Travel Tech Podcast

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

Travel Tech Podcast

Show Notes

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 Learn QA is fundamentally about translating intent into system behavior “Shift-left” eliminated QA as a team, but not as a need AI reduces the cost of writing code, not verifying it Spec-driven development is becoming a primary control mechanism Engineering is shifting from writing code to defining behavior QA thinking is rooted in empathy and adversarial reasoning AI amplifies both productivity and systemic risk simultaneously Zero-day vulnerabilities highlight unknown risks in software systems CVE management remains a high-stakes tradeoff AI adoption is reshaping incentives between productivity and burnout Security and QA are converging again under AI-driven development

Time-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

Guests Jen Reid-Schram — AI Practitioner, Former VP of Technology, Founder of Level Up Experience Jen 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-schram Company: https://www.levelup-experience.com

Oliver Deakin — Fractional CTO, Advisor and previously Technology Leader at Cirium, Former Snowflake Software CTO, and Senior Engineer at IBM Oliver 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 Podcast The 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. Host Alex Brooker — Founder, Airside Labs Alex 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 regulate

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