Airlines have been trying to modernize their retailing for over a decade, and most still can't change or refund what they sell.

Ann Cederhall is co-founder of LeapShift and one of the architects of the original NDC Direct Connect implementations at Lufthansa, where she helped build the project that became known as the "16 Euros" surcharge. In this episode, she traces the structural reasons why airline retailing has stalled: from the servicing gaps baked into NDC standards through version 24.1, to the 70% of airlines operating without any order management system, to the $650 million to $3 billion in annual revenue leakage from interline proration disputes. The conversation covers what AI can realistically fix and what it cannot.

What You'll Learn

• NDC servicing gap: Airlines could book via NDC from 2012 but could not change, cancel, or refund those bookings until the 24.1 standard in 2024, a 12-year gap that fundamentally limited what airlines could sell through the channel.
• Version fragmentation: Approximately 70% of airlines currently on NDC are still running version 17.1, leaving them without the servicing capabilities that would make the standard commercially viable.
• Order management absence: Nearly 70% of airlines surveyed have no orchestration or order management system, meaning they have no centralized control over what they have sold, to whom, and what can be changed.
• Ancillary inventory failure: Airlines routinely sell ancillary services (seat upgrades, fast track, bags) with no system to verify that those services actually exist at the time and place of purchase.
• Upgrade opportunity cost: Willingness to pay increases sharply close to departure and at the airport, but most airlines' systems cannot process an upgrade when the booking is held in a travel seller's PNR rather than the airline's own record.
• AI's real limits in retailing: Agentic AI can filter and interpret shopping results, but it cannot replace shopping engines that have not been modernized in 30 years and still process 20 million fares to surface a handful of relevant options.
• Revenue management transformation: AI agents can harvest competitor cancellation rates, demand signals, and real-time market data overnight and present a synthesized briefing. That is a significant shift from traditional RM systems built on historical averages.
• Revenue leakage scale: Global interline revenue leakage runs between $650 million and $3 billion annually, driven by inaccurate proration calculations, uncollected taxes, missing ancillary settlements, and unsettled ticket coupons. Many of these disputes cost more to resolve than the amounts in question.

Time-Stamped Highlights

• (00:00) Introduction and Ann's background in travel
• (01:19) First airline role at Spantax, then Amex, Amadeus, and SAS
• (04:03) Arriving at Lufthansa in 2014 and the beginning of NDC
• (05:15) The "16 Euros" surcharge: what it was and why it caused shock
• (11:02) Why NDC fell short: no servicing, no ecosystem, GDS recapture
• (19:03) The order management gap: 70% of airlines with no orchestration
• (24:32) Ancillary failures: selling services that don't exist
• (30:33) Upgrade economics and the travel wallet effect
• (36:00) Why auctions and seat upgrades require caution on premium routes
• (42:04) What AI can and cannot do in airline retailing
• (49:35) Revenue management: from sky gods and Excel to overnight AI agents
• (55:12) Where AI genuinely helps: documentation, process archaeology, long-tail demand
• (01:01:00) The shopping engine problem: 30 years without modernization
• (01:06:00) Revenue leakage: $3 billion in interline proration disputes explained

Guest bio
Ann Cederhall is co-founder of LeapShift, a consultancy focused on airline retailing, distribution, and commercial strategy. She has held senior roles at Lufthansa, Scandinavian Airlines, Amadeus, and ATPCo, and was involved in the original NDC Direct Connect implementation at Lufthansa in 2015. She is the author of the State of Airline Retailing 2026 report. LinkedIn: https://www.linkedin.com/in/anncederhall/ Company: https://leapshift.com/

About the Podcast 
The Travel Tech Podcast features long-form conversations with leaders across travel and technology, exploring 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 bio
Alex Brooker is founder of Airside Labs, an AI business that applies aviation-grade testing and compliance rigor to enterprise AI systems. Before founding Airside Labs, he built and scaled complex software in aviation and safety-critical domains. He also invests in early-stage technology ventures. LinkedIn: https://www.linkedin.com/in/alex-brooker-2280002/

Some travel operators ask you to shout your passport number across a crowded desk and think nothing of it. While intentions are good (checking who you are), this episode is about why that is a serious security failure and what it would take to fix it.

Yagub Rahimov is the CEO and founder of Polygraf AI, a company building behavioral security and contextual privacy tools for enterprise environments. In this conversation, he and Alex work through the specific vulnerabilities created when AI agents gain user level access, why human behavior rather than model failure is responsible for the vast majority of data breaches, and what a genuinely privacy respecting travel product would actually look like.

What You'll Learn:

• Agent security: AI agents are a new category of user in the digital security pyramid, with the same system access as humans but no training in deception or social engineering.
• Deep fake risk: Voice cloning is already sophisticated enough to impersonate individuals convincingly to family members and colleagues, without any technical breach of the underlying systems.
• Mosaic intelligence: Even anonymized data fed repeatedly to an AI can be re-identified over time through behavioral pattern mapping, a concept Rahimov terms "mosaic intelligence."
• Behavioral control: Addressing human behavior in real time, before a violation occurs, is more effective than after-the-fact audit or punitive controls, demonstrated by a 72% drop in DLP violations for one enterprise client.
• Data in AI tools: Organizations that deploy internal LLMs without governing what employees input are creating serious exposure, as one $25M chatbot deployment illustrated on its first day.
• Travel industry failures: Asking passengers to recite passport numbers and dates of birth aloud in crowded gate areas, or type personal data into in-flight entertainment screens, represents a real and unaddressed privacy risk.
• Tokenization as a fix: Stripping personal data before it reaches an LLM and reuniting it with processed output via tokenization can deliver the same analytical value with substantially less exposure.
• QA at scale: AI makes universal quality assurance of customer interactions cheap enough that random sampling is no longer the only option, with one call center client processing 500,000 calls daily at 5 to 10 cents per call.

Time-Stamped Highlights:

• (00:00) Introduction: The airport data disclosure problem
• (00:00:42) What actually happened with Meta's Instagram AI chatbot
• (00:06:17) AI agents as a new user type: the security pyramid explained
• (00:08:57) Deep fakes in practice: voice cloning, elderly parents, and the CEO
• (00:14:36) North Korean infiltration via data science job interviews
• (00:20:54) How Polygraf detects synthetic speech in real-time video calls
• (00:28:42) The meeting note taker with 23 vulnerabilities
• (00:36:24) How Mr. Paranoid travels: loyalty status, one airline, mid-tier hotels
• (00:42:58) The oil and gas CEO kidnapping and the email summarizer attack vector
• (00:49:00) What travel companies get wrong about passenger data collection
• (00:30:10) Mosaic intelligence and why anonymizing data is not enough
• (01:07:07) The $25M HR chatbot and the 72% DLP violation reduction
• (01:14:12) Building the next OTA: tokenization, QA at scale, and simplicity
• (01:21:01) Red teaming, visibility, and why behavioral control is the next frontier

Guest bio: Yagub Rahimov is CEO and founder of Polygraf AI, a company specializing in behavioral security, contextual privacy, and AI risk management for enterprise clients. He works across defense, financial services, and enterprise technology sectors, and is an active contributor to conversations on AI behavioral control at venues including the Gartner Security Summit. LinkedIn: https://www.linkedin.com/in/yrahimov/ | Company: https://polygraf.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 bio: Alex Brooker is the founder of Airside Labs, an AI business that applies aviation-grade testing and compliance rigor to enterprise AI systems. Before founding Airside Labs, he built and scaled complex software in aviation and safety-critical domains, and he invests in early-stage technology ventures. LinkedIn: https://www.linkedin.com/in/alex-brooker-2280002/

The travel industry is ten years behind on tech, and AI itinerary builders are making it worse, not better.

Alex Ragin is the founder of Zoftify, a travel focused software agency, and Tourseta, a booking and operations platform built specifically for high volume multi day tour operators. In this conversation, he draws on a decade of building software inside the travel industry to explain why the operational complexity of group travel is so routinely underestimated, why vibe coded solutions collapse against real world edge cases, and where AI is actually delivering value versus where it is still mostly a demo.

What You'll Learn

• Travel tech complexity: The industry is not one market but a collection of micro industries (airlines, hotels, tour operators, cruises), each with distinct workflows that make cross vertical software almost impossible to build well.
• The AI use case filter: The most reliable test for a legitimate AI application is whether a simpler procedural solution would be faster, cheaper, and more reliable, and in most cases it would be.
• Itinerary builder limitations: AI itinerary tools still require manual validation at every step because missing supplier data causes errors that directly damage traveler trust and booking relationships.
• The vibe coding ceiling: Code represents roughly 20% of what makes a complex software product work; the remaining 80% is domain knowledge, process design, and edge case handling that AI cannot yet substitute.
• Where AI is genuinely productive: Internal development workflows, UI/UX auditing, and unstructured data analysis are the areas where Zoftify has seen consistent, measurable productivity gains from AI tooling.
• The AI search shift: Tour operators are already seeing meaningful lead quality from ChatGPT and Gemini referrals, often outperforming traditional Google traffic on conversion, and this is where the real near term disruption is happening.
• Niche focus as a business strategy: Tourseta deliberately avoids FIT and day tour operators to stay laser focused on the bookable multi day, high volume segment, a sub vertical with almost no specialized competition.
• The group travel operations problem: Managing a 25 or 50 person tour involves payment installment tracking, passport data collection, rooming list management, supplier confirmation, and last minute changes at a scale where a single missed step creates outsized downstream problems.

Time Stamped Highlights

• (00:00) Introduction: Group Travel Is Harder Than It Looks
• (02:07) How Zoftify Started: From Two-Person Consultancy to Travel Agency
• (04:09) Why the Travel Industry Chose Them (Not the Other Way Around)
• (06:24) What Makes Travel Tech So Complex: Micro-Industries Within the Industry
• (10:12) AI Hype in 2022 vs. AI Requests in 2026: What's Actually Changed
• (14:14) Where AI Earns Its Place: Development, UX Audits, and Data Analysis
• (19:20) The Chatbot Reality Check: When 70% Resolution Rates Don't Show Up
• (22:47) Why Itinerary Builders Still Need a Human in the Loop
• (28:29) You Can't Vibe Code a Tour Operator: The 80% Problem
• (31:41) Tourseta's Origin: Building the Same Platform Seven Times Before Productizing
• (36:54) The Multi-Day Tour Operations Stack: Payments, Manifests, Rooming Lists
• (43:06) Where the Industry Is Headed: AI Search, GDS Adaptation, and Distribution Gaps
• (48:31) Opportunities Alex Won't Chase: Cruises, Corporate Travel Niches, and More
• (49:31) How to Reach Alex: LinkedIn, Zoftify, and Tourseta

Guest Bio

Alex Ragin is the founder of Zoftify, a travel focused software development agency, and Tourseta, a booking and operations platform for multi day tour operators. He has been building software for the travel industry since 2015, with prior experience in fintech and video streaming for major UK broadcasters. LinkedIn: https://www.linkedin.com/in/alexander-ragin/ | Zoftify: https://zoftify.com/ | Tourseta: https://tourseta.com/

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 Bio
Alex Brooker is the founder of Airside Labs, an AI business that applies aviation-grade testing and compliance rigor to enterprise AI systems. Before founding Airside Labs, he built and scaled complex software in aviation and safety-critical domains. He also invests in early-stage technology ventures and advocates for practical, real-world AI deployment strategies. LinkedIn: https://www.linkedin.com/in/alex-brooker-2280002/

The only sustainable innovations that actually scale are the ones customers never have to think about. Josh Dorfman has spent two decades building them.

Josh Dorfman is the co-founder of Planted (plantdmaterials.com), a materials startup building structural panels from fast-growing grass as a direct replacement for wood-derived products in U.S. home construction. He came up through consumer sustainability media (books, Sirius radio, TV) under the Lazy Environmentalist brand before pivoting to B2B climate technology. In this conversation, Josh and Alex explore the mechanics of low-friction sustainability across building materials, aviation, carbon credits, and the unexpected efficiency gains hiding in the GLP-1 drug story.

What You'll Learn

• The Drop-In Rule: Sustainable materials only reach scale when they integrate into existing workflows without asking the customer to change anything.
• B2B green sales: Even the most environmentally committed executive cannot justify a purchase on environmental grounds alone. The product has to win on performance and price first.
• The Trove playbook: Climate companies that succeed eventually stop leading with climate, treating sustainability as a downstream brand benefit rather than the sales pitch.
• Carbon credits: Voluntary offset schemes largely transfer the cost of an airline's impact onto consumers while delivering minimal real-world emissions reduction.
• GLP-1 and aviation: Jefferies estimates adoption of weight-loss drugs like Ozempic could save U.S. airlines around $580M annually in fuel costs, about 1.5% of fuel spend. Jefferies separately modelled a 2% weight reduction translating to roughly 4% EPS uplift. The point: the most significant efficiency wins are often not engineering solutions. 
• Battery cost curves: Declining battery costs are already reshaping U.S. power grid additions (51% solar, 28% battery storage projected for the next 12 months) and will accelerate electric aviation faster than most forecasts assume.
• Grass over trees: Planted's core material grows 10x faster than timber and can be harvested annually, enabling carbon sequestration at a scale that tree-planting programs cannot match.
• Storytelling as company-building: In a venture-backed startup, the founder is simultaneously selling the company and the product. The skill set required is identical.

Timestamped Highlights

• (00:00) Introduction: IATA 2050 targets, SAF adoption, and why materials innovation matters
• (00:31) Josh's origin story: The Lazy Environmentalist, Vivavi furniture, and going green in Brooklyn
• (07:01) The pivot: from consumer media to B2B climate materials
• (12:49) Why sustainability pitches fail, and what actually drives B2B purchasing decisions
• (18:56) The Trove case study: Fight Club rules for climate companies
• (25:03) How Planted was born: a SpaceX engineer, six trash bags of hemp, and a phone call
• (32:52) Testing every biomass: from hemp to Halloween hay
• (38:41) Bringing it to aviation: SAF, the GLP-1 surprise, and the $580M olive
• (32:33) Carbon credits: why they're mostly marketing, and what airlines should do instead
• (38:00) Planted's roadmap: biochar, graphene, and potential aviation materials
• (43:50) Battery technology and why the cost curve matters more than regulation
• (44:06) What's coming in 2026 for Planted: furniture launch, new panel systems, homebuilder announcements
• (49:50) Ground fleet electrification and the Our World reusable cup trial

Guest bio Josh Dorfman is the co-founder and CEO of Planted (plantdmaterials.com), a North Carolina-based materials company producing structural building panels from perennial grass as a timber replacement. He previously built the Lazy Environmentalist media brand across books, Sirius Satellite Radio, and television, and hosts the Super Cool podcast (getsuper.cool/podcast), which covers climate technology and founders. LinkedIn: linkedin.com/in/dorfmanjosh/

About the Podcast The Travel Tech Podcast features long-form conversations with leaders across travel and technology, exploring 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 bio Alex Brooker is the founder of Airside Labs, an aviation AI agency applying aviation-grade testing and compliance rigour to AI systems in safety critical and regulated domains. Before founding Airside Labs, he built and scaled complex software across aviation and both business and safety critical domains. LinkedIn: linkedin.com/in/alex-brooker-2280002/

The travel tech stack has a dirty secret: the more suppliers connect to each other, the higher the chance your inventory ends up competing against itself.

Olivier Boinet is the founder of room-matching.com and Omnitravel.ai, two tools built to solve the data normalization and room-mapping problems at the root of travel distribution chaos. In this conversation, Alex and Olivier work through why hotel data loses quality and identity as it moves through the distribution chain, how the current API landscape creates circular inventory loops, and what hoteliers need to do right now to ensure AI search agents can find and trust their properties.

What You'll Learn

• Room mapping: Identical hotel rooms listed under different names and codes across suppliers create significant matching errors that still require manual comparison in most agencies.
• Data normalization: Pushing inventory through intermediary systems strips away a hotel's personality, including the specific content, offers, and experiences that differentiate the property.
• Distribution loops: In B2B travel, strategic partnerships between suppliers are so interlocking that a hotel's own inventory can circulate back to it through a chain of partners, marked up along the way.
• AI discoverability: LLMs evaluate hotels first as websites. If a property's content isn't structured for machine legibility, it won't surface in AI-powered search results or recommendations.
• Dynamic content personalization: Corpus-based retrieval architectures allow a single property's content to respond differently depending on whether the searcher is a Gen Z solo traveler, a British couple, or a corporate booker.
• Vibe booking: High-quality, experience-focused content drives significantly higher conversion, whether the audience is a human or an LLM scanning for properties to recommend.
• Direct booking imperative: As LLMs increasingly route booking intent straight to properties, hotels without structured, AI-ready web pages will lose direct channel share to those that have invested in content quality.
• The confirmation paradox: The industry-wide check-recheck-check loop across API chains consumes enormous resources and still produces availability errors, a structural inefficiency that AI pressure is beginning to expose.

Time-Stamped Highlights

• (00:00) Introduction and context: the fake hotel booking episode that sparked this conversation
• (00:01:17) Olivier's origin story: from software developer to travel agency floor shock
• (00:02:00) 20 agents, 10 portals each: the room comparison problem in practice
• (00:03:05) Building room-matching.com: applying NLP and heuristics to dynamic room deduplication
• (00:05:00) The normalization trap: why pushing data through intermediaries erases hotel identity
• (00:06:14) Omnitravel's approach: using the live website as the source of truth for AI-ready data
• (00:09:22) The circular inventory problem: how B2B partnerships create self-distribution loops
• (00:11:23) What LLMs are actually doing when they evaluate hotel websites
• (00:13:10) Dynamic personalization via corpus-based retrieval: serving different content to different traveler profiles
• (00:10:40) Vibe booking: why content quality is now a distribution strategy
• (00:09:01) The check-recheck-check loop and its cost to the industry
• (00:15:14) Open-source tools that can power personalized AI content distribution today

Guest bio
Olivier Boinet is the founder of room-matching.com, a dynamic room-mapping platform used across the travel industry, and Omnitravel.ai, a data normalization and AI-readiness tool for hotels and tour operators. With 30 years of software development experience spanning antivirus heuristics, NLP, and travel technology, he brings an unusually technical lens to the distribution and content quality problems facing the hospitality sector. Connect with him at linkedin.com/in/olivier-boinet-3b328023, room-matching.com, and omnitravel.ai.

About the Podcast
The Travel Tech Podcast features long-form conversations with leaders across travel and technology, exploring 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 bio
Alex Brooker is the founder of Airside Labs, an AI business that applies aviation-grade testing and compliance rigor to enterprise AI systems. Before founding Airside Labs, he built and scaled complex software in aviation and safety-critical domains. He also invests in early-stage technology ventures and advocates for thoughtful, real-world AI deployment strategies. LinkedIn: linkedin.com/in/alex-brooker-2280002

What if the AI moment in travel is less about building a better OTA, and more about making the OTA unnecessary?

Christopher Olivares is the solo founder of Elyo (elyo.io), a conversational AI travel assistant that helps travelers find the cheapest flights across flexible destinations and dates, with no commissions, intermediaries, or date pickers. In this episode, Christopher traces his path from OECD policy analyst and expat traveler to vibe-coded solopreneur, and explains how generative AI unlocked both the product idea and the ability to build it without a technical background. The conversation covers the incentive problems embedded in OTAs, the economics of airline distribution, the future of travel discovery, and why AI may finally enable a return to genuinely traveler-first service.

What You'll Learn

• Traveler intent vs. traveler input: Elyo is built around decomposing what a traveler wants (cheapest meeting point, most flexible weekend, best value destination) rather than the rigid inputs legacy search UIs require.
• The OTA commission problem: Using a "free" platform isn't free. Commissions get reflected in prices, and the traveler absorbs costs they never see.
• Freemium as a trust mechanism: Elyo's subscription model exists specifically so the platform doesn't have to earn commissions, which keeps the traveler's interest as the unconditional North Star.
• AI as a leveler for solo founders: Christopher built Elyo without any prior coding experience, using LLMs both to imagine the product and to build it, illustrating a real shift in who can launch a technical startup.
• GDS access is getting harder for startups: At least one major GDS has closed its developer portal, raising barriers for early-stage builders trying to validate ideas before committing to full commercialization.
• The seller-of-record problem: Many white-label distribution APIs make startups the seller of record for tickets, a liability that most early-stage founders (Elyo included) want no part of.
• AI as a return to the travel agent era: By removing the human cost of advisory, AI can deliver the personalization of pre-internet travel agents alongside the price transparency the metasearch era created, without the commission layer.
• Corporate travel is an underserved use case: The remote-team "where should we rendezvous?" problem is a direct extension of Elyo's core optimization, and today's corporate booking platforms remain shockingly poor on UX.

Time-Stamped Highlights

• (00:00) Introduction and episode overview
• (00:01:14) Christopher's background: diplomacy, teaching English in Japan and Spain, and the OECD
• (00:04:26) The data standards challenge: why counting schools is harder than it sounds
• (00:07:05) The original idea: meeting friends in a cheap third city
• (00:10:34) Why generative AI unlocked both the product concept and the build
• (00:14:19) Elyo: what it is, how it works, and why the date picker had to die
• (00:24:12) The traveler-first business model: freemium, no commissions, direct airline links
• (00:32:07) Navigating airline distribution: GDSs, NDC, white-label APIs, and the seller-of-record problem
• (00:37:45) Incentive structures in travel: why "free" platforms aren't free
• (00:40:01) The AI moment in travel distribution: OTA integrations into chat services
• (00:44:45) Corporate travel and the remote-team rendezvous use case
• (00:45:51) The return of the travel agent: personalization plus democratization
• (00:48:12) Early adopters, honest pricing, and what's coming next for Elyo
• (00:47:37) Where to find Elyo and the origin of the name

Guest Bio
Christopher Olivares is the solo founder of Elyo, a conversational AI travel assistant. Before launching Elyo, he spent four and a half years at the OECD in Paris working on internal ethics, education policy, and international statistical indicators, and is currently completing an executive master's in statistics and artificial intelligence at Université Paris Dauphine. LinkedIn: https://www.linkedin.com/in/christopher-olivares-40b8b283/
Elyo: https://elyo.io/?ref=travel-tech-podcast&utm_source=podcast&utm_medium=podcast 

About the Podcast
The Travel Tech Podcast features long-form conversations with leaders across travel and technology, exploring 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 Bio
Alex Brooker is the founder of Airside Labs, an AI business that applies aviation-grade testing and compliance rigor to building enterprise AI systems. Before founding Airside Labs, he built and scaled complex software in aviation and safety-critical domains. 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/

Airline distribution is sitting on decades of tech debt and AI might be the only thing that can fix it.

Jim Hetzel is a travel and airline technology veteran who now leads retailing strategy at TWAI. In this conversation, he traces the full arc of airline distribution from fragmented pre-GDS ticketing to the NDC standards work and makes the case that AI is positioned to become the new orchestration layer the industry desperately needs. The discussion also explores the trust problem that no one in the AI agent era has solved yet: who plays the role of IATA when billions of bots are buying plane tickets?

What You'll Learn

• GDS origin: The Global Distribution System was built to solve a fragmentation problem giving travel sellers a single electronic marketplace instead of supplier-by-supplier chaos.
• NDC's limits: NDC is a messaging standard, not a retailing platform; airlines that want to become true retailers still need massive investments in CRM, personalization, and revenue management.
• Standards incompatibility: NDC versions are not backwards compatible with each other, which means early adopters face millions of dollars in re-implementation costs every major release cycle.
• AI as normalizer: AI can sit on top of both legacy GDS infrastructure and modern NDC standards simultaneously, acting as an intelligent interpreter rather than waiting for the industry to agree on a single format.
• Bot demand risk: AI shopping agents never stop checking, unlike human travelers, which means airline systems could face look-to-book ratios of one million to one, infrastructure costs that dwarf current GDS fees.
• Trust gap: IATA's historic role was to certify agents and airlines as legitimate counterparties; no equivalent trust and authentication layer exists yet for machine-to-machine AI agent transactions.
• Fare calculation art: Even today, skilled international pricing specialists can find fare combinations that GDS pricing engines miss and that variability, tolerance for imprecision, is baked into the industry by design.
• Intermediaries survive: AI doesn't kill intermediaries wholesale; it kills the weak ones. The players who solve orchestration, trust, and content normalization at scale will define the next generation of distribution.

Time-Stamped Highlights

• (00:00) Introduction and episode framing
• (00:21) Distribution before computers: fragmentation and the pre-GDS world
• (03:04) How the GDS created an electronic marketplace buffer
• (04:11) NDC: messaging standard vs. retailing platform
• (09:59) Why backwards incompatibility made NDC costly for early adopters
• (12:17) "A dumpster fire": the current state of airline distribution standards
• (15:25) Travel agencies caught supporting both GDS and NDC simultaneously
• (17:22) AI as the normalization layer across incompatible standards
• (22:21) Bot demand: look-to-book ratios and machine-generated traffic at scale
• (23:55) IATA's dual trust role and why AI agents have no equivalent
• (35:05) GDS pricing discrepancies: three systems, same itinerary, different fares
• (38:39) The "art" of international fare calculation and AI's opportunity there
• (40:25) Who builds the next trust and orchestration layer?
• (45:53) TWAI: modern retailing across GDS, NDC, and non-air content today

Guest Bio
Jim Hetzel is a travel and airline technology executive with a career spanning corporate travel agencies to enterprise distribution platforms. He currently works at TWAI, a travel retailing technology company that enables airlines and travel sellers to offer multi-source content: GDS, NDC, hotels, car rental, activities through a unified platform. LinkedIn: https://www.linkedin.com/in/jhetzel/ | Company: https://twai.com

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 Bio
Alex Brooker is the founder of Airside Labs, an AI business that applies aviation-grade testing and compliance rigor to enterprise AI systems. Before founding Airside Labs, Alex built and scaled complex software in aviation and safety-critical domains. LinkedIn: https://www.linkedin.com/in/alex-brooker-2280002/ | Company: https://airsidelabs.com

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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 Bio
Fred 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.

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 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.

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 agents
• The real complexity in travel isn’t search—it’s data normalization, deduplication, and pricing logic
• Agentic AI shifts power away from brands toward personalized user-controlled experiences
• Loyalty programs may weaken as agents optimize for outcomes, not brand preference
• The “last mile” problems—like booking failures at hotels—still cost the industry ~2% of transactions
• AI can now solve operational gaps (like reconfirmation) that were previously too expensive to fix with humans
• Travel distribution is becoming infrastructure-first, where aggregation layers power entire ecosystems
• In the future, agents may transact directly with other agents, reshaping how commerce works

Time-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 Solutions
Mike 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.com
Routestack: 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 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.