Trip Planning with Tana and Tana AI

Trip Planning with Tana to easily create a travel itinerary for any upcoming holiday. In this article and video, I show my process, including a Google Maps trick to visualise it all.

Trip Planning with Tana and Tana AI

Hi Everyone,

This is an article (and video) about Trip Planning with the amazing tool called Tana. It not only is a formidable notetaking tool allowing you to jot your thoughts down or transform your data with different views, but it also gives us so much more. By using Tana and Tana AI, you can easily create a travel itinerary for any upcoming holiday or trip. In this article and video, I will discuss my process, which includes a nifty Google Maps trick so that you can visualise where you are going.

My better half and I have been thinking of going to Lisbon, Portugal, for a long weekend in October but are unsure of what to do and see whilst there. After some head scratching, some YouTube videos where we forgot the places mentioned, or you had to complete an assault course to obtain the names of places, or the lengths of stay (or budget) were completely different to ours, we figured, why not use the new kid on the block, OpenAI's GPT with our notetaking tool, Tana.

By leveraging the power of GPT and Tana, we were able to obtain an itinerary that broadly suited us. This is, of course, just a starting place. We will now study the list in more detail to tailor it to the places we really want to see together with any hints and tips we find along the way.

Ok, great - show me how!

First up is to make sure you have Tana AI enabled (check this video by Ev Chapman to set things up). Next, we create a new node, in our example, we called it "Lisbon Trip Planning", but you can call yours whatever you desire.

We then create a node with the prompt that we want to send to OpenAI API. To do this, we can easily type "AI: " and then our prompt - so something like:

AI: I am planning a 3 day trip to Lisbon in October. Give me an itinerary with places to see and mid-priced places to eat lunch and dinner and briefly describe each place. At the end, summarise in a list the name of the places to see and eat in individual items and do not number the list.

After which, you should see a "Ask AI" button appear. Click on this button. In the above prompt, we are basically:

  1. Setting the scene with the background
  2. Telling GPT what we what it to do - give me an itinerary describing the places suggested.
  3. Summarise in a list the names of the places suggested (you will see why we want this shortly)

Once the information is returned, we can do some light touch formatting, and we are good to go. We have a great itinerary split by day and time period with a suggestion of what to do and eat.

The above is great, but it feels like something is missing - I have no idea where the places are and would rather not have to type them individually in Google Maps. Here comes the kicker, you don't need to.

By obtaining a list of places from the above prompt, we can now import this into a new Google Map to have them appear on a map like the below:

How to do this:

  1. Copy the list returned into an Excel / Google Sheets and save.
  2. Import to Google Maps as a new layer - you may get a couple of prompts.
  3. See the markers on the map. For any places that it did not find, you can manually amend and add a marker.

You can now tweak the map to show all markers, colour the places to see and eat in different colours, amongst other things.

I now like to print screen the map into Tana so that I can have it handy with me. You can also prettify the page to add a banner image (click the node and then ctrl / cmd + k -> Configure Node) and add an image. In the end, you can get something like the following:

There we have it, a nice itinerary in Tana with the use of Tana AI and a quick pit-stop in Google Maps.

Once you visit the place, you can then add your photos under the locations for prosperity.

I hope you found this useful, and if you have any comments, please let me know.

Many thanks for reading / watching.