Building the Software Behind the Automated Lab #helicalbrew #viral #viralvideo #biology #podcast

Everyone sees the robot. But some of the hardest problems in laboratory automation live in the software nobody sees. Armon Naddaf joins Sura Hadi and Mike Ouren to talk about what it actually takes to build software around physical science — from hardware drivers, instrument APIs and testing to version control, orchestration, user interfaces and the legacy systems that still sit underneath modern labs. The conversation moves from the practical realities of debugging physical systems into a bigger question: what software architecture has to exist before laboratories can become genuinely more autonomous? Along the way, Armon explains why not everything should be automated, why standards matter, how scientists should shape the systems they use, and where AI adds value without replacing deterministic engineering. In this episode: → Why testing software gets harder when the output is a physical process → Where orchestration and LIMS become more complex than a single device driver → Why some modern integrations still depend on Windows 7 and GUI automation → Why lab workflows benefit from version control and software-engineering discipline → What scientists actually need from automation interfaces → How standardization can hide complexity without limiting scientific flexibility → Why it is not worth automating every task just because you can → Where AI genuinely helps in laboratory automation → What industrial automation can teach autonomous labs about safety → Why consistent interfaces, orchestration, traceability and governance matter before autonomy → What Armon would change about today’s vendor-dependent automation stack → Why open hardware and more competition could make lab automation more accessible 🎙️ Guest: Armon Naddaf — Software Engineer, Persist AI 👥 Hosts: Sura Hadi & Mike Ouren 📁 Series: Automation in the Wild Guest:   / armon-naddaf   Persist AI: https://www.linkedin.com/company/pers... CHAPTERS 00:00 Cold Open 00:27 Meet Armon Naddaf: Software Behind the Automated Lab 03:12 Testing Software That Controls Real Hardware 04:35 Where Lab Automation Software Gets Complicated 08:29 Instrument APIs, Windows & GUI Automation 12:10 Physical Processes, Failure Modes & Version Control 17:23 Building Automation Scientists Actually Trust 20:42 How Much Complexity Should Software Hide? 21:57 Standardization vs. Flexibility: OPC UA 23:58 What Autonomous Labs Can Actually Do Today 27:04 Where AI Adds Real Value in the Lab 28:42 Safety, Standards & the Foundations for Autonomy 33:34 Rebuilding the Lab Automation Stack 35:06 Pricing, Open Hardware & the Future of Automation 39:02 Picks of the Week 43:18 Where to Find Armon + Wrap-Up 44:57 Helical Brew Sing-A-Long 💬 What is the hardest software problem in lab automation today: instrument interfaces, orchestration, data, testing, usability, standards — or something else? 👉 YouTube:    / @helicalbrew   🎧 Spotify, Apple Podcasts & Amazon Music 📍 @helicalbrew everywhere 📩 helicalbrew@gmail.com #LabAutomation #SoftwareEngineering #LifeSciences #Automation #HelicalBrew