Just exploring AI trip planners — need some product advice

Questions
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Hello everyone,

I recently heard about AI trip planners, so out of curiosity I searched and checked a few of them. One platform I came across was SearchSpot, and I personally liked it the most. It’s not perfect and definitely has flaws, but it made me feel that this kind of product can be built much better.

This got me interested in understanding what actually goes behind building something like this. On the surface it looks simple, but I’m sure there are many challenges once you start working on it seriously.

I come from a product background, so I want to understand things from a practical point of view.

I’d really like to know:

  • What are the main challenges in building an AI-based trip planner?

  • Where do such products usually fail — data, workflows, UX, or costs?

  • What should a good MVP look like?

  • If someone is using tools like n8n, what parts should be kept simple in the beginning?

I’m still exploring and learning, so any advice or real-world experience would be really helpful.

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Hey @techy_Mandavi! Welcome to the n8n community here’s a quick practical view from real-world travel/AI product experience:

Main challenges
• Getting reliable, real-time travel data and combining many APIs well.
• Making AI understand user intent and preferences accurately.
• Handling changes like delays or weather and updating plans.

Where products usually fail
• Data quality or stale info leads to bad plans.
• Complex UX that overwhelms users.
• Costs and maintenance of APIs/AI models.

Good MVP
• Simple input (where, when, interests, budget).
• AI generates itinerary + key suggestions.
• No deep booking flows yet.

If you’re using n8n
• Keep it basic: collect user input → call AI → show itinerary.
• Add a couple of reliable APIs (weather, basic pricing) later.
• Skip advanced bookings/real-time updates at first.