alphalist.CTO Podcast - For CTOs and Technical Leaders

Unfiltered insights on microservices myths, cloud cost reality, and pragmatic technical leadership Two veteran CTOs tear down today's tech hype with brutal honesty and hard-won experience. Raz Schweiger-Shuty shares his controversial approach to technical leadership at auxmoney, where he stopped a microservices rewrite and focused on business outcomes over engineering trends. From his early days as a QA engineer to running 80-person engineering organizations, Raz demonstrates why sometimes the best technical decision is the boring one that actually works. This conversation offers a masterclass in pragmatic technical leadership for an age obsessed with the latest frameworks and architectures. Key insights for technical leaders: • 🏗️ Domain-driven design as prerequisite for any architectural decision • 💰 FinOps strategies that connect engineering decisions to business metrics • 🔄 Modular monolith patterns for teams of 40+ engineers • 📊 Why velocity metrics are vanity and DORA metrics matter • 🚫 Avoiding Kubernetes complexity when elasticity isn't needed • 👥 Conway's Law applied to value stream organization • 🔧 Platform engineering pitfalls and centralization nightmares TIMESTAMPS: [00:01:00] Show premise: Two CTO Dinosaurs vs. Today's Tech Hype [00:03:56] Raz's unconventional path: QA to CTO via pragmatic learning [00:08:31] Junior vs senior engineers in the AI era [00:11:01] auxmoney: 17 years without a CTO, then Raz arrives [00:13:45] Stopping the microservices migration: building trust through disagreement [00:15:08] Language choices: PHP works, Rust creates hiring problems [00:19:35] Modular monolith strategy using domain-driven design [00:21:56] Value stream teams and Conway's Law alignment [00:22:26] Kubernetes reality check: elasticity vs complexity overhead [00:29:53] FinOps deep dive: €120k to €85k AWS cost reduction [00:32:13] Cost-per-transaction metrics for engineering accountability [00:35:00] Platform engineering centralization dangers [00:40:22] Velocity metrics are broken: focus on DORA instead [00:43:54] Meantime to recovery as team health indicator [00:48:34] Bottom-up AI adoption: Cursor rollout strategy [00:54:16] Fintech security: ISO 27001 and AI supply chain risks [00:56:59] Leadership lessons: building trust through authentic communication

Building Human-Level AI for Code: Model Factories, RL at Scale, and Distributed Teams Technical Deep Dives: Poolside’s model factory: end-to-end automation from raw data to production models Scaling RL from code execution: 800,000+ containerized repos, millions of agent tasks Immutable versioning with Apache Iceberg for full traceability Distributed team structure: 120+ engineers across US/EU, monthly in-person sprints Hardware orchestration: 10,000+ H200s, hot swap failover, dynamic allocation Leadership: dividing responsibilities, low-ego culture, and the MIT principle Future of software: managing agent workforces, context window strategies, continual learning "Our model factory runs thousands of experiments before a single production model is trained. It’s an empirical science—every component, from data ingestion to evals, is versioned and traceable." – Eiso Kant Chapters: [00:04:28] Poolside’s unique approach to foundation models [00:13:02] Scaling hardware: 10,000+ H200s and orchestration [00:17:42] RL, agents, and the future of developer tools [00:24:56] Immutable versioning and evaluation frameworks [00:36:04] Distributed team structure and monthly sprints [00:40:26] Leadership, decision-making, and low-ego culture [00:45:54] Lessons for CTOs: breaking process dogma, preparing for agent-driven orgs [00:50:54] The next 3 years: AGI, agent workforces, and the end of manual coding [00:53:44] Context window, continual learning, and model memory [00:56:20] Everything collapses into the model: product, research, and daily life [00:59:46] Advice to a younger self: scale compute, trust RL+LM, and the four-minute mile

Bridging operational technology and cloud architecture for industrial-scale systems The convergence of AI and IoT is reshaping how technical leaders approach industrial systems architecture. Bernd Groß, CEO and co-founder of Cumulocity, shares insights from building Germany's leading IoT platform—from its origins as a Nokia spin-off to becoming a critical infrastructure for companies managing tens of thousands of connected industrial assets. This conversation explores the unique engineering challenges of industrial IoT, where systems must process 50 terabytes of monthly data from wind turbines while maintaining real-time control capabilities. Bernd discusses the evolution from monolithic architectures to microservices, the complexity of supporting hundreds of industrial protocols, and the emerging "AI-IoT" paradigm. Key technical insights: • 🏗️ Speed-layer architecture design for real-time data processing with cloud data lake offloading • 📡 Managing protocol complexity through certified partner ecosystems (320+ PLC protocols) • 🔄 Microservices transformation strategies for industrial platforms on Kubernetes • 🤖 AI model deployment and operationalization across distributed industrial assets • ⚡ Edge-cloud hybrid architectures for latency-critical and regulated environments • 🛠️ Technical debt management during platform evolution and acquisition cycles Thx 2 our partner SoSafe for sponsoring this Episode. Or start a free safety simulation with SoSafe TIMESTAMPS: [00:01:04] Introduction to Bernd Groß and Cumulocity's Industrial IoT Platform [00:03:45] Early Programming: From ZX Spectrum to PC Building [00:07:07] The Nokia Rejection: Language Barriers in Early Career [00:11:51] Nokia's Innovation Incubator and Cloud Computing (2010) [00:17:24] Meeting Werner Vogels: Early AWS and Cloud Architecture [00:20:07] Spinning Off Cumulocity from Nokia Networks [00:21:21] IoT Device Management: Original Platform Vision [00:23:56] Real-Time Architecture vs. Legacy VPN Systems [00:26:33] From APIs to Applications: Learning Customer Needs [00:31:19] Software AG Acquisition: Strategic Partnership [00:34:03] Management Buyback from Silver Lake Partners [00:37:53] AI's Impact on IoT: The Emergence of "AI-IoT" [00:42:03] Speed-Layer Architecture and Data Lake Integration [00:46:46] Edge vs. Cloud: Hybrid Deployment Strategies [00:48:53] Technical Debt: Protocol Complexity and Modernization [00:52:37] Partner Ecosystem: Managing 320+ Industrial Protocols [00:56:59] Leadership Lessons: Trust and Authentic Communication QUOTES: • "When you compare that to the generation, the technology which was available before, there was really a VPN system where you needed to dial into the wind turbine… And today it's very, very different with real-time analytics happening in the background." - Bernd Groß [00:23:56] • "Our platform does data acquisition, data normalization, contextualization of the data. So you need to help structure the data because that is the foundation for your training for your AI model training." - Bernd Groß [00:42:03]

Real-time system architecture lessons from the edge of the energy transition Technical infrastructure enables the modern energy transition. Barbara Wittenberg, CTO at 1KOMMA5°, reveals the engineering challenges behind connecting and optimizing 40,000+ household energy assets while building a unified tech platform after acquiring 80+ companies across 7 countries. Tech leaders will find valuable parallels to their own challenges as Barbara discusses how her team modernized legacy systems, managed complex integrations, and deployed advanced optimization algorithms that must respond in milliseconds to prevent grid failures. Key technical insights include: 🏗️ Building infrastructure-as-code and standardizing operations across acquired companies 📊 Creating data pipelines that connect real-world physical devices to cloud optimization systems ⚡ The millisecond-level responsiveness required for grid stabilization services 🔄 Managing the product transition from siloed applications to integrated platforms 🤖 Leveraging AI to automate complex technical explanations to end users 🧠 Post-merger integration strategies that preserve valuable domain knowledge Thx 2 our partners Surfshark & SoSafe for sponsoring this Episode. Go to surfshark.com/alphalist or use code ALPHALIST at checkout to get 4 extra months of Surfshark VPN! Or start a free safety simulation with SoSafe TIMESTAMPS: [00:00:51] Introduction to Barbara Wittenberg & 1KOMMA5° [00:02:52] Barbara's Journey from Electrical Engineering to CTO [00:05:13] Early Virtual Power Plant Development at E.ON [00:07:05] The Transition from Energy to Tech and Back [00:11:02] Explaining 1KOMMA5°'s Business Model & Technology [00:13:00] The Physics of Energy Systems and Real-Time Control [00:16:41] Grid Operators and the Complex Energy Landscape [00:19:47] Smart Meters and Market Differences Across Countries [00:22:32] Battery Storage and Energy Trading Economics [00:25:35] Building Software Systems for Installation Companies [00:28:54] Tech Stack and Integration of Acquired Companies [00:33:19] Managing 2,500 Employees Across 80+ Locations [00:37:21] Data Standardization and Business Intelligence [00:42:10] Using AI to Explain Energy Decisions to Customers [00:49:22] Female Representation in Energy & Engineering [00:54:28] Closing Thoughts on Consumer Energy Solutions QUOTES: ""We send live signals in two-second intervals to 40,000 assets in the field. In Sweden, we need to respond to grid frequency changes in milliseconds - you can't send faxes, you can't even send an email. You need real-time control of your assets."" - Barbara Wittenberg [00:13:50] ""If you want to bring the best solution, you need to have all assets connected in one system."" - Barbara Wittenberg [00:12:12]

Insights into hypergrowth, late-stage career frameworks, AI adoption, and the tech powering Canva's collaborative editor. In this episode, Tobi chats with Adam Schuck, Senior Engineering Director at Canva, a company that has scaled to over 5,000 employees, 2,000+ engineers, and 230 million MAUs while remaining profitable. Adam shares his journey through startups (including acquisitions by Twitter and Canva) and large tech companies like Google, leading to his current role managing 220 engineers at Canva. They dive deep into the challenges and strategies behind Canva's hypergrowth, including: Scaling engineering teams from 150 to over 2000. Implementing a career framework (Growth & Development Framework) relatively late at 1000+ engineers, moving beyond "minimum viable structure." Canva's approach to AI: Viewing it as a tailwind, fostering experimentation ("AI Impact"), providing broad access to tools (Cursor, Copilot, LLMs), and emphasizing human responsibility ("humans as shepherds"). The core technology decisions enabling Canva's success, particularly the operational transformation logic for real-time concurrent editing and the strategic shift to a unified web-based mobile experience (WebX). Maintaining a startup culture of adaptability despite massive scale. Adam's personal productivity hacks for leaders, focusing on ruthless calendar management and clear goal setting. TIMESTAMPS: [00:00:51] Introduction to Adam Schuck & Canva's Scale [00:03:28] Adam's Personal Nerd Journey (Full Stack, Startups, Google, Twitter) [00:10:00] Canva's Business: Growth, Revenue, and Profitability [00:11:32] AI as a Tailwind: Canva's Strategy and Magic Studio [00:15:36] From PLG to Enterprise: Evolving Canva's Go-to-Market [00:17:21] Conway's Law & Org Structure at Scale (Matrix, Groups, Specialties) [00:19:45] Defining the "Paved Road": Tech Governance and Foundations Teams [00:24:23] AI Impact: Augmenting Engineers, Tooling (Cursor/Copilot), and Responsibility [00:31:29] Implementing Career Frameworks Late: The Growth & Development Framework Story [00:42:10] Tech Secrets: Concurrent Editing (Operational Transformation) Deep Dive [00:46:24] Tech Secrets: The Journey to a Unified Mobile Experience (WebX) [00:52:26] Personal Productivity Hacks for Leaders [00:57:19] Advice to Past Self QUOTES: "We recognized that maybe we were now at the point where it was actually causing more harm than good to not have these kind of frameworks and structure in place." - Adam Schuck [00:33:50] "We're really clear with our messaging to our engineering team that we don't, we're not entitling our team to abdicate themselves of responsibility. That ultimately every line of code that is shipped at Canva, it's a person responsible for that." - Adam Schuck [00:28:46]

Georg Zoeller, Co-Founder of the Centre for AI Leadership and a former Meta expert, dives deep into the reality of AI's rapid evolution. He warns against the blind adoption of AI technologies, highlighting the risks of prompt injection and the economic strains facing the industry. The conversation touches on the commoditization of software engineering driven by vast training data, and Georg emphasizes the crucial need for CTOs to invest in understanding and governance. He also discusses geopolitical risks tied to Big Tech's influence and offers actionable advice for navigating this complex landscape.

Leading in ambiguous environments and the impact of AI on engineering practices In this episode, Tobi talks with Ivan Kusalic, CTO of Enpal, who leads a team of 250 engineers at one of Germany's leading solar energy companies. Ivan shares insights from his extensive technical leadership journey and his recent return to coding after seven years due to his excitement about AI. Ivan discusses how he navigates complexity and ambiguity in the renewable energy sector, where Enpal builds systems to help households manage solar panels, batteries, EV chargers, and heat pumps as integrated energy solutions. He explains the challenges of coordinating with Germany's fragmented energy grid infrastructure and how Enpal's Virtual Power Plant stabilizes the grid by coordinating household energy consumption in real-time. Discover: 🧠 How Ivan uses intuition as a leadership tool while managing complex technical organizations 🌞 The technical challenges of building integrated renewable energy systems for households ⚡ How Enpal's Virtual Power Plant (VPP) helps stabilize the energy grid through coordinated home energy management 📱 Ivan's personal productivity system and thought management techniques 🤖 Insights on AI's impact on engineering productivity and the future of coding 🚀 Practical tips for managing complexity and making decisions in ambiguous environments TIMESTAMPS: 00:00 Introduction to Alphas Podcast 00:54 Meet Ivan Kusalic, CTO of NPAL 02:00 Ivan's Journey into Engineering and Leadership 07:05 The Role of NPAL in the Renewable Energy Sector 14:54 Navigating Ambiguity in Complex Systems 16:30 The Importance of Intuition in Leadership 23:24 Tools and Techniques for Managing Thoughts and Productivity 26:01 The Future of AI in Engineering 29:07 Experimenting with AI in Coding 29:57 Productivity Gains with AI Tools 30:40 Challenges with AI in Complex Projects 31:37 AI's Randomness and Managing It 32:24 Real-World Examples of AI Limitations 35:08 Setting Up AWS Infrastructure with AI 38:10 The Evolution of Tech Stacks 44:35 Adopting AI in Large Organizations 51:01 Reflections and Advice for Engineers 54:28 Conclusion and Contact Information QUOTE: "Intuition is an impulse to explore. It triggers the right thoughts for exploration in a moment that you would otherwise miss." - Ivan Kusalic, CTO of Enpal

In this episode, Stefan Richter, Founder and CTO of freiheit.com technologies, discusses his journey in building high-performance engineering organizations. He emphasizes the importance of a radical engineering culture and maintaining a high bar for recruitment by focusing on 'tested in life' candidates. Stefan reveals how successful project delivery relies on simplicity, disciplined processes, and full stack engineers. He also shares insights on reducing friction in workflow and creating a collaborative environment that drives innovation and continuous feedback.

Tobi and Dat discuss AI's impact on technical leadership, tools, deep learning, and Europe's innovation scene, including practical use cases for AI agents. AI is moving faster than ever, and staying ahead of the curve is a challenge for every tech leader. In this episode, Dat Tran joins Tobi to break down what’s happening in the AI space, from cutting-edge model releases to AI-powered productivity tools and the global race for AI dominance. Dat has spent years leading AI teams at Idealo and Axel Springer, co-founding AI-driven startups, and now helps companies make sense of AI without the fluff. Together, they explore the latest AI trends, the reality behind AI agents, and how engineering teams can actually get more done with AI today. 🚀 Dat’s journey in AI and tech leadership – From hacking on machine learning before it was cool to leading AI at Axel Springer and co-founding AI startups 🤖 DeepSeek R1’s impact – Why this new Chinese AI model is shaking up the industry and what makes it different from OpenAI’s GPT and Meta’s Llama 🛠️ AI agents & automation – What’s real and what’s just hype? Where do AI agents actually work in business today? 💻 The evolution of coding assistants – How AI tools like Cursor and GitHub Copilot are redefining what it means to be a full-stack engineer 🌍 The global AI race – Is Europe really falling behind? A look at China’s AI boom, US dominance, and what European AI companies need to do to compete 📈 CTO strategies for AI adoption – How to separate hype from real opportunities and where AI can have the biggest impact in engineering teams today If you’re a CTO, AI enthusiast, or just trying to keep up with the latest AI breakthroughs, this episode is packed with insights you won’t want to miss. 00:00 Introduction to Alphalist Podcast 01:02 Meet Datran: From Berlin to AI Consulting 02:01 Datran's Journey in Tech and AI 03:42 The Evolution of AI and Machine Learning 04:25 Challenges and Successes in AI Startups 06:35 The Role of Open Source in AI Development 08:12 Building a Personal Brand in Tech 11:20 Recent Developments in AI 17:33 The Future of AI and Its Impact on Jobs 37:13 Long-Term Code Management Challenges 38:07 The Evolution of Programming Languages 39:34 Boosting Engineer Productivity with LLMs 43:42 The Rise of AI Agents 46:21 Evaluating AI Agents in Business 56:24 Global Perspectives on AI Development 01:01:33 Personal Reflections and Future Outlook 01:07:48 Outro and Final Thoughts

Platform Teams and DevOps Optimization: Insights from Camille Fournier on platform engineering, career growth, and CTO strategies for success. How do you create an effective platform team and optimize DevOps? Tobi interviews Camille Fournier about her career, technical insights, and best practices in platform engineering. Camille shares her journey from building her own computers and installing Linux in high school to becoming Managing Director at JPMorgan Chase and authoring influential books for engineers 📚. 👩‍💻 Camille's early fascination with computers and engineering, including building her own systems and installing Linux 📚 Authoring 'The Manager's Path' and 'Platform Engineering' 🌐 Understanding platform engineering and its evolution from DevOps 🚀 Challenges and strategies in platform engineering for larger companies 💡 Key advice for CTOs on starting and managing successful platform teams Listen here 00:00 Welcome to the Alphalist Podcast 01:09 Introducing Camille Fournier 02:04 Camille's Journey into Engineering 04:37 The Fascination with Platform Engineering 07:43 The Evolution of DevOps and Platform Teams 14:48 Defining Platform Engineering 18:54 Building Effective Platforms in Diverse Organizations 30:35 The Importance of Trust in Platform Teams 33:33 The Role of Product Managers in Platform Products 34:12 Customer Focused Mindset in Platform Engineering 35:02 Measuring Success and Metrics in Platform Teams 35:53 Communicating Platform Success to Leadership 40:22 The Importance of Recognizing Engineering Work 44:31 Avoiding Overengineering in Platform Teams 48:19 Leadership Challenges in Platform Engineering 55:22 Advice for Aspiring Platform Engineers 59:42 Final Thoughts and Reflections