Beyond Coding

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 outThis 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/CODING20Timestamps:00:00:00 - Intro00:00:19 - Holding Peers Accountable When Managers Won't Help00:03:58 - The Surprising Truth About Code "Quality"00:05:43 - Scaling Accountability Across Large Teams00:07:50 - When Climbing the Career Ladder Feels Political00:12:37 - How to Stay Relevant in Tech Without Burning Out00:14:49 - The Key to Learning Without Feeling Overwhelmed00:15:18 - The Real Difference for Engineers Working Globally00:17:44 - What to Do When You Get a Better Job Offer00:20:51 - Finding Motivation Beyond a Higher Salary00:21:41 - How to Build Real Credibility and Authority00:25:31 - The Advice I'd Give My Junior Developer Self00:29:05 - The Art of Effective Delegation00:31:47 - Why Delegation Is Really an Act of Trust00:32:21 - Team Player vs. Individual Star: A False Choice?00:34:43 - The #1 Personal Development Skill for Engineers00:37:11 - The Hidden Dangers of Relying on AI Tools00:40:08 - Is Volunteering at Tech Conferences Worth It?00:42:50 - My Personal Struggle with Embracing Change00:45:32 - The Career "Regret" I Don't Actually Regret00:46:45 - How to Stay Productive While Dealing with Grief00:49:08 - My Process for Finding Great Podcast Guests00:50:48 - The Secret to Making Guests Feel Comfortable00:52:06 - How Podcasting Transformed My Communication Skills00:53:35 - Handling Guarded or Difficult Podcast Guests00:56:11 - Final Thoughts & How to Support the ChannelGot questions for the next Q&A? Drop them in the comments 👇#SoftwareEngineering #CareerGrowth #TechLeadership

Sander Mak, Director of Technology at Picnic and creator of the Tech Academy, shares secrets to elevating one’s engineering career. He emphasizes the importance of understanding core principles over just coding skills. Sander explores the value of 'boring' technology, the pitfalls of copying without comprehension, and the shift from coder to product-focused engineer. He also discusses training strategies, fostering developer happiness, and integrating soft skills with technical growth to prepare engineers for real-world challenges.

In this session, Kate Ivanova, a seasoned Product Manager with a strong background in AI product development, discusses the evolving landscape of tech teams. She highlights how AI is merging the roles of product and engineering, enabling smaller teams to drive significant impact. Kate emphasizes the need for adaptability and an experimentation mindset for AI workflows. She also shares insights on ideal team structures, the importance of engineers understanding business, and ways to boost developer happiness and ownership. Tune in for a fresh take on modern tech collaboration!

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 Builder00:02:42 - How AI Helps You Build an MVP in One Day00:06:26 - Why This Engineer is a Hackathon "Living Legend"00:07:41 - From Hackathon Idea to Real AI Product00:11:42 - The Secret to Winning: Treat it Like a Startup00:17:22 - How Booking.com Onboards Juniors with a 4-Week Hackathon00:20:25 - Why We Still Need Junior Engineers in the Age of AI00:26:57 - The #1 Struggle Teams Face in Hackathons00:31:04 - The Real Reason to Join a Hackathon (It’s Not the Prize)00:35:46 - How to Start and Finish Your Personal Projects00:40:12 - 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 - Intro00:00:45 - Why Maarten Started a Dutch AI Hub00:02:15 - The "Flywheel" Effect Crucial for AI Success00:04:42 - The Hard Truth: Why the Netherlands is Lagging in AI00:07:52 - A Controversial Take: The EU AI Act is Actually Good for Everyone00:11:26 - The Real Bottleneck to Innovation Isn't Regulation00:14:25 - From POC to Production: Why Top-Down Vision is Non-Negotiable00:17:13 - A Wake-Up Call for Inexperienced Leadership Teams00:20:30 - How Winning Companies Use AI to Dominate Their Market00:23:44 - The Right Way to Learn From Your Competitors00:27:30 - Maarten Outsourced Core Development to an AI Company00:31:59 - The #1 Metric You Must Track for AI Observability00:36:03 - Open-Source vs. Closed-Source: Which AI Model Will Win?00:40:23 - The Inevitable Crisis That Will Force Innovation00:42:19 - 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 TechnologiesGuests 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 fakesThis 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/paryalotfiTimestamps:00:00:00 - Intro00:00:35 - The Scary Reality of AI-Generated Videos00:02:32 - The Dangerous Side of Facial & Voice Biometrics00:03:45 - The Disturbing Reality of Voice Cloning Scams00:06:46 - How to Use AI to Catch AI-Generated Fakes00:10:11 - Solving AI's "Black Box" Problem with Explainability00:12:10 - The Different Types of Deepfakes Criminals Use00:14:15 - How Deepfakes Are Used to Launder Millions From Banks00:18:18 - Inside the Darknet's "Deepfake-as-a-Service" Business00:22:32 - Why Banning Deepfake Technology Is Impossible00:24:58 - How Deepfakes Are Being Weaponized in Global Conflicts00:27:30 - Red Teaming: How to Think Like a Deepfake Criminal00:29:09 - The North Korean Spy Who Used a Deepfake to Get a Job00:31:54 - The Ultimate Goal: A Deepfake Detector for Everyone00:37:23 - The Future That Scares Me: AGI and Self-Aware Robots00:44:33 - The Journey of Building a Deepfake Detection Company00:47:42 - The Surprising Reason Deepfake Detection Is So Hard00:54:44 - 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

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 Features00:00:49 - The #1 Thing That Changed for Product Managers01:28 - From Pixels to Tokens: The AI Product Shift02:58 - Why AI Is All About Output Quality, Not UX04:46 - When Is an AI Feature "Good Enough" to Ship?06:45 - The "Non-Embarrassment Bar" for Releasing AI09:07 - Why Old User Feedback Methods Don't Work for AI12:28 - The New Expectations for Software Engineers in AI15:33 - When to Involve Engineers in the Product Process17:43 - How Microsoft Structures Its AI Product Teams20:40 - Why 3-Month Planning Is Obsolete in the AI Era22:42 - How to Remove Bias From Your Product Decisions25:36 - Balancing Data vs. User Intuition in AI27:44 - The Biggest Bottleneck in AI Experimentation31:12 - How to Define the Right Metrics for Your AI Product33:39 - Building Trust and Culture in a Remote Team37:47 - The Most Underrated Skill for Product Managers40:57 - How to Cultivate a Strong Product Culture44:32 - The AI Tools a Microsoft PM Actually Uses46:29 - How to Manage the Expanding Scope of the PM RoleConnect with Stéphanie Visser:https://www.linkedin.com/in/stephanievisserConnect with Patrick Akil:https://www.linkedin.com/in/patrick-akilhttps://twitter.com/PatrickAkil_Sponsors:Xebia - https://xebia.com#ProductManagement #AI #Microsoft

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-shahkaramiFull episode on YouTube ▶️https://youtu.be/Jui-8Lx6kvkBeyond Coding Podcast with ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠🎙Patrick Akil⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Powered by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Xebia⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠!Timestamps:0:00:00 - Why Now Is The Best Time to Hire Junior Talent00:01:46 - The Massive Mistake Companies Make with AI Hiring00:03:11 - How Junior Talent Can Stand Out in 202500:04:39 - Why Senior-Only Teams Can Become Negative00:05:56 - The ROI Problem: What If Your Junior Talent Leaves?00:07:44 - How Companies Can Actually Retain Top Talent00:11:06 - How AI Has Changed Personal Productivity for Leaders00:15:34 - How the Role of a Data Scientist Is Evolving00:18:28 - The 80/20 Rule of Building AI Products00:21:37 - The Rise of the "AI Engineer" and What It Means00:23:37 - A Simple Strategy for Personal Growth in Tech00:28:46 - Where Generative AI Delivers Real Business Value00:32:37 - Why You Must Differentiate Your Business With AI Now00:38:09 - A 2-Fold Strategy for Prioritizing AI Projects00:40:41 - The Power of a 20% Experimentation Culture00:43:10 - The Problem With Chatbots as a First AI Project00:46:20 - The Danger of Releasing an 80% Good AI Product#AI #TechCareers #DataScience

Joris Kuipers, CTO at Trifork with 25 years of experience, shares insightful perspectives on mastering software engineering. He discusses the importance of continuous learning amidst rapid technological changes and how junior developers should identify key skills to excel. Joris emphasizes that frequent deployments are often safer than slow releases and highlights the necessity of feedback loops for career growth. He also addresses the balance between independence and collaboration, advocating for environments that foster motivation and growth.