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Planning Bike Rides with AI: How Claude Creates a Complete Route Plan in Just a Few Minutes

*Thisarticle is based on a YouTube video by Sophie Hundertmark, an expert in the use of artificial intelligence with a focus on chatbots and strategic AI applications in companies and public institutions. Sophie is a researcher and lecturer at the Lucerne University of Applied Sciences and Arts and is doing her doctorate in Conversational AI at the University of Fribourg. The blog text was created using a custom GPT model that was trained on Sophie’s video content, language style and expertise. The result is well-founded, up-to-date articles based on Sophie Hundertmark‘s own expertise.

You can find the link to the video at the end of this article.


Planning a bike trip can take a lot of time. Researching routes, finding suitable starting points, checking gradients, and then compiling everything into a clear and concise guide—this often involves much more effort than one might initially think.

In my latest test, I therefore set out to see how well the AI Claude works for planning a bike ride. The result surprised me: Within a few minutes, I received several suitable route suggestions, including detailed information and ready-to-use Google Maps links.

The starting point: A bike ride around Lake Como

I already had a few ideas in mind for my next bike ride:

  • Traveling to Como by Train and Bicycle
  • Bike ride along Lake Como
  • Route length between 50 and 60 kilometers
  • Paved paths whenever possible, rather than unpaved ones
  • Few hills and routes that are as flat as possible
  • Suitable for a trip with my father

I described these requirements to Claude in a simple prompt. There were even a few typos—but that wasn’t a problem for the AI.

A simple request results in five specific tour suggestions

After I sent my request, Claude immediately generated five different route suggestions that were already a very good fit for my specifications.

What was particularly interesting was that the AI didn’t just provide general ideas, but suggested specific tours with clear itineraries. This allowed me to quickly get an overview and compare different options.

AI systems offer a major advantage, especially when it comes to leisure activities like bike tours: instead of spending hours researching on your own, you can get several options in just a few seconds that can serve as a starting point for further planning.

Refine adjustments by asking questions

As with many AI applications, the best results often don’t come from the first prompt, but from follow-up questions.

In my case, it was important to me that the tours start right at the Como San Giovanni train station. After I added this requirement, Claude adjusted all the proposals accordingly.

After that, I made a few minor changes to the content. The AI was able to easily revise the existing route suggestions and adapt them to the new requirements.

This approach clearly demonstrates how AI can be used as an interactive planning assistant: rather than starting from scratch, existing results are optimized step by step.

Automatically generated Word document containing all the information

I was particularly impressed by the next feature.

Once the route planning was complete, I asked Claude to compile all the information into a Word document. The AI then immediately made a document available for download.

This included:

  • The five planned bike routes
  • The updated versions based on my changes
  • Clearly organized information about each tour
  • Map sections for orientation
  • Links to the respective map views

This resulted in a complete set of planning documents in no time at all, which I was able to save immediately and use later.

Google Maps links directly integrated

Another highlight was the automatically embedded Google Maps links.

The links led directly to the suggested routes. The relevant locations had already been saved there, and the bike route setting was enabled.

This offers several advantages:

  • Instant route visualization
  • Review of the route
  • Adjust individual sections as needed
  • Tracking travel times and distances
  • Additional navigation directly via Google Maps

This turns the AI output not just into a collection of ideas, but into a planning tool that can be used right away.

Why the result surprised me

Up until now, I’ve usually planned my bike trips myself.

For one thing, because I wanted to stay in control of the route. On the other hand, because planning is often part of the excitement leading up to the trip.

However, the test with Claude has shown just how much AI can now assist with such tasks. What was particularly impressive was not just the speed, but the combination of:

  • Custom route planning
  • Taking personal needs into account
  • Automated document generation
  • Integration of map services
  • Option for direct further processing

Within minutes, we had a result that would normally have taken much longer to produce.

AI as a travel and leisure planner

The example of the bike ride shows that AI is no longer limited to professional tasks.

There are also numerous applications in the realm of leisure activities:

  • Plan bike rides
  • Planning Hikes
  • Plan city trips
  • Plan trips
  • Plan road trips
  • Create daily schedules
  • Researching tourist attractions

The more precisely the requirements are defined, the better modern AI systems can provide suitable suggestions.

Conclusion

Planning my bike trip around Lake Como showed just how powerful modern AI tools have become. Claude was able to come up with several suitable route suggestions in no time, adjust them based on my feedback, and then even provide a complete Word document that included links to maps.

In particular, the integration with Google Maps makes the results immediately usable and saves a great deal of the research work that would otherwise be required.

Anyone planning their next bike ride, hike, or trip should definitely give AI a try to see how it can help with the preparations. The results can not only save time, but often also lead to new ideas that you might have overlooked during your own research.

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