By Jim Santos, Wherever We May Roam
If you’ve ever tried to plan a multi-country, multi-city overland trip through Europe, you know the drill. You open fifteen browser tabs. You start a spreadsheet. You cross-reference bus schedules against train schedules against “wait, is this city even worth two nights?” And somewhere around city number six, you close the laptop and pour a drink.
I’ve done this the hard way before. My last complicated multi-stop trip took me days just to build the basic framework — before I’d even gotten to the fun part of figuring out what to actually see once we got there. So when Rita and I started mapping out a 53-night overland journey from Madrid to Hamburg for the spring of 2027, I decided to test whether AI could shortcut the grunt work without sacrificing the substance. Here’s what happened — and what I learned about where the technology genuinely helps versus where you still need to do your own homework.
The Ask
I gave the AI a fairly specific brief:
- Overland only — bus, train, or ferry, no flights
- A hard constraint: no single leg longer than 6.5 hours
- A fixed start and end: Madrid on March 25th, Hamburg by May 17–18
- A fixed sequence of 15 cities across four countries — Madrid, Alicante, Benidorm, Valencia, and Barcelona in Spain; Toulouse, Marseille, Lyon, Paris, and Lille in France; Ghent in Belgium; Rotterdam and Amsterdam in the Netherlands; Bremen and Hamburg in Germany
- Preferred bus carriers (Flixbus and Alsa) where relevant
- A request to intelligently allocate nights per city based on total trip length and what there was to actually do and see there
- And — this was the part I was most curious about — suggestions for smart detours, like a possible day trip to Geneva while based in Lyon
What Came Back
Within minutes, I had a full 53-night framework: a city-by-city sequence with suggested transport routing and approximate travel times for every single leg, a proposed night allocation for each stop (weighted toward the cities that clearly warranted it — Barcelona and Paris got the lion’s share, while Alicante and Bremen got a lighter touch), and for nearly every city, a genuinely useful shortlist of sights, neighborhoods, and local specialties worth building a day around.
The Geneva-from-Lyon idea was handled exactly the way I’d hoped — not just “yes, it’s possible,” but a real comparison: Geneva as a doable day trip versus Annecy as a scenic, arguably more affordable alternative sitting right next door. That’s the kind of lateral suggestion that usually only comes from a well-traveled friend or a good guidebook, not a booking engine.
The local-sights information was, frankly, the most valuable part of the whole exercise. It wasn’t generic “top 10” listicle filler — it flagged specific, useful details: that paella is a lunch dish in Valencia, that Ghent’s altarpiece is arguably a bigger draw than anything in more-famous Bruges next door, that Keukenhof’s tulip season lines up perfectly with an early-May Amsterdam stay. That’s the research grind that normally eats an entire evening per city, condensed into a first draft I could react to instead of build from scratch.
What We Changed
We didn’t take the output as gospel — and you shouldn’t either. We used it as a framework, and then adjusted the time spent in several locations based on our own priorities, pace preferences, and gut instinct about what we actually wanted more or less of. That’s the right way to use a tool like this: as a strong first draft that gets you 80% of the way there, not a finished itinerary you book against blindly.
The Bottom Line
This is an excellent tool for exactly the kind of trip that used to burn entire weekends before you’d booked a single ticket. It compresses the tedious framework-building — sequencing, rough timing, “how many nights does this city deserve” — into minutes, and it surfaces local knowledge that would otherwise take real research to assemble.
But — and this is important — due diligence is still absolutely required before you finalize anything. Travel times were estimates, not live schedules. Ticket booking windows, seasonal opening hours, timed-entry requirements (looking at you, Anne Frank House and Sagrada Família), and actual carrier timetables for 2027 all still need to be verified independently once schedules are released. Treat the AI’s output as a very well-informed starting point, not a booking-ready document. Cross-check every transport connection, confirm every “must book in advance” attraction, and build in buffer time for the inevitable real-world hiccups.
Used this way — as a research accelerator, not an autopilot — AI planning tools are one of the more genuinely useful developments I’ve seen for travelers who like complex, self-guided itineraries. It didn’t replace the planning. It just gave us days back to spend on the parts of planning that are actually enjoyable.
Have you used AI to help plan a trip? Rita and I would love to hear how it worked for you — drop us a note or catch us on the next episode of Wherever We May Roam.
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