The AI Tools Actually Making STR Operators Money in 2026 | Ryan Lefebvre

**Ryan Lefebvre** (0:00)
There's a way bigger opportunity in the short term rental world right now than there are in the AI world. But to spend 10, 12 hours a day building AI things that are just going to break or change in the next couple of months, it's a complete waste of time. We're looking for quick wins like owner statements at the end of the month, a comping tool, a comping agent that will go out and find other comps and put together a very nice PDF that you can send over to owners that make you look like you're organized. So the slippage that we've been finding just by having Claude do our bookkeeping just reviewing everything has been a huge lever. The first thing I did was lie to get my first job. I got really good at catching fraud and financial crime. From there, I got bored, went out and got a pilot license and then transition from being in the computer science world all the way into aviation, which is a huge change.

**Mike Reilly** (0:44)
Payroll is typically the biggest expense for property management companies. It's anywhere between 20 and 40 percent of the income. How do we make payroll less and less so that we can be more efficient?

**Ryan Lefebvre** (0:57)
If you don't know that knowledge, you will build and fix for months and months and months, hours and hours and hours. And that's just going to take away all that time that you can be prospecting, growing your business.

**Mike Reilly** (1:06)
A property management company that has 25 listings. What's the first thing that you do to help them with their revenue management?

**Ryan Lefebvre** (1:14)
We install the revenue manager into their ecosystem, which touches on a lot of data points. And then from there, we do a full scan and we take a look at the entire portfolio. We go back from day one when they started and then we try to go back to where their calendar is open until. People have their calendars open 12 months, 18 months, 24 months. Then you do a full scan of the entire portfolio. This also includes visibility through Rampreys or other types of visibility websites, includes your PMS, includes Price Labs, it includes an API to Airbnb, not directly Airbnb, but any provider that provides Airbnb data. So now we're getting a full picture of what your track record is, what your market's doing, what the demand was, and then we're able to take those projections of what happened in the past and start really doing some revenue management in the future. Actually, at our last AI Summit, I had messages from people that had set this up, and they were sending these screenshots of bookings between $8,000 and $12,000 that they've gotten just days after they ran this revenue manager. It's a very simple setup. It's something that you can set up within an hour, and you're getting massive wins right out of the gate.

**Michael Sjogren** (2:15)
Ryan, this is long overdue, buddy. Welcome to the podcast. How are you doing?

**Ryan Lefebvre** (2:20)
Hey, man. I'm doing great. Awesome to be here.
I'm a listener. Very long time listener. First time caller, first podcast altogether. But I do have a nice line up of podcasts coming up in the next few months. So it's a nice little warm up session with a group of people I know. It's awesome.

**Michael Sjogren** (2:32)
I love it, man. Well, for the folks that don't know you, I'll give some quick context. I've known you for a few years now. You've been in the Secrets ecosystem. You guys have been building your management business up in Canada. But I refer to you as my AI Sherpa, based on your background and how good you borrow with a lot of these AI tools. You've been helping me a ton really since the beginning of the year, really get my hands dirty with some AI things. And you've been building some amazing tools for us at Secrets and for a lot of the students. So why don't you give us the 60-second skinny on your background and get us up to speed on where you're at right now, what you're working on.

**Ryan Lefebvre** (3:05)
Yeah, a little 60-second on my background. I started off, I did things a little bit backwards, decided to ditch school at a very young age, went skiing and decided really quick that, hey, school is probably where I need to be. But first thing I did was lie to get my first job. I had no way to get an awesome job. So I lied and I checked the box that said I had an education. Boss hired me. I got really good at catching fraud and financial crime. They boosted me up into management and here I was, working with a bunch of people with degrees. So I did what natural thing would be to do is, went out and got a computer science degree to match up with everybody else. And that just catapulted everything. And from there, I kind of got bored and coding was long. Coding long days and long hours is super long.