Zero-Days, Superintelligence, and the Collapse of Software Assumptions

AI is rapidly changing the economics of software: code is cheaper to generate than ever, but significantly harder to reason about, validate, and secure. As systems become more automated, the real constraint is no longer building functionality, it’s maintaining confidence in what those systems will actually do once deployed.To unpack this shift, Alex Brooker is joined by Jen Reid-Schram, an AI practitioner and former VP of Technology with deep roots in QA, engineering leadership, and executive transformation. Jen brings a systems-level view of how quality thinking evolved inside engineering teams—and why it may need to re-emerge in a new form as AI reshapes how software is produced.She’s joined by Oli Deakin, former CTO of Snowflake Software and ex-technology leader at Cirium, who brings hands-on experience building and operating complex technical systems in aviation and enterprise environments. Together, they explore how AI is redefining QA, amplifying security risk, and forcing a rethink of what “good software” even means in an era of superhuman code generation.What You’ll LearnQA is fundamentally about translating intent into system behavior“Shift-left” eliminated QA as a team, but not as a needAI reduces the cost of writing code, not verifying itSpec-driven development is becoming a primary control mechanismEngineering is shifting from writing code to defining behaviorQA thinking is rooted in empathy and adversarial reasoningAI amplifies both productivity and systemic risk simultaneouslyZero-day vulnerabilities highlight unknown risks in software systemsCVE management remains a high-stakes tradeoffAI adoption is reshaping incentives between productivity and burnoutSecurity and QA are converging again under AI-driven developmentTime-Stamped Highlights(00:11) AI focus and recent industry developments(01:38) The evolving role of QA engineers(02:19) Jen’s start in QA and early tech career(03:01) Defining the QA “quality mindset”(03:23) Shift-left development model explained(04:17) Erosion of standalone QA teams(05:57) Core traits of effective QA thinking(08:27) AI and the return of test-driven development(10:30) Spec-driven development in AI workflows(11:50) AI as a leveling force across roles(14:28) Mythos, superintelligence, and AI risk discussion(18:11) Zero-day vulnerabilities explained in context GuestsJen Reid-Schram — AI Practitioner, Former VP of Technology, Founder of Level Up ExperienceJen is a technology leader with deep experience in QA, engineering leadership, and executive transformation. She now focuses on helping organizations adopt AI through hands-on training, bridging the gap between technical capability and operational understanding.LinkedIn: https://www.linkedin.com/in/jen-reid-schramCompany: https://www.levelup-experience.comOliver Deakin — Fractional CTO, Advisor and previously Technology Leader at Cirium, Former Snowflake Software CTO, and Senior Engineer at IBMOliver has served in senior technical leadership roles, including as CTO at Snowflake Software during its rise in aviation data solutions. He has deep practical experience with software architecture, developer tooling, and emerging technologies applied to complex domains like travel and real-time data systems.LinkedIn: https://www.linkedin.com/in/olideakin/About the PodcastThe Travel Tech Podcast features long form conversations with leaders across travel and technology. The show explores how software, data, operations, and distribution come together in real businesses, with an emphasis on tradeoffs, incentives, and lessons that transfer beyond any single company or role.HostAlex Brooker — Founder, Airside LabsAlex is an engineer, technology leader, and founder with deep expertise in mission-critical systems and AI oversight. He leads Airside Labs, an AI business that applies aviation-grade testing and compliance rigor to enterprise AI systems, helping organizations build and test AI agents in regulated environments. Before founding Airside Labs, Alex built and scaled complex software in aviation and safety-critical domains, blending product innovation with disciplined engineering practices. He also invests in early-stage technology ventures and advocates for thoughtful, real-world AI deployment strategies.LinkedIn: https://www.linkedin.com/in/alex-brooker-2280002/🔍 Explore 6,500+ Aviation AI Use Cases. We've catalogued over 6,500 real AI applications across airlines, airports, ATM, MRO, and more into an interactive browser. Filter by sector and see where AI is actually being deployed across aviation: airsidelabs.com/aviation-use-casesBrought To You ByAirside Labs — Airside Labs supports aviation and travel operators with tools to test, deploy, and scale modern data and AI systems in safety-critical environments. Learn more at https://airsidelabs.com.