by Kostas, Nitay
Join Kostas and Nitay as they speak with amazingly smart people who are building the next generation of technology, from hardware to cloud compute. Tech on the Rocks is for people who are curious about the foundations of the tech industry. Recorded primarily from our offices and homes, but one day we hope to record in a bar somewhere. Cheers!
Language
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Publishing Since
8/23/2024
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July 7, 2026
<p>In this episode, we sit down with Hannes Mühleisen, co-founder and CEO of Duck Labs and co-creator of DuckDB, for a wide-ranging conversation about how a self-described outsider ended up reshaping the analytics database world.</p><p>Hannes shares how he accidentally fell into databases after moving to Amsterdam, why that outsider perspective helped him spot the “warts” everyone else had accepted, and his theory that traditional databases were “sold on the golf course” rather than built for the people who actually use them.</p><p>We dig into the origins of DuckDB: the decision to throw away a working prototype and rebuild from scratch, the untapped gap between Excel/pandas and Spark, and why in-process analytics unlocked a whole new class of users. Hannes also explains the “venture communism” reasoning behind open-sourcing a project built with Dutch tax dollars, how a single Hacker News post lit the fuse, and the philosophy of solving one real user problem at a time.</p><p>Finally, we get into the latest work — DuckLake, the Quack client-server protocol, the “never give up, never surrender” approach to queries that refuse to crash, and what changes when the entity querying your database shifts from humans to machines.</p><p><strong>Chapters</strong></p><p>00:00 Introduction to Hannes and His Journey into Databases<br>02:35 The Outsider Perspective in Database Development<br>05:12 The Evolution of Database Sales and User Experience<br>08:01 The Rise of Open Source in Database Systems<br>10:56 Building DuckDB: Challenges and Innovations<br>13:31 The Gap in OLAP Systems and the Emergence of DuckDB<br>16:05 Creating a New Market for Analytics with DuckDB<br>19:05 The Impact of Open Source and Academic Roots<br>21:57 The Philosophy Behind Open Sourcing DuckDB<br>28:02 The Value of Public Funding in Research<br>29:46 Open Source Strategy and Market Credibility<br>31:39 Launching DuckDB: Initial Reactions and Strategies<br>35:07 Learning from User Feedback and Market Needs<br>38:38 The Challenges of Database Development<br>42:34 Innovations in Client-Server Protocols<br>47:02 The Evolution of Client-Server Protocols<br>52:57 Future Aspirations for DuckDB and Community Engagement</p>
June 19, 2026
<p>In this episode, Nitay and Kostas sit down with Guillaume Binet, founder of Copper Robotics, to dig into one of the most overlooked problems in modern robotics: the software stack that runs the robots.</p><p><br></p><p>Guillaume traces his journey from tinkering with old computers in the 80s and 90s, to telecommunications, to the dot-com era, and finally into more than a decade in robotics, including roles at Trilio, Google, Motional, Argo AI, and as CTO at Skyways building long-range carbon-fiber logistics drones. Along the way, he discovered a recurring gap: while cloud software has matured into a rich ecosystem of tools and frameworks, the software powering real-world robots is still surprisingly broken.</p><p><br></p><p>That insight led him to start Copper Robotics, where he is building a new operating system and runtime designed specifically for real-time robots.</p><p><br></p><p>We talk about:</p><ul><li>Why robots are fundamentally different from cloud services and laptops, and what "real-time" actually means when sensors, perception, and actuation all have to meet a fixed time budget</li><li>The mismatch between microservice-style architectures (and ROS) and the constraints of an autonomous system that has to react in milliseconds</li><li>How Copper builds a statically described, deterministic operating system around your robot, with a scheduler tailored to the exact shape of the system</li><li>Running the same Rust codebase across heterogeneous compute, from Linux hosts to bare-metal MCUs, with a single self-contained executable</li><li>Why TCP/IP is usually the wrong answer inside a robot, and how to think about latency, bandwidth, and dropped data in a real-time context</li><li>The trade-off between compile-time and runtime flexibility, and where Copper draws the line versus ROS</li><li>Safety certification for autonomous systems (ISO 26262, aerospace, medical) and why 100% deterministic replay is a game-changer for proving that what you tested in simulation is what runs on the robot</li><li>The community forming around Copper: students, new robotics startups, and teams who have already "hit the wall" with existing tooling</li><li>A fun detour into restoring 80s and 90s computers, floppy disks, and the lost art of magnetic media</li></ul><p>If you have ever wondered why we see so many incredible robot demo videos but so few robots actually deployed in the real world, this conversation is for you.</p><p><br></p><p>Learn more about Copper Robotics and join the community via their open source project and Discord.</p>
June 5, 2026
<p>In this episode, Nitay and Kostas sit down with Sergey Arkhangelskiy, founder of Positronic, to dig into the state of physical AI and what it will really take to bring general-purpose robotics into the real world.</p><p><br></p><p>Sergey shares his journey from a decade at Google Search, where he worked on ranking and helped build the "Tetris" layer that unified web, image, and map results, to co-founding Wanna (a computer vision AR company acquired by Farfetch), and most recently launching Positronik to focus on robotics and physical AI.</p><p><br></p><p>The conversation explores why robotics is approaching but has not yet hit its "GPT-3 moment," the data and hardware bottlenecks that make physical AI fundamentally harder than LLMs, and why measurement and evaluation matter so much. Sergey walks through Positronik's newly released Physical AI Leaderboard (fail.ai), which benchmarks open-source vision-language-action (VLA) models on real hardware using production-grade metrics like throughput (units per hour) and mean time between failures, rather than simple success rates.</p><p><br></p><p>They also discuss why commercial and industrial applications (manufacturing, logistics, pick-and-place) are likely to lead before household robots, the economics of automation and the "cost of intelligence," the role of human-in-the-loop systems, latency and cloud-vs-edge tradeoffs for running VLA models, and the growing importance of open source in both robotic software (ROS) and hardware (OpenArm).</p><p><br></p><p><strong>Topics covered:</strong></p><ul><li>Sergey's path from Google Search ranking to robotics</li><li>Why physical AI is harder than LLMs: data, hardware, and the real world</li><li>The Physical AI Leaderboard and how it evaluates VLA models on real robots</li><li>Throughput and mean time between failures as production metrics</li><li>Why commercial use cases will lead household robotics</li><li>The economics of automation and the "cost of intelligence"</li><li>Human-in-the-loop and the realistic path to full automation</li><li>Cloud vs. local inference, latency, and bandwidth constraints on the factory floor</li><li>The role of open source in robotics hardware and software</li><li>What the ecosystem needs next to accelerate adoption</li></ul>
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Join Kostas and Nitay as they speak with amazingly smart people who are building the next generation of technology, from hardware to cloud compute.
Tech on the Rocks is for people who are curious about the foundations of the tech industry.
Recorded primarily from our offices and homes, but one day we hope to record in a bar somewhere.
Cheers!
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