Beyond Coding

System design interviews often focus on theoretical complexity, but how do Senior Engineers at GitHub actually approach scaling? In this episode, Bassem Dghaidi breaks down how to think about system design when real business impact is on the line.

We discuss why "simple is complicated enough," the dangers of premature scaling, and why vertical scaling often beats complex distributed systems. If you want to bridge the gap between theory and practice, and understand how to design software that actually serves the business, this conversation is for you.

In this episode, we cover:

- The "Order of Magnitude" rule for scaling systems

- Why GitHub often runs millions of requests on simple architecture

- How to communicate technical constraints to non-technical stakeholders

- Why 90% of Bassem's code is now written by AI agents

Connect with Bassem Dghaidi:

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

Timestamps:

00:00:00 - Intro

00:00:48 - Theory vs. Practice in System Design

00:02:06 - The Startup That Almost Failed via Kubernetes

00:03:33 - How GitHub Scales (It's Simpler Than You Think)

00:05:20 - The Underrated Power of Vertical Scaling

00:08:23 - Why Big Tech Interviews for Scale You Don't Need Yet

00:10:39 - Software Evolves, It Isn't Just "Built"

00:11:53 - Only Design for the Next Order of Magnitude

00:15:39 - Stop Building Generic Frameworks

00:18:17 - "Hacking" the System Design Interview

00:21:29 - Translating Tech Problems to Business Risks

00:27:37 - Layoffs & Engineering Efficiency

00:29:41 - Proving Your Impact with Numbers

00:31:00 - Professional Engineering vs. Hobby Coding

00:32:19 - "Simple is Complicated Enough"

00:35:03 - The Rise of AI Coding (The Motorcycle Analogy)

00:37:30 - "90% of My Code is Written by AI Agents"

00:41:04 - How to Become a Great Engineer

#SystemDesign #SoftwareEngineering #GitHub

What does it take to build a career as a mobile engineer when AI is changing everything?

Pasha Mazurin shares how he went from Java backend engineer to Head of Mobile, why he only joins mobile-first companies, and how AI-assisted development brought the joy back to his work. This isn't theory, it's real lessons from 15+ years in the field and now learning Android at a senior level.

In this episode, we cover:

AI-assisted mobile development workflow (the four-window tmux setup)

Why mobile-first companies operate completely differently

Hiring for strengths, not lack of weaknesses (lessons from Uber)

Leading as a hands-on engineer who stays in the trenches

Why React Native doesn't feel native and when to go fully native

Whether you're building your mobile engineering career or figuring out how AI changes your workflow, this conversation offers practical perspectives on staying effective and making intentional career choices.

Connect with Pasha:

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

TIMESTAMPS:

00:00:00 - Intro

00:01:13 - Using AI as Your Junior Engineer Teammate

00:02:33 - The Four-Window Tmux Setup for AI-Assisted Development

00:04:29 - Managing Multiple Features with Git Worktrees

00:05:52 - Why AI Makes You a Better Code Reviewer

00:08:07 - Setting Up Markdown Files for AI Context

00:11:54 - Small Teams vs Big Companies: Where Mobile Engineers Thrive

00:16:26 - The Mobile-First Company Filter That Shapes Every Career Move

00:18:31 - Being Nice: The Underrated Career Skill

00:20:29 - Pick Your Battles: When to Disagree and Commit

00:22:52 - Hire for Strengths, Not Lack of Weaknesses

00:25:16 - Is Software Engineering Still a Good Career Choice?

00:28:19 - How I Accidentally Became a Mobile Engineer

00:31:41 - Why I Only Work on Apps That Matter to People

00:35:08 - Joining Uber During the Big Mobile App Rewrite

00:39:12 - Leading Without Rank: Managing as a Hands-On Engineer

00:43:01 - How AI Changed Mobile Development in 12 Months

00:46:09 - The Communication Skills That Make or Break Engineers

00:49:59 - It's Okay to Say You Don't Understand

00:51:30 - Working on Payments: Building Critical App Infrastructure

00:53:25 - Why React Native Doesn't Feel Native (And What Works Better)

00:55:36 - Can You Switch Specializations Without Taking a Pay Cut?

00:57:02 - How Learning Android Brought the Joy Back

Worried about staying relevant as AI and new tools keep changing tech? The answer isn't chasing every new framework, it's treating your career like an engineering problem you can solve.

In this episode, we cover:

• Why staying relevant isn't about the tools (and what it's really about)
• The 3 essential career management tools: Brag Doc, Competency Framework, and Mentors
• How to get promoted when you're already doing the work
• Navigating salary negotiations and knowing when to leave
• Building a career plan that gives you permission to relax

If you're an engineer who wants to take control of your career instead of letting it happen to you, this episode gives you the frameworks and tactics to do it.

Connect with Özgen Güngör:

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

Timestamps:

00:00:00 - Intro

00:00:46 - The Biggest Challenge for Tech Careers Today

00:01:33 - How to Stay Relevant in the Age of AI

00:03:46 - The Coming Commoditization of Coding

00:05:29 - How to Move Up the Value Stream as an Engineer

00:07:35 - Your First Tech Job is a Throwaway (And That's OK)

00:09:24 - The Power of Breaking Down Your Career Plan

00:11:44 - You Work 13% of Your Life: Why Intentionality Matters

00:13:56 - I Have Too Many Career Options. What Do I Do?

00:15:34 - The "5 Whys" Exercise for Your Career

00:19:38 - How to Get Your Manager to Be Your Ally

00:22:15 - The Truth About Big Tech's Broken Promotion Process

00:24:43 - The #1 Person Who Cares About Your Career

00:28:48 - Why You MUST Keep a "Brag Doc"

00:34:08 - How to Avoid Falling Behind in Promotions

00:37:33 - What is a Competency Framework?

00:40:34 - How to Map Out Your Own Career Ladder

00:44:35 - The Silent Factor That Kills Engineering Performance

00:48:31 - Your Career Transcends Your Company

00:52:40 - The 5-Year Plan That Changed My Career

00:56:18 - 3 Essential Tools for Total Career Management

#TechCareer #SoftwareEngineering #CareerAdvice

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'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

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

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

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

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

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