Travel Tech Podcast

Airside Labs

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

  1. 5D AGO

    Fix the Data First: A Contrarian's Guide to AI in Hospitality

    Hotels are sitting on millions in uncollected revenue and corrupted content and most of them don't even know it. Fred Bean is the founder of HotelPORT, a hospitality content governance and distribution technology company he launched in 2019 after three decades working across hotel reservations, GDS connectivity, and online distribution. His career spans roles at Hyatt, Sabre, and TravelWeb, where he helped build foundational infrastructure for hotel bookings online.  This conversation covers the persistent structural problems in hotel distribution from inaccurate third-party content and uncollected OTA payments to the misapplication of AI and how governed data is the prerequisite for every meaningful technology deployment in hospitality. What You'll Learn Variable Net Rates: The mechanism that allowed hotels to revenue-manage against net rates after 9/11 — locking in OTA margins while letting room rates float with demand — was pioneered at TravelWeb in 2002 and became an industry standard adopted by every major distribution player.Content Governance: Inaccurate hotel content on third-party channels is not an edge case — it is the norm, affecting even hotels with active distribution connectivity, and the downstream impact on bookings and guest experience is systematically underestimated.Revenue Leakage: An audit across 2,000 hotels found $7 million in uncollected OTA virtual credit card payments, with over $500,000 already expired — a direct result of resource constraints at property level, not negligence.AI Prerequisite: AI deployed on top of ungoverned data will hallucinate and erode guest trust; the correct sequence is governance first, activation second — verify the source of truth before connecting any AI-facing interface.Distribution Expertise Decline: Institutional knowledge of how hotel distribution systems interconnect is eroding as experienced practitioners retire without adequate replacements, creating an industry-wide vulnerability that neither software nor AI can currently compensate for.Channel Misalignment: Digital marketing and distribution teams within hotels frequently operate without visibility into each other's decisions — resulting in spend on paid search during periods of zero availability, a problem that requires internal alignment before technology can solve it.Generational Engagement Shift: Voice, text, and chat AI are not competing formats — they serve different traveler cohorts simultaneously, and hospitality operators need human off-ramps in AI voice flows and multi-channel support to avoid alienating any segment.OTA Consolidation Risk: The consolidation of major OTAs into a few parent companies has created an illusion of channel choice for consumers, reducing competitive pressure on incumbents and opening genuine opportunity for startups that solve problems the big platforms have deprioritized. Time-Stamped Highlights (00:00) Introduction — Why a Call Center in Omaha Started a 30-Year Career(01:10) From Reservation Agent to Distribution Architect at Hyatt and Sabre(02:58) Building the First Internet-Bookable Hotel Reservations in the Late 1990s(08:10) Inventing Variable Net Rates: How Hotels Took Back Margin from OTAs Post-9/11(11:25) Data at Scale: Why More Channels Has Made Content Accuracy Worse, Not Better(15:00) The Long Tail Problem: How Smaller Hotels Get Overwhelmed and Where They Fall Short(20:35) AI Skepticism Grounded in Experience: Dot-Com Parallels and the Pets.com Generation(30:11) Governance Before Activation: The Two-Step Framework for Responsible AI Deployment in Hotels(36:12) PropertyView and the $7 Million Discovery: Auditing Revenue Leakage Across 2,000 Hotels(42:20) Engage: Voice, Text, and Chat AI Powered by Verified Hospitality Data(45:30) Generational Divergence in Guest Communication: Designing for All Three Cohorts(50:00) OTA Consolidation, Fake Hotel Websites, and the Fraud Problem AI Is Making Worse(55:00) Where Startups Can Still Win: Packaging, Event Travel, and Value-Based Selling(58:30) The BIG Foundation: Teaching Food-Insecure Youth to Cook as a Pathway into Hospitality Guest BioFred Bean is the Founder and CEO of HotelPORT, a hospitality content governance platform he launched in 2019 after 30 years working in hotel reservations, GDS connectivity, and distribution technology at companies including Hyatt, Sabre, and TravelWeb, where he co-developed the variable net rate model adopted across the industry. He also founded the BIG Foundation, a Miami-based initiative addressing food insecurity among hospitality-industry families by giving students culinary skills and a pathway into the workforce. LinkedIn: https://www.linkedin.com/in/fredbean/   |   Company: hotelport.com  |   Foundation: https://bigfoundation.net/ 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 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-cases Brought To You By Airside 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.

    59 min
  2. APR 28

    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 Learn QA 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 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-schramCompany: https://www.levelup-experience.com Oliver 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 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 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-cases Brought To You By Airside 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.

    31 min
  3. APR 21

    The 5-Minute Build That Breaks Traditional Travel Tech

    For decades, building a travel business meant stitching together fragmented supply: GDS systems, hotel APIs, pricing layers, and fulfillment infrastructure. It was complex, expensive, and slow to scale. Now, that’s changing fast. With the rise of AI agents and MCP-powered infrastructure, what once took years of engineering can now be deployed in minutes—fundamentally shifting who can participate in the travel ecosystem, and how distribution works. Mike Putman, CEO and Founder of Custom Travel Solutions, has been at the center of this evolution—from launching one of the earliest online travel agencies in the mid-90s to building the infrastructure powering modern AI-driven booking systems. This episode explores how travel distribution is being rebuilt, why agents—not brands—may control the customer relationship, and what it means when any company can become a travel seller overnight. What You’ll Learn Building a travel booking engine has gone from multi-year projects to minutes with AI agentsThe real complexity in travel isn’t search—it’s data normalization, deduplication, and pricing logicAgentic AI shifts power away from brands toward personalized user-controlled experiencesLoyalty programs may weaken as agents optimize for outcomes, not brand preferenceThe “last mile” problems—like booking failures at hotels—still cost the industry ~2% of transactionsAI can now solve operational gaps (like reconfirmation) that were previously too expensive to fix with humansTravel distribution is becoming infrastructure-first, where aggregation layers power entire ecosystemsIn the future, agents may transact directly with other agents, reshaping how commerce worksTime-Stamped Highlights (01:03) Early Days of Online Travel (01:55) Evolution of Travel Technology (03:11) Launch of 11th Hour Vacations (04:10) Gaining First Customers (06:03) Pre-Google Search Engines (07:02) Partnership with Lastminute.com (09:18) Amadeus Acquisition and OneTravel (10:19) How Custom Travel Solutions Works (14:34) Lessons from Previous Ventures (16:20) Scaling Challenges (18:23) AI in Travel Industry (32:39) Future of Agentic AI in Travel Guest Mike Putman — CEO & Founder, Custom Travel SolutionsMike Putman is a travel industry veteran with over four decades of experience across distribution and technology. He founded one of the earliest online travel agencies in the 1990s and has since worked with major global travel brands. Today, he leads Custom Travel Solutions, building infrastructure that powers modern travel booking, including AI-driven aggregation, agentic APIs, and back-office automation tools. LinkedIn: https://www.linkedin.com/in/mikeputman/Company: https://customtravelsolutions.comRoutestack: Routestack.ai 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 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-cases Brought To You By Airside 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.

    35 min
  4. APR 13

    What’s Actually Stopping Air Taxis From Taking Off

    The US is about to publish rules that let drones fly beyond line of sight routinely — here's what that unlocks. Part 108, the FAA's upcoming rulemaking for beyond visual line of sight (BVLOS) operations, is set to change the economics of commercial drone flight. For the first time, operators will have a clear regulatory path to fly without visual observers — making routine, scalable drone operations commercially viable. Kraettli L. Epperson, Co-Founder and CEO of Vigilant Aerospace, has spent years building the detect-and-avoid systems that make this possible. His focus isn't the drone itself — it's the invisible layer of data, sensors, and safety logic that allows autonomous aircraft to share airspace without introducing unacceptable collision risk. This episode unpacks what Part 108 actually enables, why detect-and-avoid is the gating technology, and what still needs to happen before drones — and eventually air taxis — can operate at scale. What You’ll Learn Detect-and-avoid is the gating factor for scale: Autonomous flight is limited not by hardware, but by the ability to safely manage shared airspace.BVLOS is where real commercial value begins: Moving beyond visual line of sight unlocks scalable use cases, but requires regulatory approval and robust safety systems.Airspace awareness depends on data fusion: Combining multiple data sources—transponders, radar, telemetry—is essential to build a reliable picture of the sky.Non-cooperative aircraft create real risk: Not every aircraft broadcasts its position, requiring fallback systems like radar and acoustic detection.Regulation defines what’s commercially viable: FAA frameworks like Part 107 and upcoming Part 108 directly shape what operators can and cannot do.Routine operations require predictability: Businesses invest when operations become repeatable, not just technically possible.Autonomy is an infrastructure problem: The future of aviation depends on invisible systems coordinating decisions in real time, not just smarter vehicles.Time-Stamped Highlights (03:02) Why Detect-and-Avoid Became the Industry Bottleneck(07:09) From NASA Research to Commercial Safety Systems(09:07) Why Collision Avoidance Is Technically Complex(12:05) Beyond Visual Line of Sight as the Key Unlock(17:09) The Gradual Shift Toward Autonomous Operations(18:59) Real Constraints on Range, Altitude, and Scale(20:21) What Changes When Flying Becomes Routine(24:05) The Challenge of Non-Cooperative Aircraft(28:06) Managing Tradeoffs Between Different Airspace Users(31:08) Where Radar Fits in Drone Safety Systems(39:34) How Air Taxis Fit Into the Same Safety Framework(42:45) What a Fully Integrated Airspace Could Look Like by 2035Guest Kraettli L. Epperson — Co-Founder and CEO, Vigilant AerospaceKraettli L. Epperson is the Co-Founder and CEO of Vigilant Aerospace, a company focused on detect-and-avoid and airspace management systems for drones and advanced air mobility. With a background in software, data systems, and entrepreneurship, he works at the intersection of aviation safety, autonomy, and regulation—helping enable scalable, routine drone operations.LinkedIn: https://www.linkedin.com/in/klepperson/ Company: https://www.linkedin.com/company/vigilantaero/ 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 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-cases Brought To You By Airside 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.

    48 min
  5. APR 6

    The Real Reason One Broken Machine Disrupts an Entire Airport

    Queues move, bags get scanned, and passengers eventually make it through. But beneath that surface is a fragile operational layer held together by fragmented systems, manual workarounds, and frontline teams stitching together processes in real time. Anne Marie Pellerin has seen both sides of that system—designing queue segmentation at TSA that improved throughput, and later discovering that when security systems fail, the response is often disconnected, slow, and opaque. This conversation goes beyond passenger experience into something more fundamental: how airports actually recover when critical systems break—and why solving that requires rethinking how data, workflows, and people are connected on the ground. What You’ll Learn Segmenting passengers reduces stress and improves throughput: Separating travelers by experience level can increase efficiency by lowering stress-induced errors at checkpointsAirport operations still rely on fragmented workflows: Many frontline teams use disconnected systems, emails, and even pen-and-paper to manage critical equipmentDowntime creates cascading operational risk: A single equipment failure can lead to long queues, baggage disruptions, or even flight delaysThe real problem is coordination, not detection: Technology for identifying threats has advanced rapidly, but operational orchestration has lagged behindOrchestration layers unlock system-wide visibility: Connecting frontline staff, maintenance teams, and vendors creates shared context and faster resolutionFrontline workers are the missing link in system design: Most tools are not built for the people actually operating equipment day-to-dayAI depends on unified data, not just models: Without a consolidated dataset across systems, predictive analytics and automation remain limitedAutomated escalation can replace manual processes: AI-driven workflows can route issues directly to the right technician with full context, even via voice callsGovernment and regulated sales cycles require long-term thinking: Success in aviation tech depends on patience, trust, and multi-year relationshipsSecurity operations extend beyond airports: The same operational challenges exist in borders, cruise terminals, data centers, and critical infrastructureTime-Stamped Highlights (00:10) Airport Queues as a Design Problem(02:09) TSA’s Checkpoint of the Future Program(03:13) Passenger Segmentation and the Origins of PreCheck(05:01) U.S. vs. European Airport Security Models(07:03) The Hidden Complexity of Security Equipment Management(09:12) How Equipment Failures Disrupt Airport Operations(10:10) Why Airport Systems Remain Fragmented(11:04) Building an Orchestration Layer for Security Operations(13:01) Toward a Unified Operational Control System(14:17) From Government to Startup: Shifting Perspectives(18:41) Navigating Long Sales Cycles in Aviation(22:26) Expanding Beyond Airports Into Other Industries(24:04) What Actually Happens When Equipment Fails(26:40) AI in Security Operations and Failure Detection(29:26) Automated Calls and Real-Time Escalation With AIGuest AnneMarie Pellerin — CEO & Co-Founder, Curie Technologies; Managing Partner & Founder, LAM LHA Anne Marie Pellerin is a former TSA leader who served as Director of Checkpoint of the Future and spent six years as the agency’s representative in Europe. She worked on programs that informed modern checkpoint design and passenger flow, including concepts that influenced TSA PreCheck. She is now co-founder of Curie Technologies, a platform focused on improving operational coordination and uptime for security equipment.LinkedIn: https://www.linkedin.com/in/anne-marie-pellerin-1007038/ Company: https://www.linkedin.com/company/curie-technologies/ 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 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-cases Brought To You By Airside 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.

    35 min
  6. MAR 31

    Why AI Is Slowing Down Experts Before It Speeds Up Work (Brooker, Painter, Deakin, McKenzie)

    AI adoption inside teams is not following the narrative most people expect. In some cases, the most experienced engineers—the ones expected to benefit the most—are actually getting slower. That friction reveals something deeper. The challenge is not just about tools or capability. It’s about trust, accountability, and how work itself is structured. In high-stakes environments, where someone must sign off and take responsibility, AI doesn’t simply slot in—it fundamentally reshapes how teams operate. This conversation with Alex, Ian, Oli, and Adrian explores what happens when AI moves from experimentation into real production environments, and why the bottlenecks are as much human and organizational as they are technical. What You’ll Learn AI can reduce productivity before improving it: Senior engineers may initially slow down due to context switching and deeply ingrained workflows.Trust is not abstract, it is operational: In regulated or high-risk systems, adoption depends on proof, repeatability, and accountability—not just perceived capability.Accountability remains human even in AI-driven systems: Someone must still sign off on outputs, especially in safety-critical environments.Team roles are shifting from building to assuring systems: The future focus moves from writing code to validating system behavior and outcomes.Junior career paths are being disrupted: Traditional entry-level tasks are increasingly automated, forcing a rethink of how engineers are trained.AI adoption varies dramatically by domain: Safety-critical industries like aviation will adopt far more slowly than consumer or enterprise software.Larger code generation introduces new risks: AI can produce more code faster, but also increases bug rates and cognitive load for reviewers.The real constraint is system-level understanding: Teams must still comprehend architecture and system behavior, even if AI generates the code.Productivity gains follow a J-curve: Teams must go slower first to learn how to work effectively with AI tools. AI is already contributing to real production work: A measurable share of global code commits is now AI-assisted, with rapid growth expected.Time-Stamped Highlights (00:48) Anthropic Future of Work Data and Real Usage Gap (01:10) Theoretical AI Capability vs Actual Adoption (02:28) Why AI Agents Cluster in Certain Domains (03:31) Early Signals of AI Impact on Teams (05:19) Trust and Accountability as the Real Constraint (07:04) Why High-Trust Environments Adopt AI Slower (10:06) Proof vs Trust in AI System Validation (12:06) Shift from Coding to System Assurance (15:03) Disruption of Junior Developer Career Paths (17:03) Rethinking Learning and Skill Development (18:05) Why Senior Engineers Can Get Slower with AI (20:21) Rise of AI-Generated Code in GitHub (21:45) Larger Code Output and Increased Bug Rates (23:04) The J-Curve of AI Productivity (24:46) Human Oversight and AI in Production Systems Guests Ian Painter — Startup Advisor and Mentor. Previously, Vice President, Platform and Data at Cirium; Founder, Snowflake SoftwareIan is a seasoned technology leader in aviation data and analytics. He founded Snowflake Software in 2001, building enterprise data exchange and aviation data platforms that were later acquired by Cirium (RELX plc). As VP of Platform and Data, he oversaw data strategy and large-scale platform initiatives at one of the world’s most trusted aviation analytics companies.LinkedIn: https://www.linkedin.com/in/ianpainter/ Oliver 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/ Adrian McKenzie — Director of Software Engineering at CiriumAdrian leads engineering teams responsible for delivering scalable, mission-critical aviation data and analytics solutions. His background includes progressive leadership in software delivery and architecture at both Snowflake Software and Cirium, with decades of experience in team performance, engineering operations, and large-scale systems.LinkedIn: https://www.linkedin.com/in/adrianmckenzie/ 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 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-cases Brought To You By Airside 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.

    22 min
  7. MAR 25

    How a Simple Barcode Saved Airlines $1.5 Billion and Replaced Paper Tickets

    That quick moment at the gate when you pull up a boarding pass on your phone and scan a QR code feels routine now. It isn’t. That interaction represents one of the most successful global standards ever deployed in aviation—a shift from magnetic stripes to barcodes that saved the industry over $1.5 billion annually. But the real story isn’t the technology. It’s how an entire industry coordinated across competitors, regulators, and infrastructure to make it work. Eric Leopold spent 15 years at IATA working on exactly that kind of industry plumbing. In this episode, Eric Leopold takes us inside the machinery of aviation standards—from boarding passes to APIs to AI—and explains why the next wave of innovation won’t be limited by technology, but by data consistency, trust, identity, and industry alignment. That becomes even more important once the conversation turns to AI. The interesting question is not whether an LLM can help you shop for flights. It is whether the travel industry can build the identity, data consistency, trust networks, and commercial models needed for AI agents to actually transact on your behalf without breaking the system underneath. What You’ll Learn The barcode boarding pass was a standards and adoption challenge, not just a scanning upgrade: Replacing magnetic stripes required industry alignment across airlines, airports, manufacturers, and regulators.IATA standards only work when multiple airlines share the same problem: A standard starts when airlines identify a common need, build support, test the technical approach, and then push for industry adoption.The old airline distribution stack was both brilliant and constrained: Long before the web, airlines had global real-time reservation infrastructure, but it was built on private networks and legacy protocols that later needed modernization.NDC emerged from the need for a common API layer: Airlines had already tested direct API distribution, but agencies would not adapt for one carrier at a time, forcing the industry toward a shared standard.AI in travel depends on data models more than demos: If the underlying entities, definitions, and relationships are inconsistent, AI systems will produce plausible but wrong answers.The aviation industry data model matters more now than when it was created: A shared semantic layer becomes much more valuable once AI agents need normalized data they can reason across.Travel intermediaries may split rather than disappear: AI could create a new model where travelers have trusted buying agents while suppliers are represented by their own selling agents.Trust, identity, and settlement are still unsolved AI-era problems: For autonomous shopping and booking to work, agents need ways to verify who they represent, enforce agreements, and resolve disputes across the network. Time-Stamped Highlights (00:10) Eric Leopold and the Hidden Infrastructure Behind Modern Travel(02:35) Why 2005 Was a Turning Point for Aviation Technology(03:13) Designing the Barcode Boarding Pass Standard(05:56) Why Politics, Not Technology, Slows Aviation Change(08:13) How IATA Actually Creates Global Standards(10:30) From Standards to Global Implementation(13:35) The Shift from Magnetic Stripes to Barcodes(16:06) How Mobile Phones Accelerated Adoption(19:57) NDC and the Move to API-Based Distribution(24:24) Airline Websites vs Online Travel Agents(28:36) AI Enters Travel Booking(30:06) Why Data Quality Is the Real AI Bottleneck(33:27) The Problem of Data Normalization(36:22) Knowledge Graphs vs LLMs(41:04) Trust, Identity, and the Future of AI Travel AgentsGuest Eric Leopold — Founder, Threedot Eric is the founder of Threedot, a consultancy focused on the travel industry, and a board member and advisor to multiple travel companies. He spent 15 years at IATA, where he worked on some of the most impactful industry standards, including the transition to barcode boarding passes and the development of airline distribution and data models. His work has directly shaped the infrastructure used by billions of passengers worldwide.LinkedIn: https://www.linkedin.com/in/ericleopold/Company: https://www.linkedin.com/company/threedot/ 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 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-cases Brought To You By Airside 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.

    1h 11m
  8. MAR 16

    Why Your Istanbul Airport Sandwich Costs €22: The Economics Behind Drop-Off Fees and Retail

    Airports look like infrastructure businesses. Runways, terminals, aircraft movements. It’s easy to assume they make their money from planes. But some of the most valuable assets at capacity-constrained airports—slots—generate no direct revenue for the airport at all. Meanwhile, car parks can outperform landing fees, retail margins influence pricing strategy, and regulation quietly determines why your drop-off charge keeps rising. Professor Achim Czerny has spent decades studying airport economics. In this conversation, he breaks down the real incentive structures shaping airport behavior—from slot allocation and price caps to transfer competition and why a €9 coffee might be entirely rational. What You’ll Learn Why airports do not profit from slots: Slots are scarce and valuable, but under global scheduling rules, the economic value primarily accrues to airlines—not airports.How non-aeronautical revenue drives strategy: Car parking, retail, and drop-off fees can materially outperform traditional landing fees.Why regulation reshapes pricing incentives: Price caps on aeronautical services push airports to increase non-aeronautical charges instead.How competition differs by passenger type: Origin-destination passengers create local competition; transfer passengers create global hub competition.Why some airports may subsidize airlines: Under a “single till” logic, strong retail margins can justify lowering—or even offsetting—aeronautical charges.Why friction persists despite technology: Priority lanes and congestion can be revenue-generating mechanisms, complicating the push toward full efficiency.How airports compete for airlines: Route development, incentives, and even marketing tactics are used to attract airline bases.What the airport of the future might look like: Humanoid robots, biometric boarding, and automation could reshape both labor and passenger experience.Time-Stamped Highlights (00:22) Guest Introduction: Professor Achim Czerny(04:09) Airport Slots and Why Airports Do Not Capture Their Value(08:28) Aeronautical vs. Non-Aeronautical Revenue Explained(10:21) Why Car Parking Can Outearn Landing Fees(13:10) Heathrow Regulation and the Incentive to Raise Drop-Off Charges(17:08) High Retail Prices at Major Hubs Like Istanbul(18:50) The 60/40 Revenue Split and How It Has Evolved(21:14) Catchment Areas and Real Airport Competition(24:00) Origin-Destination vs. Transfer Passenger Markets(29:05) Why Transfer Competition Is Globally Intense(32:04) London Southend’s Route Strategy With Wizz Air(35:30) Airline Leverage and the Threat to Withdraw Capacity(38:08) The Future of Airports: Technology and AI(39:19) Humanoid Robots as a Response to Labor Constraints(45:06) Priority Channels, Congestion, and Revenue IncentivesGuest Professor Achim Czerny — Professor, Department of Logistics and Maritime Studies, Hong Kong Polytechnic University Professor Czerny is a leading scholar in aviation and transportation economics. He serves as Chairman of the German Aviation Research Society, Vice President of the International Transportation Economics Association, and is a member of the executive committees of the European Aviation Conference Institute and the Air Transport Research Society. His work focuses on airport pricing, slot allocation, regulation, and market competition—bringing academic rigor to questions that directly affect passengers, airlines, and policymakers.LinkedIn: https://www.linkedin.com/in/achim-i-czerny-0b61a1113/ 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 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-cases Brought To You By Airside 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.

    54 min

About

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

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