Not all moats survive. This edition is about the things that do: the market you've actually earned the right to claim, the network that gets harder to leave with every new user, the distribution that agents can't commoditize overnight. And the invisible tax that founders pay to build any of it.

1. A small ask

A small ask. The Travel Tech Essentialist Copilot has had 400+ conversations since I launched it a few weeks ago. I have no idea what they’re about. ChatGPT doesn’t give me that data.

So I’m asking directly. If you tried it, I’d love to know two things: what problem you were trying to solve and whether it actually helped. One sentence or ten, whatever feels right. Just hit reply.

I built it for travel founders and operators. The only way I know if it’s working is if you tell me.

2. The TAM slide that fools nobody

Pear VC’s Pepe Agell breaks down what early-stage investors want to see. A relevant point for travel founders is that bottom-up market sizing beats top-down every time.

Travel founders are especially guilty of the “$1.5T global travel bookings” slide. It signals to investors you haven’t thought carefully about your customer or your path to them. A bottom-up number, customers you can plausibly reach multiplied by what they’ll actually pay, tells investors you understand your business. The trillion-dollar figure tells them you read Statista.

His traction framework also changes by stage. Pre-seed, you’re validating the idea. Seed, you need a handful of people obsessed with your product. Founders often confuse “we have hotel partnerships” with product love. Those aren’t the same thing.

3. The invisible tax

I shared a version of this on LinkedIn last week and it resonated, so I’m expanding it here with something I left out.

When you work at Google, McKinsey, or Booking.com, doors open, emails get answered, and people take your calls. Most of the time, it’s the logo. A borrowed coat. Entrepreneurs don’t have that. Every door you open, you open yourself. Every email that gets answered, you earned. No tailwind, no borrowed credibility. That’s the invisible tax.

I co-founded eDreams in 1999, served as CMO and a board member, and remained with the company for 15 years through our IPO. We felt it from day one. In Barcelona, convincing local talent to join an unknown startup was harder than recruiting people from Australia, Israel, or the US. Airlines and travel providers barely answered our calls. Every meeting we got, we fought for.

The tax doesn’t disappear when you build something real. It reappears the moment you step outside your context. When I moved to the San Francisco Bay Area in 2015, nobody had heard of eDreams, a European company that didn’t register on the Valley’s radar. Same person, same track record, different country code.

So if you’re sitting inside one of those institutions right now, here’s a small ask: reply to that founder’s email. Take that meeting. Make that intro. It costs you almost nothing. For them, it might change everything. You also never know how quickly the roles flip.

And if you’re the founder paying the tax…it’s real, it’s not just you, and almost nobody talks about it. But it’s also temporary. You’re building your own coat, one relationship at a time. Eventually, it feels better than a borrowed coat ever did.

4. Sell the work

Many AI companies are building tools that make agents, revenue managers, and ops teams more productive. That’s the copilot model: AI in the hands of a professional, making them faster and sharper. The autopilot model is different. Instead of selling the tool, you sell the work. The customer buys the outcome directly.

Julien Bek from Sequoia argues that the companies that win in the long term will be autopilots. Read + Sequoia

Travel already has the conditions for autopilots to take hold. Insurance distribution, revenue management, customer service at scale…these are areas where a significant share of the underlying work is rules-based and already handled by outside providers.

Bek's key insight is to start where outsourcing already exists. If a task is already done externally, the budget line exists, the buyer expects an outside provider, and replacing a vendor is far easier than replacing headcount. For every dollar spent on software, six are spent on services. Autopilots go after the six.

The wedge in travel could be in TMC contracts, outsourced revenue management retainers, distribution agreements with brokers, etc… Each one has a budget line, an incumbent doing repetitive work, and a buyer already comfortable with an outside provider.

The long-term question for travel AI founders has shifted from “What tool can I build?” to “What work can I own?” That’s where the real opportunity sits.

5. Agents will eat your App, but they can’t eat your network

Slow Ventures’ Yoni Rechtman makes a distinction easy to miss. Aggregation is collecting options in one place. Useful, but it doesn’t trap anyone. Users can leave anytime, and an agent can replicate it overnight. Network effects are different. The more people use the product, the better it gets, and the harder it becomes to walk away from. As Yoni puts it: “Aggregation creates value. Network effects capture it.“ Read + Yoni Rechtman

Agent can scan flights, hotels, and experiences across the web in seconds. If your value is “we have everything in one place,” an agent can and will replicate that. What agents can’t replicate is a genuine network. A platform where hosts and guests build reputations, or a marketplace where reviews compound over time.

Many travel startups are building a list. A curated set of suppliers, experiences, or options. That was a defensible business when search and discovery was hard, but it’s a much weaker one when search is free and instant.

Take solo travel startups. Flash Pack, for instance, has leaned into the community layer: alumni groups, repeat travelers, a sense of belonging that outlasts the trip. Each returning traveler makes the product better for the next one. That’s a network. A startup that plans great trips for strangers, but where most people do one trip and move on, has a compelling brand and curation. But the value is in logistics and taste, not in a compounding community. One is agent-proof, the other is not yet.

Before your next product decision, ask whether adding one more user makes the product better for every other user. If the answer is no, you’re building aggregation. It’s not a death sentence, but you should know which game you’re playing.

6. Agents in the wild

Anthropic published a detailed study on how AI agents are being used in practice. Software engineering accounts for nearly 50% of all agentic activity. Travel ranks last at 0.8%. Read + Anthropic

That gap has less to do with how sophisticated travel operators are and more to do with what’s at stake when something goes wrong. Most agent activity today happens in domains where mistakes are assumed to be detectable and reversible, though even that assumption is being tested (Amazon recently had a nearly six-hour site disruption tied to AI-related issues). In travel, the consequences land harder. A bad booking propagates into real-world logistics…wrong hotel, missed transfer, ruined trip. The adoption curve will likely follow that risk gradient: research and price monitoring first, supervised booking next, and fully autonomous transactions once accountability structures are in place to support them.

It’s also worth questioning the 0.8% figure itself. Travel is less absent from the agent data than it appears. Software engineering includes the PMS, RMS, booking engine systems, back office automation, CRM, marketing tools that run this industry and that travel operators use daily. BCG reports that 37% of travelers already use AI embedded in online travel sites to plan and book trips, and AI-driven pricing has delivered upward of 15% RevPAR growth at some hotels. Travel’s AI activity is real. It’s just being counted in someone else’s column.

7. Selling to agents

One of the most important questions for founders is how to make sure agents know about their product/service and choose it? All the old tricks won’t work.

Brian Flynn makes the argument that AI agents don’t browse; they query. They have no brand loyalty, they are not driven by impulse and not subjected to the attention economy. They simply focus on: can you solve my problem, how fast, how much, how reliably? What matters for that is your API.

In one sweep across 44 agent services, only 2 had fully working endpoints. 53% of direct service calls succeeded. Flynn’s conclusion is that, in agent commerce reliability is the entire product. Read + Brian Flynn

For travel, this reframes the distribution question. The industry spent decades mastering human-facing distribution: search ads, metasearch rankings, OTA placement, landing page optimization. Machine buyers don’t respond to that. A hotel, airline, or activity provider that wants to be visible to AI agents needs machine-readable capabilities, protocol-based pricing, and provable reliability scores.

8. The Personalization shortcut

Hotels have spent years and enormous sums trying to crack personalization: loyalty programs, CRM platforms, tracking pixels, third-party data partnerships. Most still can’t do it effectively. The data flywheel that powers Amazon doesn’t have the same physics in hospitality. A loyal guest stays twice a year, and that’s not enough of a signal.

On this post, Gautam Lulla makes a sharp observation. A generative hotel website (one that responds dynamically to what each visitor asks rather than serving static pages waiting to be browsed), short-circuits the entire problem. The site assembles content around the guest’s specific question in real time. No behavioral profile required and no prior data needed. The guest’s intent replaces years of accumulated data.

The same content architecture that powers this also makes a hotel visible and accurately represented to AI agents, the next distribution surface.

9. Algorithmic relevance

BCG zooms out on the same problem. Brand equity in hospitality is shifting from name recognition to algorithmic relevance. In an AI-driven discovery environment, a hotel that can't be read and confidently recommended by an AI agent won't appear in the results at all. It’s not a problem of being ranked lower or being penalized or paying too high of a commission. The problem is being absent.

The mechanics matter. AI engines favor properties with comprehensive, high-trust, multisource content. Guest reviews, syndication across authoritative platforms, consistent digital presence: these become core commercial levers. Sparse or inconsistent footprints get filtered out.

The industry spent two decades figuring out their complex relationship with OTAs. This is the same battle, with higher stakes and less time to prepare. Read + BCG AI-First Hotels

10. Travel’s search dependency

Travel puts more of its ad budget into search than many other consumer categories.

The harder question is what happens in a world where AI agents make recommendations that ad spend doesn’t directly influence.

According to this BCG report, only 10% of travel executives outside the CMO role have prior marketing experience, compared to 40% in other consumer industries. BCG flags the stat without drawing the conclusion, but it’s hard not to. When the people approving the budget lack marketing instincts, long-term brand building loses to short-term performance marketing every time.

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Mauricio Prieto