Travel Tech Podcast

Alex Brooker

The Travel Tech Podcast, hosted by Alex Brooker, 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. Alex Brooker is an industry veteran with experience in aviation, start up to exit, and AI transformation.

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#33
Yesterday · 57 min
Above China, Your Starlink Doesn't Exist
The most reliable AI on your next flight might be the one that assumes it has no internet connection at all. Ajith Balakumar is the CEO and founder of Forthcode, an aviation technology company that grew out of a point-of-sale system built for a 2,500-outlet coffee chain in India. The conversation covers how an offline-first architecture built for retail became the foundation for in-flight commerce, catering, loyalty, and an AI ground-staff agent called Davix, and how Ajith thinks about AI maturity, regulation, and building software at founder speed. What You'll Learn Offline-first architecture: In-flight software can't assume connectivity, because satellite access can be blocked by entire governments regardless of available bandwidth. AI trust: Ground staff trust an AI's answer more when it cites the exact SOP page and paragraph behind it, not just when it gives a confident response. AI maturity: Organizations move through three stages: co-pilots where the human decides everything, agents where the human approves a subset of decisions, and operational intelligence where multi-agent systems feed executive decision-making. Regulatory readiness: GDPR already applies to any European passenger's data, and standardized AI compliance layers, similar to an API gateway, are emerging from major cloud providers. Data sovereignty: Forthcode avoids routing airline data through frontier LLMs, preferring locally hosted models so information never leaves the airline's environment. Adoption pattern: Most airlines are still running isolated AI pilots rather than operational AI, because executives want quantifiable ROI before scaling. Builder speed: AI-assisted prototyping now lets a founder build and test a fully functional application in about an hour, compared with days of spec-writing and revision cycles. Prompting as a diagnostic: How someone prompts a general AI tool reveals their own problem-solving process, which is part of why teams with AI tools still underuse them. Time-Stamped Highlights (0:00) The accidental entry into aviation, through a coffee chain's point-of-sale system (4:03) Why offline-first became the only viable architecture for in-flight transactions (4:45) The geopolitics of connectivity: Starlink, airspace, and government restrictions (7:56) The reconciliation problem: every flight is a store with no fixed manager (11:27) Where Forthcode sits in the airline tech stack: retail, catering, and Lounge in the Sky (13:44) Introducing Davix, the AI roving agent for ground staff (15:54) Why evidence and citations solve AI's trust problem with frontline staff (19:41) The stress of ground staff work and how AI changes accountability (25:53) The AI maturity model: co-pilots, agents, and operational intelligence (29:27) India versus Europe: GDPR, EASA, and the coming wave of AI guardrail tooling (33:37) Why Forthcode avoids frontier LLMs and is building fully offline in-flight AI (36:32) The current state of AI adoption across airlines: pilots versus operational AI (42:38) Building a WhatsApp-driven to-do list app in one hour as a founder (55:05) Closing thoughts: the upcoming Forthcode aviation AI report and what's next Closing thoughts: the upcoming Forthcode aviation AI report and what's next Guest bio Ajith Balakumar is the CEO and founder of Forthcode, an aviation technology company built around an offline-first architecture, covering in-flight retail, catering management, and the loyalty product Lounge in the Sky, along with Davix, an AI agent for airport ground staff. Company: forthcode.com. LinkedIn: linkedin.com/in/ajithbalakumar. 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, and he now also invests in early-stage technology ventures.
#32
August 26 · 48 min
Why Can't I Just Book My Own Trip? Dual Identity, Dreadful Booking Tools and the Real Job of Corporate Travel
Why can't you just book your own work trip? You can. You just won't get reimbursed. Corporate travel exists to manage risk, cost and duty of care, and the tools built to enforce that have spent years treating the traveler as a problem to be contained rather than a person who books flights every week in their own life. Caitlin Gomez, Head of Growth at Amgine, joins Alex to unpack the dual identity at the heart of corporate travel: the same person is a consumer on their phone and a business traveler in the program, and almost nothing in the supply chain connects the two. They cover why the booking tools travelers have suffered through were never designed for them, how suppliers should think about attribution when a traveler shows up under a personal account, why Amgine positions itself as middleware that plugs into existing GDS and TMC infrastructure rather than replacing it, and why AI in corporate travel is only as useful as the antiquated systems it has to talk to. The conversation also takes in Amgine's omnichannel booking flow, the industry's blind spot on ground transportation, and what the recent strategic investment from BCD actually signals about the partnership. What You'll Learn Traveler experience vs. program design: Corporate travel isn't optimized for consumer grade experience because its real job is risk mitigation, cost control, and getting people home safely, not replicating a consumer app. Middleware positioning: Amgine deliberately avoids becoming a consumer brand, choosing instead to integrate into existing TMC and GDS infrastructure rather than compete with it. Fit over features: Flashy travel technology often fails in production because buyers select tools the way people furnish an apartment without measuring the room, and the tool doesn't actually fit the program. Attribution is unsolved: Consumer platforms like rideshare apps have no reliable way to tie a traveler's personal account back to their corporate persona, which limits how partners can prove value to a CFO. Ground transport is the visibility gap: Travel programs track travelers well in the air and at check in but lose visibility the moment someone is in a car between the airport and the hotel. AI is bounded by data quality: AI in travel is only as reliable as the legacy GDS and API infrastructure underneath it, and teams that skip fundamentals for AI shortcuts get stuck when systems break. Human judgment still leads: AI acts as a force multiplier for agents and engineers who already understand the domain, not a substitute for the human judgment needed when a trip goes wrong. Partnership over funding: Amgine's BCD investment came after four months of proven results and was framed internally as acceleration on an already fully funded company, not a lifeline. Timestamped Highlights (00:00) Cold open and podcast intro (00:46) Can employees just book their own travel? (02:49) Why corporate travel is layered, not hard (05:12) Where Amgine sits as "middleware" in the travel stack (06:18) Inside the omnichannel workflow: email, chat, Slack, WhatsApp (09:13) Lessons from GBTA and building Innovation Row (11:02) The apartment without measurements analogy (14:22) What suppliers get wrong: attribution and connective tissue (19:12) The ground transport blind spot and duty of care (25:17) Walking through the WhatsApp booking flow (32:43) Why AI is only as good as the data behind it (38:53) Personal vs. business travel risk tolerance (42:09) The BCD investment and what it actually signals (44:40) Amgine's agnostic positioning and where to find the team Guest bio Caitlin Gomez is Head of Growth at Amgine (amgine.ai), an AI powered middleware platform that automates the manual, time consuming parts of corporate travel booking without replacing existing GDS and TMC infrastructure. Her background spans travel technology partnerships at Lyft and CLEAR, a consumer facing role at Staples, TMC sales at HRG and Travel Leaders, and founding Innovation Row at GBTA. LinkedIn: https://www.linkedin.com/in/caitlingomez/ 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 in regulated environments. Before founding Airside Labs, he built and scaled complex software in aviation and safety critical domains and now invests in early stage technology ventures.
#31
August 18 · 47 min
89% of Airline Carts Never Convert
Airline checkout loses close to 9 out of 10 shoppers before they ever pay, and Kameron Bertine's fix isn't a redesign — it's an identity layer airlines were never built to have. Kameron Bertine is co-founder and CEO of Movmo, a startup building an identity and checkout layer for airlines and hotels modeled on Shopify's ShopPay. The conversation covers the origin of the problem in Kameron's own booking experience, why airline cart abandonment runs as high as 89%, how Movmo integrates with legacy PSS and NDC infrastructure without replacing it, and why Movmo is deliberately holding off on fully agentic booking despite having the technical capability today. What You'll Learn Cart abandonment: Airline booking abandonment runs around 89%, higher than e-commerce's roughly 70-79% and close to ferry bookings at the top of the range. Design pattern: Movmo is modeled directly on Shopify ShopPay and payment layers like Stripe Link and Klarna rather than inventing a new checkout behavior from scratch. Merchant of record: Airlines care most about retaining the merchant-of-record relationship, so Movmo is built as an identity and checkout layer that sits on top of existing systems rather than replacing them. Legacy infrastructure: Movmo is designed to work with whatever PSS, GDS, or NDC infrastructure an airline already runs, since rip-and-replace projects in this industry routinely stall for years. Agentic readiness: Movmo could technically ship agentic booking today, but is deliberately sequencing a two-to-three year rollout through express checkout and white-label products first to build traveler trust before letting AI agents transact directly. Sales reality: Enterprise airline sales cycles typically run 12 to 24 months, sometimes up to 36, which reframes a two-month first proposal as unusually fast progress. Industry priorities: Agentic or AI-driven booking reportedly sits under 5% on airline executives' list of priorities, well behind operations and other concerns. Conversion signal: ShopPay profiles reportedly convert roughly 50% better than guest checkout, a gap Movmo is betting will show up similarly in airline booking once identity persists across sessions. Time-Stamped Highlights (00:00) Cold open and episode introduction (02:05) The Ecuador-to-Spain booking that started it all (03:14) The ShopPay moment: the light bulb for Movmo (07:57) 89% cart abandonment and why it happens (11:01) What Movmo's early user research actually found (14:17) Inside the express checkout flow, explained (15:39) Designing the one-click booking experience (17:18) The escalator sales funnel at FTE/APEX Long Beach (21:52) Legacy rails: working with NDC, GDS, and PSS instead of replacing them (23:50) Layla, Gemini, and where agentic booking is really headed (31:18) Merchant of record, loyalty, and airline governance requirements (33:16) The commercial model and transaction-fee approach (36:58) Why Movmo won't launch full agentic booking yet (39:17) Biggest surprises: sales cycle length and a 35 NPS award Guest bio Kameron Bertine is co-founder and CEO of Movmo, an identity and checkout layer for airlines and hotels designed to reduce cart abandonment and enable persistent traveler profiles across booking sessions. He came from a product design background with prior experience in ERP systems, and founded Movmo in June 2024 after his own frustrating international booking experience. Company: movmo.io | LinkedIn: linkedin.com/in/kameron-bertine 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, helping organizations build and test AI agents in regulated environments. Before founding Airside Labs, he built and scaled complex software in aviation and safety-critical domains, and he also invests in early-stage technology ventures.
#30
August 12 · 32 min
The Feedback You Don't Notice You're Getting
Alex Brooker hands his own microphone to the two people who know him best and lets them ask the questions he never answers on his own show. Adrian McKenzie and Oli Deakin, Alex Brooker's former colleagues at Snowflake Software, take over hosting duties on the Travel Tech Podcast to interview Alex directly. The conversation moves through leadership philosophy, the book Alex is writing about his career before and during Snowflake Software, and the early-life habits, from door-to-door fossil sales to a career defining dressing down, that shaped how each of them works today. What You'll Learn Leadership: Being kind, not nice, means having the uncomfortable conversation instead of avoiding it. Feedback: The best feedback often doesn't register as feedback until you reflect on the conversation afterward. Trust: Giving honest feedback gets harder, not easier, with people you haven't worked with for long. Writing: Alex's book centers on the moment a founder's problems outgrow what one person can code alone. Strategy: Most technology leaders solve what's directly in front of them instead of planning three to five years ahead. Formation: Early hustle, from door-to-door sales to Christmas Day shifts, builds a lasting baseline for how someone works. Resilience: Harsh, accurate feedback early in a career can become the turning point that accelerates it. Risk: Leaving a large corporation trades procedural safety nets for closeness to every decision. Time-Stamped Highlights (0:00) Introduction: turning the tables on Alex (2:18) Lessons from moving out of corporate life (2:50) Be kind, not nice (8:17) The challenge of giving honest feedback to people you don't know well (11:14) Alex's book project and its emotional core (13:47) Ollie's hypothetical book: technology strategy (15:50) Formative story: Alex's childhood fossil-selling hustle (19:29) Ollie's turning point: the feedback that changed his career (24:01) Adrian's formative story: dinner table debates and connecting people (25:41) Threads between early formation and post-corporate strengths (26:11) Being closer to the edge: solopreneurship vs. corporate safety (29:02) Why corporate stability is more illusion than reality (30:04) What's next: AI, small business leverage, and future chapters (31:41) Closing thoughts and thanks Guest bios Adrian McKenzie helped transform and build Snowflake Software alongside Alex Brooker and Oli Deakin before moving into leadership and team performance work, built around the principle of being kind rather than nice. Oli Deakin was also part of the leadership team as CTO at Snowflake Software (in its second life) and now advises technology leaders on building longer term technology strategy, helping heads of tech and CTOs connect day to day decisions to a three to five year vision. 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 also invests in early-stage technology ventures.
#29
August 3 · 55 min
An Airline Is Just a Software Stack Nobody Finished Building
PLAY Airlines went from zero to $350 million in revenue in three years, did nearly everything right by its former CEO's account, and still went bankrupt — because in aviation, fuel price doesn't care about your execution. Birgir Jónsson is the former CEO of PLAY Airlines, former deputy CEO of WOW air, former CEO of Iceland Express, and previously led a turnaround at Iceland's postal service. In this conversation he breaks down why aviation resists new talent, why airline technology is far less standardized than outsiders assume, and what actually happened when fuel prices upended PLAY's business model after the invasion of Ukraine. What You'll Learn Closed industry: Aviation is a tight-knit, self-referential community that makes it structurally hard for outside talent to break in and stay. Culture split: Airlines run two cultures at once — crew and office — with different metrics, incentives, and worldviews, which makes company-wide alignment unusually hard. Standardization gap: Selling an airline seat looks like a solved e-commerce problem from the outside, but every new airline has to build its distribution and inventory stack from scratch. Fuel exposure: A single input cost — fuel — can erase the value of near-perfect operational execution within weeks. Hub model risk: PLAY's Iceland-as-a-hub strategy between Europe and the US stopped working once new aircraft types and geopolitical shocks shifted capacity onto direct Atlantic routes. Manager gap: Fast-scaling companies routinely promote technical experts into management roles without training them for the different skillset leadership actually requires. AI reality check: AI's near-term value in aviation is internal — helping new hires and cross-functional teams make sense of complex, fragmented data — more than customer-facing booking automation. Founder takeaway: The durable money in aviation tech has historically gone to companies solving infrastructure problems, not to the airlines themselves. Time-Stamped Highlights (00:00) Introduction: an airline CEO joins the show for the first time (01:17) Twenty years in and out of Icelandic aviation (02:36) The "outsider's perspective" and why aviation resists new blood (04:19) Crew vs. office: the divided culture inside every airline (08:15) Building PLAY out of WOW air's DNA, during the pandemic (10:56) Why an airline is really an unfinished software stack (14:07) Negotiating distribution deals in a "very old school" industry (18:16) Legacy vs. new: why a five-year-old airline already has legacy debt (19:50) PLAY's bankruptcy and the fuel price that broke the model (21:30) Private equity, EasyJet, and why aviation takes business personally (29:02) Why the Iceland hub strategy stopped working (35:38) Scaling from zero to $350 million: growing pains and manager training (46:57) Where AI actually helps in aviation today (53:46) Closing advice for founders building in travel tech Guest bio Birgir Jónsson is the former CEO of PLAY Airlines, where he led the Icelandic low-cost carrier from launch through rapid growth to roughly $350 million in annual revenue. He previously served as deputy CEO of WOW air, CEO of Iceland Express, and led a turnaround at Iceland's postal service, and has also worked in medical equipment and printing. LinkedIn: https://www.linkedin.com/in/biggijonsson/ 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 in regulated environments. 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/
#28
July 28 · 15 min
Nobody Would Fund a Human for This
Four founders who have never met each other all built the same tool for the same reason: a phone call that no human team could ever be funded to make. This is the first episode in a new series pulling together ideas that surfaced independently across separate conversations with founders and operators. Host Alex Brooker features Mike Putnam (Custom Travel Solutions / reconfirm.ai), Anne Marie Pellerin (airport operations and security), Yagub Rahimov (call center AI infrastructure), and Fred Bean (Hotel Port), each making the case for AI-driven phone calling from a different corner of the travel and aviation industry. What You'll Learn The reconfirmation gap: Roughly two in every hundred hotel reservations get lost between the booking channel and the property, and the traveler usually finds out at the front desk. Hotel switches and data loss: Distribution tools like travel gateways and hub systems make shopping easier for consumers but create more points where a confirmed booking can quietly disappear. Voice as an audit layer: In airport maintenance operations, AI-driven calls to service engineers can capture and structure information that would otherwise stay fragmented across frontline paper logs, call center software, IT systems, and vendor platforms. The data orchestration bottleneck: Predictive analytics in airport maintenance is blocked less by AI capability and more by the absence of one unified, high-quality data set across all the systems involved. The unit economics case: Processing a single call for transcription and analysis can cost 5 to 10 cents while saving an organization roughly $200 in support time, which is what makes the business case close on its own. Privacy-by-architecture: A gateway approach can anonymize call data before it reaches an LLM, using a single base URL swap rather than a full architectural rebuild. The human off-ramp requirement: Voice AI adoption depends on giving customers a fast, obvious route to a human when they don't want to talk to a machine. Text over voice, long-term: At least one founder in the space expects text and messaging channels to eventually overtake voice as the dominant interface for these interactions. Time-Stamped Highlights (00:00) Introduction: a new series built from ideas raised independently (00:27) Framing the theme: AI phone calling as the through-line (01:10) The traveler's worst moment: a booking that isn't there at check-in (02:00) Mike Putnam on the hotel switch problem and lost reservations (03:22) Inside reconfirm.ai: how the reconfirmation call actually works (04:24) Why the labor cost alone rules out a human doing this job (04:36) Shifting to aviation: Anne Marie Pellerin on equipment failure at 2am (05:16) The failure engine: building a smarter picture of equipment breakdowns (06:09) The real blocker for predictive analytics: no unified data set (08:17) Yagub Rahimov on a call center processing hundreds of thousands of calls daily (10:05) The gateway approach: anonymizing data with a one-line code change (11:38) The cents-versus-hundreds math behind the ROI (13:00) Fred Bean makes the case against voice: the "are you a human" problem (13:16) Why a human off-ramp is non-negotiable for adoption (13:58) The case for text and messaging overtaking voice long-term (14:06) Closing: four founders, one convergent idea, and what's next in the series Guest bios Mike Putnam is the founder of Custom Travel Solutions and built reconfirm.ai, a service that uses AI-driven phone calls to verify hotel bookings directly with properties before guests arrive. Anne Marie Pellerin works in airport operations and security, where she has integrated AI into a failure engine that analyzes equipment breakdowns and automates service-engineer notification calls. Yagub Rahimov works with call center infrastructure at scale, building gateway-based AI systems that anonymize customer data before it reaches a language model for processing. Fred Bean is the founder of Hotel Port and offers a counterpoint on voice AI adoption, arguing that human off-ramps and text-based channels will ultimately matter more than voice alone. 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, helping organizations build and test AI agents in regulated environments. He previously built and scaled complex software in aviation and safety-critical domains, and now invests in early-stage technology ventures while advocating for thoughtful, real-world AI deployment.
#27
July 22 · 1 hr 13 min
Fly First, Regulate Later: Why Europe's Rules Are Pushing Drones Abroad
Two women who've collectively worked nearly every job aviation has to offer sit down to explain why Europe keeps writing the rulebook before anyone's allowed to fly. Julie Garland, CEO of Avtrain and president of the Joint European Drone Associations, and Sarah Owen, VP for Europe Travel and Transportation at Sutherland and chair of the Aviation Club of the UK, join host Alex Brooker for the podcast's first in-person recording, held in London. The conversation covers unconventional career paths through aviation, the regulatory gap between Europe and the US/China on drones and AI, the persistent gender imbalance across pilots, engineers, and the drone sector, and where AI is (and isn't yet) delivering results in flight operations. What You'll Learn Career sequencing: Julie moved through roughly ten-year blocks in engineering, flying, and law before founding a drone training company, treating each stage as a deliberate step rather than a single fixed path. Regulatory sequencing: Europe tends to regulate a technology before it has been operated at scale, while the US and China let operators fly first and shape rules from what they learn. Drone scalability barriers: Missing planning, noise, and airspace-access frameworks — not the drones themselves — are why some European drone delivery operators are concentrating expansion in the US, UK, and UAE instead. AI in flight operations: Tools like OptiFlight already use AI to rebalance horizontal and vertical thrust during climb, cutting fuel burn by roughly 5-6% on that phase of flight. Data silos as the real bottleneck: Airports, ground handlers, and airlines often each hold separate slices of operational data, and commercial incentives actively work against sharing it. Safety reporting culture in drones: Unlike commercial aviation's decades-old just culture of non-punitive incident reporting, the drone industry is only now being pushed toward mandated reporting that would let it prove real safety performance. Gender representation stalled: Female representation across pilots, air traffic controllers, and maintenance sits around 5%, with maintenance specifically closer to 2-2.5%, despite lower technical barriers to entry than in the past. Boeing versus Airbus as a cautionary tale: Slower, more conservative adoption of forward-looking technology is framed as a contributing factor in Boeing's more difficult recent stretch relative to Airbus. Time-Stamped Highlights (00:00) Cold open and guest introductions (02:59) Origin stories: how Julie and Sarah each got into aviation (08:22) The last ten days: a week in the life of a drone regulator and an industry chair (10:13) Interviewing Willie Walsh and the Aviation Club dinner (12:55) Ireland's outsized role in global aircraft leasing (16:06) Career challenges: being a female apprentice on the hangar floor in the 1990s (19:10) Mentors who shaped each guest's path (28:51) Imposter syndrome, hesitancy, and why women apply for roles differently than men (36:09) The stalled numbers: gender statistics across pilots, ATC, and maintenance (38:09) Apprenticeship snobbery and the skills pipeline problem (42:52) Tech culture versus aviation culture on diversity enforcement (46:29) The future is already here: multimodal transport, drone deliveries, and the "three Ds" (52:55) AI in practice: OptiFlight, turnaround optimization, and the data-sharing problem (54:40) Regulate-then-operate versus operate-then-regulate: Europe vs the US and China (1:06:00) Building a just culture and mandated reporting in the drone industry (1:09:37) Closing advice for young people considering an aviation career Guest bio Julie Garland is CEO of Avtrain, Europe's leading drone training and certification body, and president of the Joint European Drone Associations. She began her career as an aircraft maintenance engineer with Aer Lingus, went on to fly as a commercial captain and type-rating instructor, and later qualified as a barrister specializing in aviation law before moving into drone regulation. She also serves on the JARUS industry stakeholder group. Company: avtrain.aero · LinkedIn: linkedin.com/in/julie-garland-87925b25 Sarah Owen is VP for Europe Travel and Transportation at Sutherland, chairs the Aviation Club of the UK Forum, and sits on the Council of the Royal Aeronautical Society. She has held senior roles at Google, Salesforce, and Cyient, and led commercial strategy at Assaia, a computer vision company focused on aircraft turnaround. Company: sutherlandglobal.com · LinkedIn: linkedin.com/in/sarah-owen-mraes-38b26b20 · Also referenced: aviationclub.org.uk 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, helping organizations build and test AI agents in regulated environments. Before founding Airside Labs, he built and scaled complex software in aviation and safety-critical domains. LinkedIn: linkedin.com/in/alex-brooker-2280002
#26
July 8 · 1 hr 4 min
The Real AI Bottleneck in Travel Content Is Copyright, Not Hallucination
Everyone's worried about AI hallucinating travel content. Íñigo Valenzuela says the real problem is that you can't get sued for a hallucination, but you can get fined for a photo. Íñigo Valenzuela is the founder of Smartvel, a travel content and traveler-support data company working with airlines, cruise lines, and OTAs including Iberia, Delta, and MSC. The conversation covers Smartvel's pivot from destination content to COVID travel restriction tracking, the operational complexity of cruise line documentation requirements, and why AI-generated content struggles with image licensing and the long tail. What You'll Learn COVID pivot: Smartvel repurposed its museum-event web-crawling technology to track changing COVID travel restrictions in near real time for airlines like Iberia and Delta. Cruise complexity: Vaccination and visa requirements on a cruise can depend on the order of ports visited, not just the destinations themselves. Information design: Smartvel's product philosophy is to show travelers only the rules that apply to their specific nationality, age, and itinerary, not the full rule set. AI competition: Valenzuela argues destination content for individual queries is now free and unwinnable, so Smartvel focuses upstream on inspiration and conversion instead. Token economics: Heavily subsidized AI token costs are a temporary condition, and pricing normalization could reshape which AI travel products remain viable. Image licensing: AI-generated destination images can't be used commercially without IP rights, and AI-generated images are unreliable for anywhere that isn't a famous landmark. Market structure: New AI-native travel apps face a distribution problem, since building the product is now nearly free but earning customer awareness against Booking or Expedia isn't. Dynamic pricing: Valenzuela expects personalized pricing based on inferred willingness-to-pay to become more common and views it as a real risk to price transparency for travelers. Time-Stamped Highlights 01:16 - How Íñigo got into travel as a coach-business trainee 03:26 - Smartvel's original idea: monetizing destination event content 05:18 - The COVID pivot and the call from Iberia 07:46 - Scaling from 5 destinations to Delta, United, and Ryanair 13:19 - Why cruise vaccination rules depend on port order 19:12 - Inside the customer journey: white-labeling for cruise lines 21:32 - The travel pets problem and per-airline, per-breed rules 26:03 - AI itinerary planners vs. Smartvel's upper-funnel positioning 30:30 - Why long tail content only works for big travel brands 35:57 - TikTok, Instagram, and the unsolved influencer-to-booking gap 40:53 - Why trip planners for end users won't succeed 48:20 - Airport apps: which ones are actually indispensable 55:50 - The picture licensing problem, explained simply 58:07 - The future of bundled travel and personalized pricing risk Guest bio Íñigo Valenzuela is the founder of Smartvel, a travel content and traveler-support platform serving airlines, airports, cruise lines, and OTAs worldwide. He previously held C-level roles in the coach, travel agency, and business travel industries before founding Smartvel 13 years ago. Company: https://www.smartvel.com/ | LinkedIn: https://www.linkedin.com/in/inigovalenzuela/ 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. Host bio Alex Brooker is the founder of Airside Labs, an AI business applying aviation-grade testing and compliance rigor to enterprise AI systems. He previously built and scaled complex software in aviation and safety-critical domains, and now invests in early-stage technology ventures.
#25
June 30 · 51 min
Travel Inspiration Lives on TikTok. The Booking Still Lives in 47 Browser Tabs.
Every billion pieces of travel content on TikTok and Instagram ends in a dead end. Boop is building the call to action that has been missing the whole time. Nancy Li Smith is the CEO and founder of Boop, a social travel platform that lets users generate bookable itineraries from their camera roll and share them with friends who can copy, personalize, and book from them directly. This conversation covers how Boop uses on-device AI to extract trip data from photo metadata, how a 50/50 affiliate commission split rewards itinerary creators, and why Nancy believes trust between real people will consistently outperform AI-generated recommendations built on anonymous internet data. What You'll Learn Social discovery vs. booking infrastructure: 89% of Gen Z travelers already discover destinations on TikTok and Instagram, but the transaction layer remains a disconnected, multi-tab booking experience that captures intent far too late. On-device AI for privacy: Boop processes photo metadata locally on the user's device, extracting location and trip structure without uploading the camera roll to external servers. The trust graph as a product moat: An AI recommendation grounded in a real friend's verified experience consistently outperforms a general-purpose LLM recommendation because it eliminates the need for the user to evaluate the source. Creator commission mechanics: Boop generates affiliate links automatically across hotel, experience, and activity providers, splitting commissions 50/50 between the platform and the original itinerary creator. Long tail outperforms celebrity: The most-copied trips on Boop are not from large influencers. A Chicago-based flight attendant's eight-day Japan itinerary and an Amsterdam local's guide during the Beyonce tour both outperformed influencer-produced content. The experience economy gap: 80% of experience providers globally are not bookable online. The activity market captures only around 20% of actual experience bookings, and Boop sees that as a primary expansion surface. Frequency signal from data: 50% of trips booked through Boop are four days or fewer, suggesting the platform is activating weekend and micro-trip behavior rather than just annual vacation planning. Network formation without explicit tools: Without building dedicated group-coordination features, Boop already sees users naturally sharing itineraries into WhatsApp groups for pre-trip alignment before anyone books a flight. Time-Stamped Highlights (00:00) Introduction and sponsor (00:32) Nancy's background: Meta Ray-Ban glasses, augmented reality, and the path to travel (02:37) The Venice honeymoon moment that sparked Boop (04:51) Live demo: turning a camera roll into a bookable itinerary (07:55) The BootBesties creator network and the 50/50 commission model (10:44) Balancing influencer reach with the long tail of authentic local trips (13:24) Privacy architecture and on-device AI (17:12) How Boop's AI agent uses the social trust graph versus generic LLMs (21:22) Agentic universal cart: booking hotels, experiences, and niche local providers in one transaction (23:46) The shift from search to social in travel distribution (27:00) Brand strategy: Heineken, sports clubs, and fan-generated itinerary libraries (36:01) Growth metrics: 50% week-over-week growth, doubling users every two weeks (48:49) Founding advice and the community-first approach to building a startup Guest bio Nancy Li Smith is the CEO and founder of Boop, a social travel platform based in Seattle. She previously led the AI platform behind the Meta Ray-Ban glasses, held CPO roles in enterprise AI, and ran global perception AI and augmented reality partnerships at Microsoft. LinkedIn: linkedin.com/in/nancyliseattle | Company: boopwithme.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. He also invests in early-stage technology ventures and advocates for disciplined, real-world AI deployment. LinkedIn: linkedin.com/in/alex-brooker-2280002
#24
June 22 · 56 min
Computer Says No: Why Airlines Won't Take Your Upgrade Money
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/
#23
June 15 · 1 hr 3 min
96% Human Error: Why AI Security Starts with the Human, Not the Model
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/
#22
June 8 · 54 min
You Can't Vibe Code a Tour Operator
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/
#21
June 2 · 48 min
The New Olive: How GLP-1 Drugs Could Save Airlines $580M
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/
#20
May 25 · 17 min
Vibe Booking: Hotel data Is Not AI Ready. Here's Why
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
#19
May 19 · 49 min
The Day We Killed the Date Picker
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/
#18
May 12 · 48 min
50 Years of tech debt, AI enters the chat
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 tkVDKZ6VNIo9a6ml0xrc
#17
May 5 · 58 min
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 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.
#16
April 28 · 30 min
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 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.
#15
April 21 · 34 min
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 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.
#14
April 13 · 48 min
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 2035 Guest Kraettli L. Epperson — Co-Founder and CEO, Vigilant Aerospace Kraettli 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 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.

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