Beyond Coding

What do coding agents need from engineers to be trusted? AI consultant Fausto Albers builds production software with agents and doesn't believe anyone still reads the code line by line. Here is what he relies on instead. We cover: Why newer models are "eating the harness", and the shift from context engineering to loop engineering The state a coding agent should be in before it runs for hours, and the gates its output has to pass Observability with open-source MLflow when you can't read every trace A shared ontology and a three-layer memory stack: a Karpathy-style Markdown wiki in Obsidian, graph memory and a local vector database in Docker Disposable vs durable software, and why software built by intent threatens traditional SaaS Why AI makes attacks cheaper than defense This episode is for software engineers and tech leads who want to give coding agents real autonomy without giving up responsibility for what gets built. Timestamps: 00:00:00 - Intro 00:00:49 - Why Newer Models Keep Eating the Harness…

What is the most future-proof engineering skill to learn now with AI and Coding agents? Time is up for traditional development cycles as Agents shrink vulnerability exploit windows from 200 days to just 18 hours. In this video, IBM HashiCorp Field CTO Anna McDougall shares why brilliant engineers have been avoiding the single most resilient career path in tech and how it's time to change that. It's now part of what software engineering is becoming: Why 20% of software engineers are grieving hands-on IDE coding (and why manual code is becoming like carpentry) The #1 future-proof engineering specialty that protects your career as AI agents write more code How to stand out in interviews using the "Pumpkin" CV strategy, high-signal personal achievements, and human networking Why non-deterministic coding agents ignore skills.md files and why 88% of breaches come down to credentials How engineering leaders can implement deterministic runtime guardrails, workload identity, and scoped credentials at scale Whether…

Meta Staff Engineer Sajal Rustagi reveals what Staff Engineers do that most don't and what the best engineers do differently to reach the top. While foundational behaviors like proactivity and ownership still separate growing engineers from stuck ones, leveling up today requires a completely new set of staff skills built around agents. In this video, we cover: The behavioral shift from IC4 and IC5 (Senior) to IC6 (Staff Engineer) at Meta How top engineers treat on-call firefighting as a system-wide ownership opportunity Why rotating between Engineering Manager (EM) and Staff IC sharpens your business and technical influence Transitioning from Developer Experience (DX) to Agent Experience (AX) using MCP, Claude, and markdown context This conversation is for software engineers, senior ICs, and tech leads who want to learn the new staff skills required to multiply their impact and get promoted now. This episode was recorded at TechLead Conference, a conference for engineering leaders on adopting AI. Timestamps:…

How do senior engineers use coding agents on prod infrastructure when “make no mistakes” is just a polite request? Kerim Satirli (HashiCorp, an IBM company) explains why prompt rules don’t hold in production, and what he runs instead. In this video, we cover: How Infrastructure as Code (Terraform, Contentful, Datadog, Okta, Cloudflare providers) evolved from open-source PRs to automated agent harnesses Why AI skills files and “make no mistakes” prompts are only requests, and what replaces them in production pipelines How AI-generated pull requests are overwhelming open-source maintainers (and why projects like cURL are pushing back) Personalized “software factories”, spec-driven development (GitHub Spec Kit), and cutting AI documentation noise with BLUF (Bottom Line Up Front) What open-source Rust clones of Adobe mean for the future of SaaS For infrastructure engineers, DevOps practitioners, and software architects who want to move past one-shot prompting and run coding agents on production infrastructure…

Lead Architect Carlos Kelkboom shares his rules for coding agents and how great engineers architect software with AI. One of the great ones is: he throws away generated code the moment he doesn't understand it. He breaks down why coding agents fail at iterative changes, why his main agent never touches files, and how he scaffolds projects for one-shot execution. In this video, we cover: Why AI coding agents struggle with iterative changes (SlopCodeBench) and excel at one-shot execution How to manually scaffold code, types, and folder boundaries before letting sub-agents run Designing a distributed Markdown and indexed-search graph harness for progressive context disclosure Using Git worktrees to run parallel coding agents and merge the best implementations Why dynamic memory and the heap need to disappear in favor of deterministic programming languages How AI bubbles and solo coding impact junior engineers and team collaboration This episode is for software engineers, tech leads, and system architects who…

What happens when coding agents see your entire system: code, services, infrastructure and live traffic, all connected? Most agents are blind to everything outside the repo. Adyen Staff Engineer Mat Jones explains what changed once theirs weren't, and why he calls it somewhat scary. In this video, we cover: Running five or six coding agents in parallel with git worktrees and Atrium, an internal tool that lets agents coordinate and share memory Architect: nine connected graphs in Neo4j covering services, code, DNS, data stores and infrastructure Ingesting 7 million trace spans a second with Kafka and Apache Flink, and what collapsed on the first try Sentinel: anti-pattern monitoring, with agents that raise the fix as a merge request MCP vs APIs vs CLI tools, and how to deal with tool bloat This episode is for software engineers and platform teams who want coding agents to reason about real systems, not just the repo in front of them. You'll leave with a concrete place to start and an honest view of the risks.…

HumanLayer CEO Dexter Horthy, who coined "context engineering", on why AI agents degrade codebases over time. He breaks down a benchmark that measures AI code quality across features, and how his team ships with agents without drowning in slop. In this video, we cover: SlopCodeBench, SWE-bench and which coding benchmarks to trust Token maxing, dark factories and the "Instagram phase" of AI engineering Why 2-4x productivity beats chasing 100x Pull requests, design docs and how engineers build taste now Dex's agentic engineering workflow: one-shots, overnight janitor bots and research-design-plan For engineers and engineering leaders adopting AI coding agents who want to know what's real and what works in teams at scale. Timestamps: 00:00:00 - The Man Who Coined the Term: Context Engineering 00:00:54 - SlopCodeBench: Proof AI Makes Codebases Worse Over Time 00:05:49 - Background Agents and the Enterprise Friction Problem 00:08:13 - Why You'll Never One-Shot a Big Feature 00:11:18 - Scaling Agentic Engineering…

Amp ships to production around 50 times a day with AI agents, but the change that makes their team ship faster isn't AI at all. Dario Hamidi, AI engineer at Amp, makes the case that pull requests are holding your team back, and explains what replaces them. In this video, we cover: Why Amp works without pull requests or feature branches, and how to try it with your own team Agent permissions, approval fatigue, and building environments where you can trust agents Orbs: remote agent execution, parallelism, and multiplayer sessions Short-lived credentials and workload identity federation for cloud agents Triaging 60+ bug reports a day with agents without frying your brain For engineers and engineering leads who want to ship faster with AI agents and are ready to question the workflows they've always used. Timestamps: 00:00:00 - Is It Time to Kill the Pull Request? 00:00:45 - What Happens If Every PR Gets Auto-Closed Tomorrow 00:05:04 - Pull Requests Were Built for Strangers, Not Teammates 00:07:20 - Does…

How do top engineers still get hired in 2026 when most applicants get ghosted, 120,000 people have been laid off this year, and hiring managers say they can't find talent? A recruiter, a hiring lead, a career coach and an open source engineer explain why your resume is dead on arrival when every CV looks the same, and what actually gets you in the room instead. In this episode, we cover: Why 120,000 tech layoffs and 60,000 open engineering roles exist at the same time Why only 20% of LinkedIn messages get a reply, and how to write the ones that do Why one hiring team bans AI tools in interviews and is building an agentic coding session instead Adaptability and resilience: the two soft skills that keep you in the room Getting hired through GitHub, referrals and open source when your CV can't stand out Whether junior engineers still have a path, and which engineering cohort is at risk in 3 to 5 years Titles vs scope: how to grow when your title never changes For software engineers, students about to graduate,…

Jordan Tigani helped create Google BigQuery, then got fired as Chief Product Officer on a Friday morning. He planned to hack on DuckDB to learn Rust. Investors offered to fund it before he'd decided to start a company. That company became MotherDuck In this episode, we cover: The DuckDB Labs partnership: why MotherDuck gave the open-source creators a co-founder share instead of going open-core From alpha to paid product: 11 founders, 3 to 4 months to alpha, two years to something people would pay for AI on top of the data warehouse: vibe-coded dashboards (Dives), pipelines (Flights), a context layer (Guides), and why business users catch mistakes analysts miss Are dashboards dead? Jordan wrote "Big Data Is Dead"; his answer on dashboards is different Career advice: why you shouldn't want to work on the query optimizer, and the skill Jordan says matters more For engineers curious about database and infrastructure companies, open-source business models, and how AI is changing who gets to ask questions of data.…

Niantic Spatial CTO Brian McClendon on how the best engineers solve problems most give up on — from a 4D model of the world to shipping research in months. He built Google Earth and ran Google Maps for over a decade, and he's been there, done that. What he's building now is harder, and it's already live for customers. Along the way: who makes it on his team and who doesn't, and the one piece of advice he'd give every engineer using AI. In this video, we cover: - The 4D model of the world: visual positioning, change detection, and treating a pile of photos like a database - Gaussian splats and real-to-sim: capturing a room and loading it into Nvidia Isaac to train robots - Turning a research idea into a production service in six months - What Google Maps taught him about building for robots instead of humans - Designing problems AI can self-check, and why token maxing is a waste For engineers and engineering leaders who want to work on problems that don't have a known answer yet — and who want to know what a…

How do new staff engineers build judgment without the years of experience that used to come with the role? Mallika Rao, engineering leader in big tech, explains why the data-structures-and-algorithms foundation everyone was trained on is no longer enough on its own, and where the complexity has actually shifted now that AI writes the implementation. In this video, we cover: Why "how does AI affect engineers" is the wrong question, and what to ask instead Rehearsing multiple futures: what judgment looks like in a staff engineer The case method: building judgment from incident reports and system design history instead of waiting years for it Cognitive coordination, code review load, and the surprise ask for more meetings at staff level Tiger teams vs scaled teams, trust as architecture, and building evals from a spreadsheet Splitting planning from execution so engineers stop falling behind with agents Taste vs judgment, and how to build both outside of software If you've just made staff, or you're about to,…

How does Amazon build its agentic AI? Michael Giannangeli, Head of Product for Amazon Nova and Agentic AI, breaks down evals, RL gyms, and model routing. He also explains why the bottleneck in software has shifted away from engineering hours and what takes its place. In this video, we cover: The eval lifecycle: building from real failure modes, saturation, and why 100% means delete RL gyms: training models on real environments like migrations, DevOps, and pen testing Model routing, cost-per-token trade-offs, and why routing isn't solved The agent stack of an Amazon product lead: Claude Code, Codex, and Kiro Autonomous migrations, trust, and how much human-in-the-loop survives For engineers and product people building with AI agents who want to see how a frontier lab actually closes its feedback loops. Recorded at the AI4 conference 2026. Timestamps: 00:00:00 - Intro 00:00:36 - The Agents an Amazon Product Lead Uses Daily 00:03:36 - Why Nobody's Heard of Amazon Nova 00:04:55 - Model Costs and the Routing…

AI is changing what developers build, but code alone is no longer enough to prove what you can do. Wes Bos explains why engineers need to solve problems beyond syntax, how agent workflows are reshaping software development, and what still requires human thinking. In this conversation: The limits of generative UI and AI-generated design Agent loops, harnesses, and cheaper AI models The rising cost of AI coding and the case for local hardware Why developer education is shifting from syntax to problem-solving Personal branding, conferences, newsletters, and AI-generated content For developers navigating AI-assisted coding, this episode explores the skills and signals that still help you stand out. This podcast was recorded at JSNation, the key web dev conference. OUTLINE 00:00:00 - Code Is Not Enough for Developers 00:00:32 - Why Generative UI Still Feels Unfinished 00:04:35 - How Agent Loops Improve AI Coding 00:07:06 - When Agent Workflows Become Standard Tools 00:08:19 - Are Cheaper AI Models Good Enough?…

Answering engineer questions on AI pressure, career growth, product thinking and impact. Including the production incident I'm glad happened, and the mindset I refuse to accept when things break. In this video, we cover: - Whether managers are really demanding more output because of AI - Balancing fundamentals with AI coding tools and agents early in your career - Specialist vs generalist and when to lean into each - Visibility, personal branding and who gets credit for your work - Product thinking, evaluating impact and what I got wrong about content being king For software engineers at any level who want honest answers on career strategy in the agent era, from someone doing both engineering and product. Timestamps: 00:00:00 - How to Spot the Next Big Thing 00:03:15 - The Saying I Hate Most 00:04:27 - The Production Mistake I'm Glad I Made 00:07:32 - Are Managers Demanding More Because of AI? 00:13:39 - Learning Fundamentals vs AI Coding Tools 00:19:00 - Will AI Ever Get Good at Distributed Systems?…

How do you prove AI is shipping more features? Amos Haviv leads the Developer Workflow teams at Booking.com, supporting 4000 engineers operating 8000 repos. Everybody is burning through their AI budget right now and almost nobody can answer what it bought them. Amos can, because his team spent four years building an event system to debug their own SDLC before AI upped the urgency. In this video, we cover: Why verification is the bottleneck right now, and where it moves next Building an event store that separates KTLO from real feature delivery Why static dashboards create the metric they measure, and the cobra story behind it Agent cost, model routing, and why Booking ignores token maxing entirely Running a developer survey with a 92% response rate across 3k+ engineers Who should own skills and MCPs: a central platform team or the domain experts? For platform engineers, engineering leaders, and anyone being asked to prove ROI on AI tooling this quarter. Timestamps: 00:00:00 - Everyone is burning through…

"I need to stop using Opus. This doesn't work." That was Heitor Lessa's conclusion after a refactor cost him 200 million tokens, and it forced him to rebuild the entire agent workflow now available for 1400 engineers. Heitor spent 11 years at AWS, built Lambda Powertools to 230 billion API calls a week, and in this episode he walks through the full SDLC workflow on screen, from discovery to merge check. In this episode, we cover: The product loop: discovery, whiteboarding, and the /roadmap command Spec-driven development with Open Spec and why vanilla setups fail Three model tiers: SOTA for planning, mid-tier for implementation, cheap models for reviews Merge checks with adversarial reviewers and attestations that catch agents fabricating test results The /retro command: using the Socratic method to make your workflow more deterministic If you're an engineer figuring out how to work with agents at team scale without losing trust in your codebase, this is the workflow to steal. This is also the first Beyond…

What senior engineers do differently has less to do with output than most career ladders suggest, and Lindsey Simon, VP of Engineering at Vercel, has watched the distinction sharpen as everyone in the valley becomes a "member of technical staff." From why new grads with hackathon years might out-prepare engineers with six years on the job, to what happens when PR throughput stops being your lever, this is a conversation about what earns seniority now. In this episode, we cover: Why engineering roles are consolidating into "member of technical staff" How to ask agents first and frame better questions to humans The scope-of-impact ladder and what the best engineers systematize Learning how to learn: closing gaps to 100% understanding Why writing is the skill that scales If you're wondering whether your years of experience still compound, or you're early-career and tired of the "woe is the juniors" narrative, this one reframes both. This podcast was recorded at TechLead Conference, a conference for engineering…

The fastest engineers are falling behind, and Kitze was one of them. He built his reputation on raw coding speed, then realized his coding wasn't competing with anyone's coding anymore, it was competing with their setups. Wake-up call for developers: Kitze now runs 140 projects solo with agent loops, and in this episode he breaks down what separates the engineers pulling ahead from the ones getting left behind. In this episode, we cover: Vibe coding vs vibe engineering, and how to get better results from your agents Police files: Self-correcting loops that end every agent turn with zero errors Why teams of 10 are collapsing into teams of 2, and who survives The rude awakening coming for engineers who refuse to adapt The number one advice to stay on track and fight FOMO For individual contributors, tech leads, and principal engineers who don't plan on falling behind This podcast was recorded at React Summit, the biggest React conference worldwide. TIMESTAMPS: 00:00:00 - Intro 00:00:40 - Vibe Coding vs Vibe…

Danila Shtan runs engineering at Nebius, one of the biggest AI clouds in the world, and he told me exactly which engineers he hires on the spot. There are only hundreds of people on the planet with the skill he wants most, and it is not the one you are grinding on. We get into which engineering skills are actually scarce and well paid today, and which ones are quietly on the way out. In this episode we cover: The engineering skills in highest demand right now and which ones are on the way out Why an AI cloud CTO restricts Claude Code inside his own company Dan's rule for merging any AI-written code into production Why working with an agent is like managing a junior engineer The interview question that surfaces top tier engineer qualities Why he still runs algorithm interviews today If you are an engineer trying to work out where the value sits now that agents write the easy code, this is a straight answer from the person building the infrastructure underneath all of it. Timestamps: 00:00:00 - AI Agents doing…

120,000 tech workers have been laid off in 2026, yet there are 60,000 open roles. Engineers applying are sending out 100 applications for zero replies. Former Reddit, Uber and Disney Plus recruiter Keki Mwaba breaks down why the market broke, why every resume now looks identical, and what gets you hired when yours looks like everyone else's. In this video, we cover: Why 120,000 layoffs and 60,000 open roles don't add up Why CVs have become too good and it's no longer enough How to treat LinkedIn as a platform Getting into companies like OpenAI and Anthropic How to reach out to people without seeming fake If you're a software engineer trying to stand out in the most competitive tech market in years, this is the playbook. Timestamps: 00:00:00 - Intro 00:00:35 - How bad is the tech job market in 2026? 00:02:38 - 120,000 laid off, 60,000 jobs open: the math is not mathing 00:04:05 - LinkedIn isn't a CV, it's a platform 00:08:30 - The underrated move: comment your way into a job 00:10:48 - Is AI ruining LinkedIn?…

Jeroen Gordijn and Jeroen Dee: two frontrunners who stopped writing code months ago and say software development is already solved. Typing code is no longer necessary, but what matters more now? If you're an engineer that loves coding, you're in a tougher spot than you might realize. In this video, we cover: - Why writing code is "solved" but engineering isn't - Spec-driven development and how to get it started in your team - The "Dark Factory" and why code review is a huge bottleneck - Model vs harness: what matters more, and why - The unhealthy side of agentic coding If you write software for a living and you're trying to work out what your job becomes next, start here. Timestamps: 00:00:00 - Coding Is No Longer Necessary 00:00:43 - Why "Software Development Is Already Solved" 00:02:57 - Should You Even Read the AI's Code? 00:05:05 - What Is a "Dark Factory"? 00:06:52 - If You Can Regenerate It, Why Care About Quality? 00:07:49 - Spec-Driven Development Explained 00:11:32 - Adopting Specs Without Starting…

AI generates 10x more code, but your senior engineers still review it by hand and it's burning them out. Even Google admits code review is now the bottleneck nobody knows how to solve. Florian Buetow, AI engineer at Xebia, has been running experiments to eliminate the human from the review loop entirely, and what he found changes where engineers should focus their effort. In this episode, we cover: Why "stop doing code reviews" is a serious answer (and what replaces them) The guardrails that gave the most value: Semgrep rules, architectural unit tests, and stop hooks Why your harness matters more than the model How Amazon and Google police AI-generated code with policies AI burnout, cognitive debt, and "cognitive surrender": what stays your responsibility Step one for adopting agentic software engineering in your team this week Whether you're an individual developer drowning in AI-generated PRs or driving AI adoption across a large engineering org, you'll leave with concrete experiments to run. More from…

Are you ready to adapt to the rapidly evolving rules of software development? In this deep dive, Logan Kilpatrick, Director and Engineer at Google DeepMind, breaks down how AI agents, advanced model-product symbiosis, and tools like Gemini 3.5 Flash are fundamentally shifting the engineering bottleneck. Learn how to maintain your competitive advantage by moving beyond the keyboard to focus on problem-solving, architectural taste, and system understanding. In this video, we cover: The changing role of the IDE and the rise of agent managers in code generation. Overcoming team bottlenecks in code review and CI/CD test execution execution loops. Why "agent coverage" and context integration are the next big tech stack metrics. Building a bulletproof software portfolio through permissionless open-source contributions. The critical difference between outsourcing intelligence versus outsourcing understanding. This episode is for software engineers, tech leads, and computer science students looking to future-proof…

As AI agents transform software engineering, how do you leverage them without losing your coding skills or risking production disasters? In this episode, Google Cloud AI Director Addy Osmani breaks down the shift from babysitting basic models to mastering advanced agent harnesses. Discover how to safely delegate complex technical tasks while maintaining your human engineering identity and setting up secure boundaries for your AI. In this episode, we cover: Human Identity vs. Machine Identity: How to avoid the trap of "cognitive surrender" and keep your critical thinking sharp. Stopping the AI "Babysitting" Cycle: How to transition from constant manual oversight to secure agent governance. Rising Abstractions: Why agent harnesses (like Claude Code and Antigravity) are changing how software is built. The Verification Bottleneck: Why coding is easy, but verifying that your agent didn't ruin production is the real challenge. This episode is a must-watch for software engineers and tech leaders looking to…

After 250 episodes of Beyond Coding, a pattern shows up again and again: the engineers who thrive aren't the ones chasing the newest tool or the cleanest code. They're the ones who learn fast, keep things simple, and understand the business they're building for. This special pulls the sharpest moments from recent guests into one conversation about what actually makes a great software engineer in 2026. We cover: Why learning is the only skill that outlives every tool, language, and platform How the best architects act more like scouts than cartographers Why "simple is complicated enough" beats clean code dogma at scale How to design systems that evolve instead of trying to predict 10 years out What junior engineers should actually do in the age of AI agents For software engineers who want to think clearer, build better, and grow into the kind of engineer companies can't replace. Timestamps: 00:00:00 - Intro 00:00:17 - Why You Should Increase Your Breadth, Not Just Focus 00:02:16 - The Only Skill That Survives…

Reddit Reacts is back. I'm taking the most controversial takes on software engineering from Reddit and giving you my unfiltered perspective on what's happening, from juniors leveraging AI tools, to the culling of engineers who refuse to adapt, to whether you should take a gap year after a layoff. In this episode, we cover: How to become technically "cracked" and what really separates great engineers Why juniors learning with AI have an edge over 20-year veterans The future of writing code by hand (and why fulfillment is shifting) Vibe coding, security holes, and what happens after 6 months The brutal reality of layoffs, gap years, and AI-driven hiring If you're an engineer trying to figure out where this industry is going and how to stay competitive, this one is for you. Mentioned in the episode:⁠ADP List⁠ - free mentorship from senior engineers Timestamps: 00:00:00 - Intro 00:00:54 - How to Become Technically Cracked in 2026 00:05:35 - Will Juniors Who Only Code with AI Get Stuck? 00:09:26 - Will Senior…

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:…

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…

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…

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…

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…

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…

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…

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 -…

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?…

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…

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…

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…

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…

The software engineering landscape is shifting rapidly. Coding is becoming "cheap" because of tools like Claude Code, Codex, Gemini, Cursor etc. Interviews are evolving to focus on system design over syntax. In this Q&A, I break down exactly which skills matter now, how to negotiate the salary you deserve, and how to deal with difficult personalities on your team. In this episode: How juniors can leverage AI tools to reach senior-level output Real-world salary negotiation tactics from my experience Why coding skills matter less in modern interviews (and what matters more) Handling "brilliant jerks" and toxic team culture Whether you are looking for your first job with no experience or you are a mid-level dev trying to break into a Staff Engineer role, this session is packed with actionable career advice. Timestamps: 00:00:00 - Intro 00:01:06 - Handling Brilliant Jerks: Toxic Culture vs. High Performance 00:04:13 - How Juniors Can Use AI to Outperform Seniors 00:07:10 - The Future of Coding Interviews: System…

"Architects shouldn't try to be the smartest people in the room, they should make everybody else smarter." In this episode, Gregor Hohpe (ex-Google & AWS, author of "The Software Architect Elevator") breaks down exactly how to transition from software engineer to architect. He shares the mental models used at Big Tech to handle complexity, visualize systems, and navigate office politics without losing your technical edge. We cover: - Why "lowering risk" is the architect's real value proposition - The "Phantom Sketch Artist" technique to visualize unclear requirements - How to gain "political capital" to push back on bad decisions - Why simple architectures are often the hardest to build If you want to move beyond just writing code and start designing systems that scale, this conversation is for you. Connect with Gregor: https://www.linkedin.com/in/ghohpe 00:00:00 - Intro 00:01:15 - How to Spot Bad Architects vs. Great Amplifiers 00:03:44 - Why Architects Are Actually Risk Managers in Disguise 00:06:13 - The…

Are you waiting for a promotion that never comes? In this episode, we break down why relying on your manager to define your growth is a career-limiting mistake and how you can take full ownership of your professional path. In this episode, we cover: Why hard skills get you hired but won't get you ahead How to create growth opportunities when your company has no clear path Using RACI to own decisions and increase your visibility Connect with Zanina: https://www.linkedin.com/in/zaninakatira References: RACI - https://en.wikipedia.org/wiki/Responsibility_assignment_matrix Timestamps: 00:00:00 - Intro 00:00:51 - Why hard skills get you hired but soft skills make you thrive 00:04:17 - How to connect your code to actual business results 00:06:44 - The art of storytelling for technical professionals 00:09:16 - Balancing execution speed with team collaboration 00:11:57 - The problem with forcing engineers into management roles 00:15:13 - Surviving when technology outgrows your current skillset 00:17:59 - Using the…

Software engineers often think adding AI is just a simple API call, but moving from a Proof of Concept to a stable production system requires a completely different mindset. Maria Vechtomova breaks down the harsh reality of MLOps, why rigorous evaluation is non-negotiable, and why autonomous agents are riskier than you think. In this episode, we cover: The essential MLOps principles every software engineer must learn How to bridge the gap between a demo and a production-grade solution Strategies for evaluating agents and detecting model drift The security risks of customer service agents and prompt injection Practical tips for using AI tools to boost your own productivity Connect with Maria: https://www.linkedin.com/in/maria-vechtomova Timestamps: 00:00:00 - Intro 00:01:25 - Why the AI Hype Was Actually Good for Monitoring 00:03:07 - Real-World AI Use Cases That Deliver Actual Value 00:05:16 - MLOps Basics Every Software Engineer Needs to Know 00:08:08 - The Hidden Complexity of Deploying Agents to…

Are your technical skills actually holding your career back? In this conversation with Anand Sahay, Global CEO of Xebia, we explore the controversial reality that "mediocre" engineers often climb the corporate ladder faster than technical wizards. And what you need to do to change that trajectory. In this episode, we cover: Why simplicity and business value beat complex code every time The specific mindset shift required to move from Senior Engineer to Executive How to maintain technical intuition and manage risk without micromanaging The hidden arrogance that stops great engineers from becoming great leaders This discussion is essential for software engineers, architects, and technical managers who want to break through the "tech ceiling" and understand how decisions are really made at the top. Connect with Anand: https://www.linkedin.com/in/ansahay Timestamps: 00:00:00 - Intro 00:01:28 - How to Pitch to Executives (And Not Get Rejected) 00:03:42 - The #1 Trait of Elite Engineering Leaders 00:06:15 - Why AI…

Tools change and frameworks die, but your career doesn't have to. Marijn Markus joins the show to explain why "Don't be a fool with a tool" is the single most important piece of advice for modern software engineers and data professionals. In this episode, we cover: The "Meta-Skill" of learning how to learn new technologies Why real innovation often originates in "dark" industries like crime and warfare How to future-proof your career against AI agents and automation Why understanding the business problem is more valuable than writing the code This conversation is essential for engineers who want to move from memorizing syntax to mastering the skills that actually last. Connect with Marijn Markus: https://www.linkedin.com/in/marijnmarkus Timestamps: 00:00:00 - Intro 00:01:01 - Realizing That Data Science Can Actually Save Lives 00:04:36 - Predicting Refugee Movements With Hamburger Prices 00:07:05 - Why You Should Try Different Roles Early in Your Career 00:12:37 - Learning in Banking to Eventually Help…

Are you just executing tickets, or are you driving business impact? In this episode, Praveen Murugesan (VP of Engineering at Samsara) breaks down why the best engineers don't just write code and why "coding skills" alone won't get you there. He explains the critical shift from "software engineer" to "product engineer," why you shouldn't wait for permission to solve problems, and how to de-risk high-stakes projects like a true owner. In this episode, we cover: The difference between a "Ticket Taker" and a Product Engineer Why Product Managers should NOT be doing project management How to grow to Staff Engineer without managing a large team The exact interview questions to ask to test a company’s culture A real story of an engineer telling a VP: "That's not an important problem" Connect with Praveen Murugesan: https://www.linkedin.com/in/praveenmurugesan Timestamps: 00:00:00 - Intro 00:01:55 - Product Engineer vs. Software Engineer: What’s the Difference? 00:06:20 - Why Product Managers Should Not Do Project…

Traditional software engineering job listings have dropped by 70%, yet Forward Deployed Engineer (FDE) roles have exploded by over 800% this year. We sit down with Mo Fagir, Principal Technical Consultant at ServiceNow, to break down exactly why this shift is happening and how you can pivot your career to ride this AI adoption wave. In this episode, we cover: The massive market shift: Why "pure coding" jobs are declining while FDEs are booming. The exact technical stack and soft skills required to land these high-paying roles. How to overcome imposter syndrome and build a portfolio that gets you hired, even as a junior. Why this isn't just a trend, but the future of how engineering delivers value. Connect with Mo Fagir: https://www.linkedin.com/in/mo-nour-tarig Timestamps: 00:00:00 - Intro 00:01:14 - Why software jobs dropped 70% while FDEs grew over 800% 00:02:55 - Why companies can't implement AI without Forward Deployed Engineers 00:05:36 - Is this career path safe for traditional software engineers?…

If you think your value as a software engineer comes just from writing code, you're already at risk. In this episode, Outsystems CEO Woodson Martin reveals why AI isn't the real threat to your career. Irrelevance is. He explains that writing code is now only 20% of the job, and the engineers who thrive are the ones who master the other "80% that matters." We cover: The billions of lines of ungoverned code AI is creating Why the "Forward Deployed Engineer" model is changing team structures The 80% of engineering work that AI cannot replace How to shift from coder to problem solver who drives business revenue A CEO's advice for building a lasting engineering career This is a reality check for developers, tech leads, and architects who want to stay relevant as agentic AI reshapes the industry. Connect with Woodson: https://www.linkedin.com/in/woodsonmartin Timestamps: 00:00:00 - Intro 00:00:56 - How Agentic AI keeps the human in the loop 00:01:55 - Real-world example: Automating the grunt work 00:04:17 - How…

What if you could build a multi-million dollar software company where only 10% of your employees are developers? AFAS, a company with hundreds of millions in revenue, does exactly that with a lean team of just 70 engineers. In this episode, Engineering Manager Michiel Overeem pulls back the curtain on their unconventional strategies for achieving massive productivity with a surprisingly small team. In this episode, we cover: Why standardization is their secret weapon for efficiency. How they thrive without traditional Scrum ceremonies. The two distinct types of engineers they hire for success. The surprising details of their 4-day work week (paid for 5). This video is for engineering leaders and software developers who want to learn proven, counter-intuitive strategies to build hyper-effective teams and get more done, regardless of team size. Connect with Michiel: https://www.linkedin.com/in/movereem Timestamps: 00:00:00 - Intro 00:01:22 - The "10% Engineering" Paradox at a €100M+ Company 00:03:20 - How…