Kyle LeMarbe

I recently came back from a 10-day family vacation to Disney and Universal. The trip was exactly what a vacation should be: a lot of walking, a lot of heat, a lot of memories, and very little interest in opening a laptop.

But AI was still involved in a surprising amount of the trip. It helped before we left, supported decisions while we were there, kept my work inbox under control, and helped me get back up to speed quickly when I returned. The most useful AI is not always the flashy kind. Sometimes it is the system that quietly removes friction from a complicated week.

Before the trip: turning scattered information into a plan

The first job was not glamorous. I needed a packing list for a family trip that included both Disney and Universal. The existing notes were spread across older vacation documents, and some were written for a different stage of family life.

AI searched those notes, separated current information from historical leftovers, and helped build a current list for two adults and children ages 7 and 9. It caught details that matter in real life, including that the 7-year-old still needs nighttime pull-ups. It removed baby and toddler items that no longer belonged on the default list and accounted for the Disney dining plan, so the list did not tell us to pack food we would not need.

The result was not just a chat response. The list was written back into my second brain, reviewed, committed, and opened as a pull request. A one-time answer disappears. A maintained note becomes part of the next trip.

Before the trip: connecting the vacation to the calendar

AI added the Universal and Disney trip to the calendar, then kept adding useful details as they arrived. That included the park plans, transportation windows, Mickey’s Not-So-Scary Halloween Party, and information from the house where we stayed.

That preparation gave me a shared operating picture before we left. The trip was not just a collection of reservations and screenshots. The important details were connected and available to the morning briefings that would guide each day.

During the trip: making decisions with the context in front of me

The most useful vacation conversations were grounded in what we were experiencing. Before the trip, AI helped compare the trade-offs between staying in a house and staying at a club-level Disney resort. The house gave our family more space, more bathrooms, less nightly noise, and a lower cost. Staying on property offered convenience, including the ability to return to the room and get back to the parks quickly.

After we experienced both options, AI captured the result in the vacation note. For our family, the house won overall, while the on-property convenience was still a real benefit. That is better than asking for a recommendation once and never telling the system what actually happened.

The same thing happened at Animal Kingdom After Hours. We found that only a few rides were operating and no late shows were running. The experience was okay, and the best part was walking through the park at night. AI recorded that as a future decision rule: do not prioritize the event unless nighttime atmosphere is the main goal or the entertainment lineup is substantially better.

During the trip: keeping work moving without taking over the vacation

I also had separate AI agents running for work. They read incoming email, analyzed what needed attention, and responded according to their configured instructions. Their job was not to make every decision for me. Their job was to keep routine communication moving and make the state of my inbox obvious.

The agents kept my inbox clean while I was away. Anything that still needed to be read remained in my inbox. Anything that needed a response already had a draft ready to go. That gave me a simple boundary between work that had been handled, work that was ready for my approval, and work that still needed my attention.

That changed what being away meant. I did not need to manually monitor every work thread from a theme park, but I also did not lose visibility into the items that mattered. The agents handled the repetitive first pass, while the inbox continued to show me the decisions and messages that required a human response.

During the trip: preserving what we learned

Travel notes are easy to create and easy to abandon. The valuable part was turning observations into future guidance.

AI updated the second-brain vacation note as we learned things. It captured what worked, what did not, and what we would do differently. It also handled the surrounding maintenance work: fixing a mistyped filename, preserving the note in Markdown, committing the changes, and opening pull requests against the main branch.

I could send a quick observation while it was fresh, and the system could turn it into an organized, searchable record. The point was not to document every moment. It was to preserve the decisions that would save us time next time.

After the trip: getting back up to speed quickly

When I got home, I did not have to reconstruct ten days from memory, email, calendar entries, and scattered notes. I could ask what happened while I was gone and receive a useful summary of the trip, the decisions we made, the notes that were updated, and the work that had continued.

That catch-up included the practical vacation takeaways, the state of the second-brain work, and the items that were still in progress. It also made the work transition easier because the inbox agents had already separated handled communication, drafts waiting for approval, and messages that still needed to be read.

The system had not just answered questions. It had maintained context across the vacation and gave me a fast path back into both personal and work responsibilities.

What I learned from using AI on vacation

The biggest lesson was that AI did not need to look like a robot concierge to be valuable. It worked as connective tissue across three phases:

• Before the trip: research, packing, calendar setup, and preparation.
• During the trip: schedule awareness, decision support, work-email handling, and notes that captured what actually happened.
• After returning: a useful catch-up instead of a blank slate.

AI did not go on vacation for me. My family made the memories, walked the parks, chose where to stay, and decided what was worth repeating. AI handled the connective work around those choices, kept routine work moving, and made the return to normal life much easier.

That is the kind of AI I want more of: not a magic trick or an unattended replacement for judgment, but a dependable layer of support that lets people spend more attention on the parts of life and work that actually deserve it.