for Engineers

00:37:11 - The Hidden Dangers of Relying on AI Tools

00:40:08 - Is Volunteering at Tech Conferences Worth It?

00:42:50 - My Personal Struggle with Embracing Change

00:45:32 - The Career "Regret" I Don't Actually Regret

00:46:45 - How to Stay Productive While Dealing with Grief

00:49:08 - My Process for Finding Great Podcast Guests

00:50:48 - The Secret to Making Guests Feel Comfortable

00:52:06 - How Podcasting Transformed My Communication Skills

00:53:35 - Handling Guarded or Difficult Podcast Guests

00:56:11 - Final Thoughts & How to Support the Channel

Got questions for the next Q&A? Drop them in the comments 👇

#SoftwareEngineering #CareerGrowth #TechLeadership

What Separates Good Engineers from Great Ones Oct 22, 2025

Show notes

What's the real difference between a good software engineer and a truly great one? It’s more than just coding skill. It's a specific mindset, a disciplined approach to technology, and a deep understanding of core principles. This is the roadmap to leveling up your career.

In this conversation with Sander Mak, Director of Technology at Picnic, we discuss the methods they use to train world-class engineers.

You will learn:

The "under the hood" knowledge that truly matters.

Why great engineers often choose "boring," proven technology.

The critical transition from being a coder to a product-focused engineer.

The most common pitfall that holds good developers back.

If you're a software developer looking to move beyond "good enough" and achieve greatness in your craft, this is the episode for you.

Connect with Sander:

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

Timestamps:

00:00:00 - Intro

00:00:30 - Building Picnic's Tech Academy for New Engineers

00:04:37 - The Key Mindset of a Successful Junior Engineer

00:08:01 - A Look Inside the Engineering Training Curriculum

00:12:19 - The Common Pitfall of Copying Without Understanding

00:14:10 - How Deep "Under the Hood" Knowledge Should Go

00:17:41 - Why Great Engineers Value "Boring" Technology

00:21:44 - Improving Developer Experience and Team Productivity

00:30:02 - The Transition from Coder to Product Engineer

00:34:18 - Key Advice for Self-Taught Developers

00:35:41 - Using AI for Learning vs. for Code Generation

#SoftwareEngineering #DeveloperCareer #Coding

From 6 Engineers to 2: Why Product and Engineering Are Merging Oct 15, 2025

Show notes

What if the standard 6-person software team is now obsolete? AI tooling isn't just a productivity booster; it's fundamentally blurring the lines between product and engineering, enabling smaller, more powerful teams to achieve what once took an entire department.

We're joined by Kate Ivanova, a Product Manager with years of experience building AI products at Big Tech companies, to discuss this tectonic shift. She explains why the traditional handoff between disciplines is breaking down and what the new, merged "product-engineer" role looks like.

In this episode, we cover:

- Why AI enables smaller teams to have a massive impact

- The merging roles of Product, Engineering, and Design

- What skills make you one of the indispensable "2 engineers"

- How to structure and manage a hyper-efficient, AI-native team

This is a must-watch for founders building lean companies, and for engineers and PMs who want to understand their evolving role in the age of AI.

Timestamps:

00:00:00 - Intro

00:00:57 - Are Agile Processes Obsolete in the Age of AI?

00:02:46 - Why Product Managers Are Redefining Team Processes

00:04:35 - The Mindset You Need for AI Product Development

00:07:54 - How AI Is Forcing Product and Engineering Closer Together

00:11:26 - Using AI as Your Personal Feedback Co-Pilot

00:15:23 - The Critical Mistake to Avoid When Using AI for Product

00:20:45 - The Ideal AI Product Team Composition of the Future

00:26:10 - The New Expectations for Software Engineers in the AI Era

00:32:05 - A Better Way to Manage Tech Debt and Developer Happiness

00:34:46 - What Truly Makes Developers Happy at Work

00:37:43 - Co-Creating a Vision That Actually Motivates Your Team

00:40:59 - How to Receive Tough Feedback as a Growth Opportunity

00:45:37 - The Painful Decision to Kill a Failing Project

00:48:44 - The Most Important Skill for the AI Era

How Hackathons Make You a Better Software Engineer Oct 08, 2025

Show notes

What if you could turn a weekend project into a core product feature at a major tech company? We sit down with Behrouz Pooladrak, a software engineer and hackathon legend at Booking.com, to uncover how these intense competitions can fast-track your skills, career, and impact. He shares the mindset and strategies that took his ideas from a one-day build to a real-world product used by millions.

In this episode, we cover:

How to treat your hackathon project like a mini-startup to guarantee success.

The surprising skills you gain from short-term projects that your daily job can't teach you.

How companies like Booking.com use hackathons to innovate and train new talent.

Why personal projects are the secret weapon for career growth.

This episode is for any software engineer looking to distinguish themselves, learn new technologies rapidly, and make a real impact in the tech industry.

Timestamps:

00:00:49 - The Mindset of a Prolific Builder
00:02:42 - How AI Helps You Build an MVP in One Day
00:06:26 - Why This Engineer is a Hackathon "Living Legend"
00:07:41 - From Hackathon Idea to Real AI Product
00:11:42 - The Secret to Winning: Treat it Like a Startup
00:17:22 - How Booking.com Onboards Juniors with a 4-Week Hackathon
00:20:25 - Why We Still Need Junior Engineers in the Age of AI
00:26:57 - The #1 Struggle Teams Face in Hackathons
00:31:04 - The Real Reason to Join a Hackathon (It’s Not the Prize)
00:35:46 - How to Start and Finish Your Personal Projects
00:40:12 - The Feedback Loop Between Your Job and Hobby Projects

#SoftwareEngineering #Hackathon #CareerGrowth

AI Startup CEO Reveals What Really Kills AI Projects Oct 01, 2025

Show notes

What if the biggest obstacles to AI innovation aren't what you think? Deeploy CEO Maarten Stolk shares his controversial but effective strategies for building successful AI products and ecosystems, challenging the common wisdom around bottom-up initiatives and regulation.

In this episode, we cover:

Why bottom-up initiatives fail without strong top-down vision.

The surprising benefits of the EU's AI Act for innovation.

How to build a thriving AI ecosystem from the ground up.

The single most important metric for AI observability.

This conversation is for tech leaders, founders, and engineers who want to move beyond AI experiments and build real-world, production-ready systems.

Timestamps:

00:00:00 - Intro

00:00:45 - Why Maarten Started a Dutch AI Hub

00:02:15 - The "Flywheel" Effect Crucial for AI Success

00:04:42 - The Hard Truth: Why the Netherlands is Lagging in AI

00:07:52 - A Controversial Take: The EU AI Act is Actually Good for Everyone

00:11:26 - The Real Bottleneck to Innovation Isn't Regulation

00:14:25 - From POC to Production: Why Top-Down Vision is Non-Negotiable

00:17:13 - A Wake-Up Call for Inexperienced Leadership Teams

00:20:30 - How Winning Companies Use AI to Dominate Their Market

00:23:44 - The Right Way to Learn From Your Competitors

00:27:30 - Maarten Outsourced Core Development to an AI Company

00:31:59 - The #1 Metric You Must Track for AI Observability

00:36:03 - Open-Source vs. Closed-Source: Which AI Model Will Win?

00:40:23 - The Inevitable Crisis That Will Force Innovation

00:42:19 - The Power of Having a Long-Term Personal Vision

#AIStrategy #TechLeadership #Innovation

The Graph Problem Most Developers Don't Know They Have Sep 25, 2025

Show notes

As a developer, you're trained to think in rows and tables. But what if that's the exact reason you're missing the most powerful connections in your data? There's a fundamental "Graph Problem" hiding in plain sight in almost every application, and once you see it, you'll wonder how you ever missed it.

In this episode, we reveal this "obvious" secret and show you how to leverage it to build smarter, more accurate, and context-aware AI.

In this episode/video, we cover:

The "Graph Problem" explained: Why you have more graph problems than you think.
Why basic RAG isn't enough, and how Graph RAG provides the context your AI is missing.
How to uncover the hidden relationships in your unstructured data and build a knowledge graph.
Real-world examples (from Amazon to your own notes) that reveal the graph structure all around you.
The #1 reason knowledge graph projects fail and how to avoid it.

This conversation is for any developer who feels their projects are hitting a wall. If you're ready for the "aha!" moment that will change how you look at data forever, this episode is for you.

Timestamps:00:00:00 - Intro00:00:39 - From Unstructured Data to a Knowledge Graph00:02:00 - The Experiment: What Happens When You Break a Knowledge Graph?00:05:41 - What Are Ontologies in the Graph World?00:07:35 - The Graph Problem You Didn't Know You Had00:09:09 - Why Graphs Are So Good for GenAI Context00:10:10 - The Best Way to Create Vector Embeddings for Graphs00:12:50 - Using Graphs to Solve Extreme Corporate Complexity00:17:14 - Real-World Problems That Are Actually Graph Problems00:19:31 - How to Find The Right Expert in Your Company00:23:33 - The Rise of Federated RAG Agents00:25:31 - The #1 Reason Knowledge Graph Projects Fail00:29:37 - A Standard Query Language for Graphs (GQL)00:32:53 - Why Teams Are Moving From RAG to Graph RAG00:34:34 - Should Your Company Build Its Own AI Assistant?00:38:28 - The "Fear of Missing Out" Driving Bad AI Projects00:40:21 - The Dangers of Chaotic vs. Laser-Focused Company Priorities00:44:05 - Why Gantt Charts Don't Work for Software00:47:08 - How Top Engineers Actually Learn New Technologies

Guests on this podcast express their own views and do not represent their employers.

#GraphDatabase #KnowledgeGraph #SoftwareArchitecture

How Deepfakes are Evolving (And What You NEED to Know) Sep 17, 2025

Show notes

It takes just three seconds for AI to steal your voice and impersonate you in a way no one can detect. How can you protect yourself, your family, and your finances when seeing and hearing is no longer believing?

In this episode, deepfake expert Parya Lotfi reveals the shocking reality of AI-driven scams, from fraudulent bank transfers to fake kidnapping calls. We uncover how criminals operate and what you can do to spot the lies before it's too late.

In this episode/video, we cover:

- How criminals use 3-second voice clones for scams

- The shocking story of a North Korean deepfake spy

- Why facial and voice ID are no longer secure

- How to use AI to detect other AI fakes

This video is for anyone who wants to understand the real-world dangers of deepfake technology and learn actionable steps to protect themselves in our new "fake reality."

Connect with Parya:

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

Timestamps:

00:00:00 - Intro

00:00:35 - The Scary Reality of AI-Generated Videos

00:02:32 - The Dangerous Side of Facial & Voice Biometrics

00:03:45 - The Disturbing Reality of Voice Cloning Scams

00:06:46 - How to Use AI to Catch AI-Generated Fakes

00:10:11 - Solving AI's "Black Box" Problem with Explainability

00:12:10 - The Different Types of Deepfakes Criminals Use

00:14:15 - How Deepfakes Are Used to Launder Millions From Banks

00:18:18 - Inside the Darknet's "Deepfake-as-a-Service" Business

00:22:32 - Why Banning Deepfake Technology Is Impossible

00:24:58 - How Deepfakes Are Being Weaponized in Global Conflicts

00:27:30 - Red Teaming: How to Think Like a Deepfake Criminal

00:29:09 - The North Korean Spy Who Used a Deepfake to Get a Job

00:31:54 - The Ultimate Goal: A Deepfake Detector for Everyone

00:37:23 - The Future That Scares Me: AGI and Self-Aware Robots

00:44:33 - The Journey of Building a Deepfake Detection Company

00:47:42 - The Surprising Reason Deepfake Detection Is So Hard

00:54:44 - Who Is Responsible When You Get Scammed by a Deepfake?

00:58:25 - The Rise of AI Influencers and Their Tragic Consequences

#Deepfake #Cybersecurity #ArtificialIntelligence

From Pixels to Tokens: UX Is Not Enough Anymore Sep 10, 2025

Show notes

What does it take to build AI features at the scale of Microsoft Copilot?

Senior Product Manager Stéphanie Visser reveals the massive shifts in product development, from focusing on pixels to tokens and embracing a culture of rapid, data-driven experimentation.

Learn how the roles of PMs, engineers, and scientists are evolving and what it takes to succeed.

In this episode, we cover:

The shift from UX-focused products to output-quality-focused AI.
How to run experiments and decide when an AI feature is ready to ship.
The changing roles and expectations for PMs, engineers, and data scientists.
Building trust and a strong product culture in a distributed AI team.

This episode is a must-watch for product managers, engineers, and tech leaders looking to adapt their processes for the age of AI and accelerate their delivery cycles.

Timestamps:

00:00:00 - How Microsoft Builds AI Features

00:00:49 - The #1 Thing That Changed for Product Managers

01:28 - From Pixels to Tokens: The AI Product Shift

02:58 - Why AI Is All About Output Quality, Not UX

04:46 - When Is an AI Feature "Good Enough" to Ship?

06:45 - The "Non-Embarrassment Bar" for Releasing AI

09:07 - Why Old User Feedback Methods Don't Work for AI

12:28 - The New Expectations for Software Engineers in AI

15:33 - When to Involve Engineers in the Product Process

17:43 - How Microsoft Structures Its AI Product Teams

20:40 - Why 3-Month Planning Is Obsolete in the AI Era

22:42 - How to Remove Bias From Your Product Decisions

25:36 - Balancing Data vs. User Intuition in AI

27:44 - The Biggest Bottleneck in AI Experimentation

31:12 - How to Define the Right Metrics for Your AI Product

33:39 - Building Trust and Culture in a Remote Team

37:47 - The Most Underrated Skill for Product Managers

40:57 - How to Cultivate a Strong Product Culture

44:32 - The AI Tools a Microsoft PM Actually Uses

46:29 - How to Manage the Expanding Scope of the PM Role

Connect with Stéphanie Visser:

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

Connect with Patrick Akil:

https://www.linkedin.com/in/patrick-akil

https://twitter.com/PatrickAkil_

Sponsors:

Xebia - https://xebia.com

#ProductManagement #AI #Microsoft

Stop Hiring Junior Engineers Because of AI? Sep 03, 2025

Show notes

As AI accelerates development, many companies are halting junior hiring, believing AI tools can replace them. Shahin Shahkarami, Director of Data & AI at Ikea Retail, argues this is a massive mistake and that now is actually the best time to invest in new talent.

In this episode/video, we cover:

Why companies should hire junior talent despite the rise of AI.

How the role of a data scientist is evolving with generative AI.

The most valuable business use cases for AI beyond chatbots.

This conversation is for tech leaders, hiring managers, and aspiring developers looking to understand how to build and grow their careers in the age of AI.

Connect with Shahin:

https://www.linkedin.com/in/shahin-shahkarami

Full episode on YouTube ▶️

https://youtu.be/Jui-8Lx6kvk

Beyond Coding Podcast with ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠🎙Patrick Akil⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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Timestamps:

0:00:00 - Why Now Is The Best Time to Hire Junior Talent

00:01:46 - The Massive Mistake Companies Make with AI Hiring

00:03:11 - How Junior Talent Can Stand Out in 2025

00:04:39 - Why Senior-Only Teams Can Become Negative

00:05:56 - The ROI Problem: What If Your Junior Talent Leaves?

00:07:44 - How Companies Can Actually Retain Top Talent

00:11:06 - How AI Has Changed Personal Productivity for Leaders

00:15:34 - How the Role of a Data Scientist Is Evolving

00:18:28 - The 80/20 Rule of Building AI Products

00:21:37 - The Rise of the "AI Engineer" and What It Means

00:23:37 - A Simple Strategy for Personal Growth in Tech

00:28:46 - Where Generative AI Delivers Real Business Value

00:32:37 - Why You Must Differentiate Your Business With AI Now

00:38:09 - A 2-Fold Strategy for Prioritizing AI Projects

00:40:41 - The Power of a 20% Experimentation Culture

00:43:10 - The Problem With Chatbots as a First AI Project

00:46:20 - The Danger of Releasing an 80% Good AI Product

#AI #TechCareers #DataScience

How to Master Software Engineering (From Junior to Architect) Aug 27, 2025

Show notes

Feeling overwhelmed by the constant change in software engineering? After 25 years in the industry, CTO Joris Kuipers shares a pragmatic roadmap to not just survive, but achieve true mastery in your craft, whether you're a junior developer or a seasoned architect.

In this episode, we cover:

How to focus your learning when new technologies emerge daily

The ideal environments for junior and senior engineers to thrive

Why rapid, frequent deployment is SAFER than slow, careful releases

The critical feedback loops you must have to accelerate your career

How to move beyond rigid processes like Scrum to deliver real value

This is for any software engineer who wants to stop just "doing the work" and start building a deeply fulfilling and successful career by mastering their craft.

Connect with Joris:

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

Full episode on YouTube ▶️

https://youtu.be/pNtkOZuWetg

Beyond Coding Podcast with ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠🎙Patrick Akil⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Powered by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Xebia⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠!

Timestamps:

00:00:00 - The #1 Thing That Gives a 25-Year CTO Energy

00:02:39 - How to Maintain Mastery When Tech Constantly Changes

00:05:30 - The Chicken-and-Egg Problem of Learning on the Job

00:08:49 - What Junior Developers Should Master First

00:11:39 - The Danger of Starting Your Career at a Small Startup