Agentic AI is quickly becoming the difference between a travel experience that feels generic and one that adapts to you in real time. In the final episode of our Agentic AI Series, Dan sits down with three builders deep in the work: Jeff Kischuk, CEO of Tripian, Jessie Fischer, Founder and CEO of GuestOS, and Marius Nigond, CEO of iWander. Together, they break down what “agentic” really means for travel in 2026, AI that can make decisions, not just generate content, and the infrastructure required to make it work reliably and at scale.

We get into tangible use cases you can immediately picture, from iWander creating dynamic, in-destination audio tours and recommendations, to GuestOS running hotel phone lines with AI teammates that capture conversations and turn guest needs into action. We also explore Tripian’s role as the critical data layer, structuring and connecting travel data so AI agents can deliver relevant, contextual, and dependable experiences. For anyone in tours and activities, hospitality tech, or travel startups, this conversation shows how agentic AI can reduce friction while still preserving what travelers value most, meaningful human moments.

Filters, dropdowns, and endless tabs are starting to feel like the old internet, and travel is right at the center of that shift. In the second episode of our Agentic AI Series, Dan speaks with Ben Manzi, Co-founder and COO of Maya, Michelle Denogean, CMO of Mindtrip, and Brianna MacNeil, Director of AI Products and Personalization, TravelAI, to unpack what “agentic AI” really means for both travel companies and travelers, especially now that AI agents can do far more than chat. They can pull real-time pricing, generate quotes, draft emails, build itineraries, and increasingly help solve the hardest part of travel, making decisions.

We get concrete on where the value shows up first, eliminating repetitive, low judgment work across email and messaging, accelerating internal workflows, and helping smaller travel brands punch above their weight. We also dig into what needs to go right for trust, including grounding agents in real data, cleaning up outdated content, and selecting the right models so costs and latency stay under control. For destinations and marketers, we explore the emergence of a new “listening layer” within conversational planning, and why AI SEO and generative engine optimization now depend on answering real traveler questions, not just publishing evergreen content.

AI that writes is no longer the headline. AI that acts is.

In the first episode of our Agentic AI Series, Dan sits down with Gilad Berenstein of Brook Bay Capital, Tahnee Perry, AI Expert Consultant, and Christian Watts of Magpie to break down agentic AI in plain terms. We unpack how it differs from generative AI, and why this next phase is less about single tools and more about systems of agents that can take real action across your workflows, data, and operations.

We also get candid about what this shift means for the travel industry right now. Gilad explains how agentic AI is reshaping startup economics, where technical moats are shrinking and advantages are shifting toward trust, distribution, customer lock in, and proprietary data. Christian challenges how travel tech teams think about capability, arguing that leaders need to understand what’s possible with today’s tools, not what was true even a year ago. Tahnee brings it down to reality with practical, field tested use cases, from data analysis and market research to automations that remove friction without losing the human touch.

What happens when your customers stop “visiting” your website because their AI agents visit for them? That’s the future we explore with Dan Flores of Satisfi Labs, who went from helping grow Maverick Helicopters into a tourism powerhouse to pioneering agent-first customer experiences that sell tickets, qualify MICE leads, and streamline service for destinations, attractions, and tours.

We trace Satisfi’s origins in sports starting with the New York Mets and how fan-centric thinking now powers travel use cases. Dan breaks down the shift from simple FAQ chatbots to specialized AI agents with goals, context, and the ability to take action: a theme park agent that finds the closest chicken nuggets and orders ahead, or a destination agent that captures group details, routes leads by territory, and hands sales teams qualified briefs. We also dig into pricing models, build versus buy considerations, and how bespoke solutions graduate into platform-wide features that benefit the entire industry.