In this episode of The Same Day Podcast, Yoni Schmidt sits down with John Ledesma, Founder and CEO of LeasIQ and LandClear, to discuss AI-driven real estate efficiency. John explains where automation delivers the strongest ROI, how landlords can streamline leasing and maintenance, and why better systems help small operators compete. He also explores land entitlement intelligence and the future of more human property management.
AI Solutions For Real Estate Efficiency With John Ledesma
John Ledesma is the Founder and CEO of LeasIQ, AI-native property management software for independent landlords, and LandClear, AI-powered entitlement intelligence for land developers and acquisition teams. John leads product strategy, software development, and customer discovery, building systems that automate leasing, maintenance coordination, tenant communication, and repetitive administrative work. Drawing on expertise in engineering, real estate investing, and software, he applies systems thinking to reduce operational friction and support better decisions.
Here’s a glimpse of what you’ll learn:
- [3:05] John Ledesma’s motivation for building smarter tools for independent landlords
- [8:22] How AI can improve efficiency, responsiveness, and day-to-day property operations
- [13:29] John’s perspective on automation, human judgment, and the evolving role of property managers
- [19:37] What to consider before hiring a property manager or investing in better systems
- [24:58] A more organized approach to maintenance, vendor coordination, and tenant communication
- [30:37] John’s insights into using technology to reduce vacancy and support rental revenue
- [36:03] The systems-thinking principles behind building practical real estate technology
- [39:19] Why AI could reshape land development research, due diligence, and risk assessment
- [45:21] What is John’s vision for using AI to simplify workflows and make property management more human?
In this episode…
Property management can become overwhelming when leasing questions, maintenance updates, and follow-ups compete for attention all day. How can technology reduce that workload without replacing the judgment and relationships that matter most?
John Ledesma, an expert in AI-powered real estate operations and software development, believes the answer is to automate repetitive work while keeping people focused on decisions that require experience, empathy, and trust. Faster responses can reduce vacancy, organized maintenance systems can prevent costly delays, and earlier renewal conversations can improve tenant retention. John also recommends improving workflows before adding staff, since better systems often reveal where human expertise creates the greatest value. Used thoughtfully, AI can make operations more efficient while giving landlords greater clarity and control.
Resources mentioned in this episode:
- Yonatan Schmidt on LinkedIn
- Mat Zalk on LinkedIn
- Keyrenter Property Management
- Keyrenter Property Management in Tulsa | Oklahoma City | Arkansas
- Keyrenter Property Management email address: [email protected]
- L John Ledesma on LinkedIn
- LeasIQ: Website | Free Trial | Email
- LandClear
- YouTube Secrets: The Ultimate Guide to Growing Your Following and Making Money as a Video Influencer by Sean Cannell and Benji Travis
Quotable Moments
- “And I think the best technology doesn’t make people feel replaced; it makes them feel more capable.”
- “The AI isn’t sitting off to the side waiting for someone to ask it a question.”
- “Technology should reduce administrative work, and people should focus on the decisions that require experience, judgment, and trust.”
- “Innovation isn’t about building more features; it’s about listening well enough to solve the right problems.”
- “The best systems aren’t the most complicated; they’re the ones where every part has a purpose.”
Action Steps
- Automate repetitive property management tasks first: Removing routine follow-ups, reminders, and tenant questions gives landlords more time for judgment-based work.
- Centralize maintenance requests and communication: Keeping updates, vendor responses, and repair histories together prevents delays and improves tenant trust.
- Respond to leasing inquiries immediately: Faster communication increases the likelihood of securing qualified tenants and reducing costly vacancy periods.
- Start lease renewal conversations early: Proactive outreach gives landlords and tenants more time to decide and helps prevent unnecessary turnover.
- Use AI to surface what needs attention: Clear priorities reduce mental overload, prevent missed tasks, and support better operational decisions.
Sponsor for this episode…
This episode is brought to you by Keyrenter Property Management.
Keyrenter Property Management is a full-service property management company that helps clients buy, renovate, and operate real estate assets.
The team helps clients build wealth while taking the headache out of property management.
That’s why, no matter what rental you have — single-family homes, condos, townhomes, or apartments — they can give you the management solutions you need.
To learn more about their services, go to https://keyrenterpmc.com/ or send them an email at [email protected].
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Episode Transcript
Intro 00:04
Welcome to The Same Day Podcast, where we discuss driving incremental business growth and other topics related to real estate, property management, and entrepreneurship. Now to the show at hand.
Yoni Schmidt 00:20
Hi there. Yoni Schmidt here, hosting today’s episode of The Same Day Podcast. Excited to be in our new office today. And today’s episode is brought to you by Keyrenter Property Management. At Keyrenter Property Management, we are a full service property management company offering our clients all services. We help our clients buy, renovate, operate real estate. that is why no matter what real estate assets you have single family homes, condos, townhouses, or apartments, we have the management solutions for you. We help our clients build wealth by removing the headache of real estate ownership. Go to keyrenterpmc.com or email us at [email protected] for more details.
Today’s guest is John Ledesma, Founder and I guess CEO as well, of LeasIQ, an AI powered property management platform built specifically for self-managing landlords and small property management managers. with a background in physics, electrical engineering, molecular biology, real estate investing, and software development. boy, that’s a lot.
John approaches real estate operations like an, like an engineering problem. He uses AI to eliminate inefficiencies, automate repetitive tasks, and help landlords operate like professional property management companies. He’s also building an AI platform that simplifies land entitlement and development workflows, making him one of the most innovative builders at the intersection of artificial intelligence and real estate technology. Today, we’re talking about the future of property management, where AI delivers the most real return on investment and how small operators can compete with much larger firms.
Welcome to the show, and thank you for being here, John. This is exciting because we’ve been trying to have this podcast for a while.
John Ledesma 02:21
Yes, it’s my pleasure. So my name is John. I’ve been around the OKC area for about five years now. I came from the Portland area, Portland, Oregon moved out to the Midwest, went to Nebraska and actually found my wife online. We were dating online and decided to make Oklahoma our home.
So we’ve been here for about five years.
Yoni Schmidt 02:54
Beautiful.
Yoni Schmidt 02:55
Well, John, let’s dive right in. Tell us a little bit about what inspired, you know, you to build LeasIQ. What was the gap that you saw in the property management software market?
John Ledesma 03:05
Yeah. So I didn’t start by trying to build an AI company. I started really noticing a pattern. Every independent landlord I was speaking with was incredibly busy, but not necessarily because managing rentals is inherently difficult. They were busy because they were doing the same repetitive work over and over again.
You know, they were answering the same leasing questions tracking maintenance through text messages or following up with vendors, remembering lease renewals. And honestly, none of those tasks require years of experience, but together they consume an enormous amount of time as well as mental energy. And then at this, you know, at the same time I looked at the software available to them and most property management platforms were really digital filing cabinets. They stored information well, but they didn’t actively help landlords run their business. So I thought, what if software could actually become part of the team instead of waiting for the landlord to remember every task?
, you know what? If it could answer routine questions, it could organize maintenance requests, it could remind you about upcoming renewals and keep the work moving even while you’re asleep. And so that’s really where it came from. The gap wasn’t that landlords needed more software. They needed software that could actually do some of the work.
And that’s what I mean by AI. Native AI isn’t a feature that we’ve bolted on to an existing platform. It is built into the way the platform operates from the beginning. And so my goal has never been to replace landlords or property managers. It’s to remove the repetitive work that prevents them from focusing on the parts of the business where experience and judgment really matter.
And I think the best technology doesn’t make people feel replaced. It makes them feel more capable. And that’s the company that we’re trying to build.
Yoni Schmidt 05:22
Yeah. Love that. And so most, most software companies seem to be chasing enterprise customers, right? The B2B is always the play when you start a business, everyone tells you go B2B. That’s where the money is.
Yeah. why did you choose to build something that’s, you know, specifically built for self-managing landlords and small operators?
John Ledesma 05:43
Yeah. Great question. I think the industry has had its priorities backwards for a long time. The only enterprise customers are important, but they usually have advantages that small operators don’t. They have a dedicated staff.
They’ve got specialized departments established processes and usually a budget to hire outside help when something falls behind. The independent landlord with five, 10 or 20 properties doesn’t have any of that. They’re they’re wearing all the hats, right. They’re the leasing agent. They’re the maintenance coordinator, the accountant, they’re customer support.
And on top of all that, they probably have another full time job. So every hour they lose to repetitive administrative work matters a lot more. And that’s why I saw such an opportunity. AI has the ability to level the playing field. And so for the first time.
A small operator can have software that answers routine questions keeps track of maintenance, follows up on tasks, and helps organize the business in ways that used to require a full office of people. So to me, that’s incredibly exciting because it democratizes capability. I also think independent landlords make decisions differently than large organizations. They don’t buy software because it’s packed with features. They buy it because it solves a problem that they deal with every day.
It helps them lease a property faster. It helps them avoid missing an important maintenance request. It gives them a few hours back every week, and they immediately understand the value. And those are the people I wanted to build for because I believe technology has its greatest impact when it helps people who don’t have an entire organization behind them. The goal isn’t to help small landlords look like big companies.
It’s to give them the tools to compete with them while still delivering the personal service that makes independent landlords special.
Yoni Schmidt 08:02
Yeah. So many questions..
Yoni Schmidt 08:06
You know, everyone is talking about AI today, but very few people are solving real business problems. Where do you think AI creates the biggest return on investment? inside the property management industry and businesses.
John Ledesma 08:22
Yeah. Great question. I think the biggest misconception about AI is that people expect it to replace expertise. And I don’t think that’s where the value is. The biggest return on investment comes from eliminating all the small interruptions that steal their time throughout the day.
So think about it. A typical landlord’s phone, right? What’s coming through? Is this property still available? Can I schedule a showing?
, the garbage disposal stopped working as a plumber. Confirmed the appointment. And none of those questions are difficult, but they arrive all day long, every day, and they constantly interrupt whatever else you’re trying to accomplish. And that’s where I think AI shines. It handles the repetitive, repetitive work instantly and consistently and around the clock.
But there’s another side to ROI that often gets overlooked. And it’s not just about saving labor, it’s about preventing expensive delays. You know, if a prospective tenant hears back in two minutes instead of two days, the chances of leasing that unit improve dramatically. If a maintenance request is identified and routed immediately, you have a much better chance of fixing a small problem before it becomes a major repair. So if renewals surf are surfaced early instead of at the last minute, you can reduce unnecessary vacancy.
And those those aren’t flashy AI demos. They’re operational improvements and operational improvements compound over time. I think that’s the difference between using AI as novelty and using it as a business tool. One generates interesting conversations and the other generates measurable results. So at the end of the day, landlords don’t care whether a task was completed by a person or by AI.
They care that their tenants were taken care of, the property stayed occupied, and their business became easier to run. And that’s where the real ROI is not in replacing people, but in removing friction..
Yoni Schmidt 10:36
Interesting. You described LeasIQ as an AI native platform. can you tell us a little bit about what that means and how is that different from simply adding, you know, ChatGPT to your existing software?
John Ledesma 10:50
Great question..
John Ledesma 10:53
You know, that’s a great question because AI native has become one of those buzzwords that can mean almost anything. And to me, AI doesn’t mean that you’ve added a chat box to your software. It means you’ve designed this software from day one with the expectation that AI would be an active participant in the workflow, and not just an operational feature. So let me give you an example. In traditional property management software, tenant sends a maintenance request.
The software will record it, and then it waits for the landlord to decide what to do next. So it’s essentially a digital filing cabinet. An AI native platform behaves differently. It recognizes that it is a maintenance issue. It creates the work order.
It organizes the conversation. It keeps the history together. It reminds you if nothing’s happening and it helps move the workflow forward instead of just documenting it. And that’s a fundamentally different philosophy. I sometimes compare it to the difference between a GPS and a paper map.
So a paper map will give you information, but a GPS actively helps you get where you’re trying to go. Both contain information. Only one is working with you. And that’s how I think about native AI software. The AI isn’t sitting off to the side waiting for someone to ask it a question.
It’s quietly helping the business operate more efficiently throughout the day. And I think that’s where the industry is heading. So in a few years, I don’t think people will be asking, does your software have AI? They’ll be asking, does your software actually help me run my business? And that’s the standard we’re trying to build toward AI isn’t the product a better operating experience is the product.
Yoni Schmidt 12:58
That’s an interesting.
Yoni Schmidt 12:59
Analogy between the map and the GPS. I like that and definitely some some good points there. you know, tell us a little bit, I mean, to, to, to build on this, like, you know, in today’s world, if we’re, you know, using the map and the GPS analogy, what tasks do you believe property managers should never be doing manually in 2026, going into seven, eight and into over the next five years?
John Ledesma 13:28
Sure, sure.
John Ledesma 13:29
And however, I think the better question is, is which tax tasks actually require human judgment, because whatever’s left, that’s what we should be automating. There’s there’s certain jobs that computers are simply better at, right? Remembering things following up consistently organizing information or responding instantly to routine questions, tracking deadlines and humans aren’t great at those things, not because we’re careless, but because we’re judging. Excuse me, we’re juggling a hundred priorities at once. So if a property manager is spending their morning copying information between systems are chasing unanswered emails sending the same lease availability message 50 times, or tracking maintenance requests on a spreadsheet.
I don’t think that’s a good use of their expertise. Technology should be handling that. And that’s where people create value is somewhere and where people create the value is somewhere completely different. So sitting down with a resident who’s going through a hardship or negotiating with a contractor after a major repair, deciding whether to renew a lease resolving a difficult conflict between people. Those situations require judgment.
, they require context, they require empathy, and sometimes they require creativity and AI can’t replace that. And honestly, I don’t think it should try. So my view is that every task and property management falls into one of three buckets. The first is repetitive work, and that’s where AI should do almost all the heavy lifting. The second is analytical work.
An AI can organize the information. It can identify patterns, surface insights. But a person should still be making the decision. And then the third is human work. And that’s building trust.
It’s, leading people. It’s solving unusual problems. And that’s where experienced property managers create tremendous value. So if we use AI, well, property managers won’t become less important. They’ll spend less time acting like administrators and more time acting like trusted advisors.
So that’s not replacing the profession. It’s really elevating it.
Yoni Schmidt 16:20
Yeah, we sure could use some elevation in our.
Yoni Schmidt 16:25
, industry, that is for sure.
Yoni Schmidt 16:29
Tell me. There are about 17 million.
Yoni Schmidt 16:31
Self-managing landlords in America today.
Yoni Schmidt 16:34
What do you believe are the biggest pain points that they face?
John Ledesma 16:40
So I think the biggest challenge isn’t maintenance. It, it isn’t vacancies. And it, and it’s, and it isn’t collecting rent. Those are those are the problems that we see. The real challenge is that self-managing landlords are constantly switching roles.
At 9 a.m. in the morning, they’re answering a leasing inquiry. An hour later, they’re scheduling a plumber at lunch. They’re reviewing a lease at that afternoon, they’re collecting rent, and at dinner they’re phone buzzes because a tenant has a maintenance question. It’s it’s not that any one of those jobs is overwhelming. It’s the fact that they’re happening all day, every day with no off switch, and that’s exhausting.
The. The second challenge is responsiveness. We live in a world where people expect answers quickly. Prospective tenants don’t wait three days for a response anymore. If.
If they contact for. Landlords are usually going to rent from the one who responds first and communicates well. And the same is true for maintenance. Tenants understand that not every repair can happen immediately. What frustrates them is the feeling that no one heard them.
So good communication builds trust even before the repair is complete. And finally, I think many independent landlords are flying blind. They know their priorities. They know their tenants, but they don’t always have visibility into how their business is actually operating. How quickly are leasing enquiries being answered?
Which Vendors consistently respond. Which maintenance requests stay open the longest? Where, where, where? Where is time actually being spent? Right?
Those questions are surprisingly hard to answer without good systems. So to me, that’s the opportunity. It. AI isn’t just about automation, it’s about creating clarity. So when landlords have better visibility into what’s happening across their portfolio, they make better decisions.
They respond faster. They spend less time worrying that something has slipped through the cracks. And so at the end of the day, most independent landlords don’t even need more hours in the day. They need fewer things that are competing for their attention.
Yoni Schmidt 19:13
Yeah, we call it monkey brain.
Yoni Schmidt 19:14
In the world of property management, where you’re like, you know, you’re doing one thing and then you have to jump on another thing, and then a fire comes in and you have to put out that fire. And so you’re jumping from one thing to the next and the next and the next over the course of the day.
Yoni Schmidt 19:28
So that’s a good point. tell me at what point should.
Yoni Schmidt 19:32
Someone hire a property manager versus investing in better software systems?
John Ledesma 19:37
Yeah. That’s great. That’s a great question. I actually don’t think that there’s a magic number. people will often ask, should I hire a property manager when I get to ten, 20, 50 units?
I think that’s the wrong question. The better question is what’s consuming your time? So if most of your day is spent answering routine leasing questions or coordinating maintenance, following up with vendors and trying to remember what still needs your attention. First, I’d invest in better systems because if you automate and organize that repetitive work, you discover you can comfortably manage more properties than you thought. And then on the other hand, if your portfolio, excuse me, has become more complex, maybe you’re operating in multiple markets or managing renovations working with investors or making strategic acquisition decisions.
That’s where a great property manager becomes incredibly valuable. So notice the difference. Software isn’t excellent at hand. Software, excuse me, is excellent at handling repetition, but great property managers excel at judgment. They know how to navigate difficult conversations.
, they know when a contractor’s estimate just doesn’t look quite right. They know how to resolve conflicts before they become legal problems. And that’s experience. And I don’t think AI replaces that. In fact, I think AI makes those professionals even more effective because it removes the administrative work that gets in the way.
So my advice is always to improve the system before you add more people. Once the repetitive work is streamlined, it becomes much clearer where human experience creates the most value. And technology should reduce administrative work, and people should focus on the decisions that require experience, judgment, and trust. And that’s where the real leverage comes from.
Yoni Schmidt 22:02
That’s great. really, really interesting stuff. So,.
Yoni Schmidt 22:07
Tell me.
Yoni Schmidt 22:07
I guess, you know, if someone owns 5 to 20 rental properties.
Yoni Schmidt 22:11
Right? How much time and money could AI realistically save them..
John Ledesma 22:18
I think it’s important to be realistic because every portfolio is different. If someone tells you AI is going to magically run your rental business for you, I’d be skeptical. That’s not how I see it. What AI does exceptionally well is to eliminate the hundreds of small tasks that quietly consume your your day. Think about how a landlord answers the same leasing questions.
. Coordinates maintenance follows up with vendors, tracks renewals, responds to routine tenant messages. So none of those tasks takes an hour by itself, but together they add up to a surprising amount of time every single week. So for many self-managing landlords with 5 to 20 properties, it’s realistic to reclaim several hours each week simply by automating those repetitive workflows. And those hours matter.
Maybe that means showing another property. Maybe it means analyzing your next investment. Maybe it’s just having dinner without checking your phone every 15 minutes. I also think people underestimate the financial impact. The biggest return isn’t usually from cutting expenses, it’s from avoiding costly delays.
So leasing a vacant property a few days sooner because every inquiry gets an immediate response. Catching a maintenance issue before it turns into a major repair. Following up on a lease renewal early enough to reduce vacancy, those operational improvements can easily outweigh the monthly cost of the software. So when people ask me how much AI can save, I think the better question is how much is Inefficiency already costing you because once you start looking at delayed responses, missed follow ups, preventable repairs and unnecessary vacancy, you realize the cost of doing nothing is often much higher than the cost of improving your systems. AI doesn’t create value because it works faster than people.
It creates value because it helps important things happen on time every time.
Yoni Schmidt 24:43
You mentioned maintenance earlier. you know, which is quoted, as you know, probably one of the biggest headaches that landlords experience, right? Yeah. Tell us a little bit about how Q changes that experience for landlords.
John Ledesma 24:58
Yeah. I think maintenance is stressful for one simple reason. It’s almost never about fixing something. It’s about coordinating people. So A tenant reports the issue.
The landlord has to gather the information, then contact a vendor. Schedule a repair follow up if nobody responds. Keep the tenant informed. Make sure that the work was actually completed. And that’s a lot of moving parts.
And every delay creates frustration for everyone involved. And what we’ve tried to do with LeasIQ is to make that process feel much more organized and much, much less reactive. So instead of maintenance requests disappearing into emails or text messages or sticky notes, everything begins in one place. The AI helps capture the details, organize the request, keep the conversation together, and make sure that nothing quietly falls through the cracks. It can keep everyone informed along the way, so tenants aren’t wondering whether anyone even saw the request.
And that’s an important point. Most tenants, they don’t expect every repair to happen immediately. Right? What they do expect, though, is communication. They want to know.
Someone heard me. Someone’s working on it. I haven’t been forgotten. And that’s where good systems make a huge difference. They create confidence even before the repair is finished.
And I, I also think maintenance creates valuable information. So over time you begin to see patterns which properties generate the most work. which vendors are responding the, the fastest, you know, are certain repairs happening repeatedly. And that’s the kind of operational insight that’s very difficult to see when everything is scattered across emails and text messages. So Li CQ helps automate pieces of the maintenance process, but more importantly, it gives landlords a system instead of a scramble.
And when maintenance becomes a system, instead of a series of emergencies, everyone has a better experience the landlord, the vendor, and most importantly, the tenant.
Yoni Schmidt 27:21
Yeah. I love that you kind of answered my next question. So I appreciate that. So I’ll skip a little bit ahead. you know, we, we, we know that, you know, one, one late paying tenant can quietly end up costing, you know, investors hundreds, if not thousands of dollars you know, each year.
So why is it that so many landlords underestimate the cost of the operational inefficiencies?
John Ledesma 27:48
Yeah. Great question. I think it’s because most operational costs never show up as a line item on a financial statement. if, if your roof needs to be replaced, you see the invoice, If you buy a new Hvac system, you know exactly what it costs. But operational inefficiency, inefficiencies, excuse me, are different.
There are a hundred small losses that never happen all at once. So a leasing inquiry sits unanswered for a day. A maintenance request gets buried in a text thread. rent collection takes an extra week. A lease renewal starts a month later than it should have, and none of those events feel catastrophic.
But when they happen over and over again, they quietly erode profitability. Take one late paying tenant as an example. Most people focus on the late fee, and I think that’s the smallest part of the story. The real cost is in the follow up calls, the reminder emails, the uncertainty around cash flow, the time spent tracking payments, and sometimes the vacancy or legal costs that follow If the situation isn’t resolved, that’s where the money disappears. I think it’s I like to think of it as operational drag.
It’s similar to driving a car with the parking brake slightly engaged. The car still moves, but and you may not even notice it at first, but over time you’re burning more fuel, you’re putting more wear on the vehicle and making the journey harder than it needs to be. And that’s what inefficient processes do to a rental business. They don’t usually cause dramatic failures. They quietly erode performance each each and every day.
And so that’s why I’m passionate about better systems. When you remove the operational drag, you don’t just save time, you improve responsiveness, you improve tenant satisfaction, you improve occupancy, you improve cash flow. Those improvements reinforce one another. So the biggest threat to profitability usually isn’t one catastrophic mistake. It’s dozens of small inefficiencies repeating themselves every week.
Yoni Schmidt 30:16
That’s an interesting take. And yeah, one that I would agree with.
Yoni Schmidt 30:20
, so beyond, beyond, you know, just improving those inefficiencies and becoming more efficient and saving time, where can AI actually help landlords create more revenue?
John Ledesma 30:36
So a great question. Great question.
John Ledesma 30:37
I think that’s one of the most overlooked questions in real estate technology. Everyone talks about how AI saves time and that matters. But revenue matters even more. When I look at a rental business, I see several places where better systems can directly improve income. The first is leasing speed every day a unit sits vacant.
It costs money. So if AI can respond to prospective tenants immediately answering routine questions 24 over seven and schedule showings faster, you increase your chances of filling the vacancy sooner, even reducing vacancy by a few days. Each turnover can have a meaningful impact over the course of a year. The second yoni is is lease renewals. Renewals shouldn’t be shouldn’t begin a week before the lease expires.
They should begin a month in advance. I think, so better systems help landlords start those conversations earlier, giving both sides more time to make decisions and reducing unnecessary turnover. And the third is the tenant experience. Happy tenants. They tend to stay longer.
They communicate more. They take better care of the property and they generate fewer surprises. And AI can’t create a great tenant relationship by itself. But what it can do is help make sure tenants receive timely communication maintenance updates, and faster responses, all of which contribute to a better experience. And then, and then there’s the decision making.
So AI can surface patterns that are difficult to see manually, like what properties consistently have higher maintenance costs or which vendors deliver the best service. Where are the vacancies lasting longer than expected? Better information leads to better decisions, and better decisions usually lead to better financial performance. So yes, AI does save time, but I think its biggest long term value is helping landlords operate a healthier business. Revenue grows when you reduce vacancy, and profit grows when you reduce inefficiency.
And the most successful landlords understand that you need both. And that’s where I believe AI creates its greatest financial impact.
Yoni Schmidt 33:11
Interesting. Let’s talk a little bit about your journey.
Yoni Schmidt 33:14
Since you’re a solo, you know, a solo founder building this, you know, these products you know, in public, what’s been the biggest challenge in creating AI software for real estate?.
John Ledesma 33:27
Great question again. I think the biggest challenge has actually been balancing two very different worlds. On the one side AI is evolving incredibly fast. And every week there’s a new model a new framework, a new capability that gets everyone excited. But on the other side, real estate moves at a very different pace.
Landlords and property managers, they don’t wake up asking, what’s the latest AI model? They wake up asking, how do I get this unit leased? Or why hasn’t the plumber called me back? So as a founder, my job is to bridge those two worlds. It’s easy to get distracted by the newest technology.
The harder and more important question is, does this actually solve a problem my customer has. And building in public has reinforced the lesson over and over. When you. When you share what you’re building, people will tell you what’s what, tell you what’s useful, what’s confusing, and sometimes what you completely missed. That feedback is invaluable.
So some of the best improvements in LeasIQ didn’t come from me sitting in front of a computer. They came from conversations with landlords who, who, who said, where, where’s, here’s where my day falls apart. And the other challenge is wearing so many hats. As a solo founder, I’m writing code. I’m talking with customers thinking about product design and working on marketing, solving infrastructure issues, planning the roadmap.
There are days when I am debugging software in the morning and talking with potential customers in the afternoon. It definitely keeps you humble, and there’s an upside to that because I’m so close to both the technology and the customer. I get to see immediately whether an idea creates real value. If it doesn’t, we change it. The the feedback loop is incredibly fast, and I think being a solo founder has taught me something that goes beyond software.
Innovation isn’t about building more features. It’s about listening well enough to solve the right problems. And so if I can keep doing that, I think technology will continue to take care of itself.
Yoni Schmidt 35:47
Yeah. you know, your background includes engineering.
Yoni Schmidt 35:51
Physics, biology, you know, investing. Tell us like, how has that systems thinking influenced the way that you build technology?.
John Ledesma 36:03
I think all of those disciplines taught me the same lesson. And that’s everything is a system. So whether you’re studying a cell, whether you’re designing a, an electrical circuit or solving a physics problem, or even managing a portfolio of rental properties, you’re trying to understand how different parts interact with one another. So once you start thinking that way, you stop looking for isolated problems. You start looking for root causes.
For example, if a property has a high turnover rate, it’s easy to say we have a tenant problem, but a systems thinker is going to ask different questions. Our maintenance requests taking too long or ceasing and eating unanswered. Are renewals being are are they started too late? Is so is the communication inconsistent? So in other words, what is the system produce.
What in the system is producing the the outcomes. That’s how I kind of approach software. I don’t start by asking what features should I build. I start asking, why is this process breaking down in the first place? Sometimes the answer isn’t more software, sometimes it’s simplifying the workflow, sometimes it’s removing unnecessary steps.
Sometimes it’s making the right information visible at the right moment. And so that’s one lesson engineering really reinforced for me. The best systems aren’t the most complicated. They’re the ones where every part has a purpose, I think biology influenced me in a different way. Living systems are incredibly resilient because they rely on feedback.
They’re constantly. They’re sensing what’s happening. They adapt, adjust, and great businesses work the same way. They pay attention to what’s happening with customers. They learn from it and improve continuously.
And that’s exactly how we’ve built Li CQ. We listen, we learn, we improve, and then we repeat the cycle. So when people ask how my background shaped the way I build technology, my answer is actually pretty simple. I don’t see software as a collection of features. I see it as a system that’s either helping people make better decisions or it’s just getting in their way.
And my goal is to always design systems that make good decisions easier, bad decisions less likely, and service more consistent. Because at the end of the day, people don’t experience software one feature at a time. They experience. They experience it one workflow at a time.
Yoni Schmidt 39:00
Okay, I’m going to skip ahead a little bit, but.
Yoni Schmidt 39:04
Tell me, where do you see AI having the biggest impact? you know, in what you’re doing right now land development over the next decade.
Yoni Schmidt 39:16
Yeah, a little bit of a topic change here.
John Ledesma 39:19
Yeah. No problem. I think the biggest impact it won’t be in that AI designs better developments. It’ll be that AI helps developers make better decisions. Land development is really a sequence of decisions.
Which property should we pursue? What are the entitlement risks? What conditions of approval are likely and how long might approvals take? Where are the hidden costs? So every one of those decisions affects millions of dollars downstream.
And the challenge isn’t that much of the information needed to answer those questions is, is scattered across the that that is the challenge. So it’s scattered across dozens of planning documents, staff reports meeting minutes, ordinances, engineering, engineering requirements historical approvals. It’s, it is public information, but it’s not easily, easily, easily usable. Excuse me. Information.
I think AI changes that. So instead of spending days or weeks searching for answers, developers will be able to understand the properties, opportunities and risks much earlier in the process. And that doesn’t replace due diligence. It makes due diligence smarter. And so I think AI will help identify patterns that are difficult for any individual to recognize.
For example, what types of projects tend to receive additional conditions of approval or what jurisdictions can consistently require certain infrastructure improvements. What issues are issues repeatedly delay approvals? Those are the insights. Those insights, they already exist. They’re just buried inside thousands of pages of public records.
And AI can help surface them. And I think that’s incredibly valuable because uncertainty is expensive. Developers don’t mind solving difficult problems. What they struggle with is discovering those problems after they’ve already committed significant time and money. And if AI can help move that knowledge to the beginning of the process instead of to Instead of the end, and you fundamentally improved the quality of decision making.
And that’s why I believe the business, the biggest opportunity isn’t automation. It’s reducing uncertainty. You know, the best projects aren’t always the ones with the highest potential to return. They’re the ones where you understand the risks before you invest in the capital. So I think over the next decade, AI will become an indispensable research and decision support partner for developers, and not because it replaces their expertise, but because it helps experts spend less time searching for information and more time applying their judgment.
Yoni Schmidt 42:19
Yeah. tell us if you could.
Yoni Schmidt 42:24
Wave a magic wand and automate one thing for every single property owner landlord in America, what would that be?
John Ledesma 42:35
I could wave a magic wand.
Yoni Schmidt 42:40
I can wait.
John Ledesma 42:43
Okay, so I’d automate the need to constantly remember everything. I know that sounds like a strange answer, but I really believe that’s the biggest burden landlords carry. Think about everything that’s running through a landlord’s mind on any given day. Which tenants still need a reply? did the plumber ever confirm that appointment?
Which lease expires next month? Did that rent payment come in or did I remember to follow up with that prospective tenant? None of those thoughts are difficult by themselves. The problem is that they’re competing for your attention at the same time, and after a while, that mental load becomes exhausting. I don’t think landlords are looking for a system that magically runs their business.
I think they’re looking for confidence that nothing important has been forgotten. And that’s a very different goal, you know? Imagine starting every morning knowing that your system is already identified. What needs your attention today? Not 50 notifications, not 100 emails, just a clear picture of what actually matters.
I think that’s incredibly freeing because your brain isn’t occupied trying to remember every task it. It has room because your brain isn’t occupied trying to remember every task. Right? It’s it has room to think strategically. So you start looking for your next your next investment instead of, you know, reading about your last maintenance request, you you spend more time building your business instead of simply reacting to it.
And that’s what I’d automate. Not decision making, not relationships, not judgment. I automate the burden of remembering because I think the greatest gift technology can give us isn’t doing our thinking for us. It’s giving us the mental space to think about the things that really matter most.
Yoni Schmidt 45:05
I love that. Yeah, that’d be great. what’s one workflow in the property management world that’s completely broken today and you believe will disappear in the next five years?
John Ledesma 45:20
Yeah.
John Ledesma 45:21
I think it’s the idea that people have to constantly change information. You know, today, property managers spend an incredible amount of time asking questions like, did anyone respond to that tenant? what’s the status of that maintenance request? did we ever hear back from the contractor which leases are coming up for renewal? And a lot of companies, the answer is still.
Let me check. That means information is scattered across emails, text messages, spreadsheets, and different software systems. The work isn’t managing properties. The work is finding the information you need to manage those properties. I don’t think that will last five years from now.
I think software will continuously organize that information in the background and surface what actually needs attention. So instead of people chasing updates. Updates will come to the people who need them. And that’s a fundamentally different workflow. I think it changes more than efficiency.
It changes the quality of decision making. So when you have the right information at the right time, you’re more responsive. You communicate better, you solve problems better, you create a better experience for owners, tenants, vendors, and your team. And that’s why I’m optimistic. I don’t think the future of property management is about replacing people.
I think it’s about removing friction. You know, the repetitive, the repetitive work will fade into the background and the human work will move into the foreground. And that’s where relationships are built. That’s where trust is earned. And that’s where great property managers have always created value.
So if AI helps us spend more time there, I think that’s a feature worth building because the best technology is almost invisible. It quietly helps people do their best work. And if we can get that right, property management won’t just become more efficient. It’ll become more human.
Yoni Schmidt 47:53
Wow. Love it.
Yoni Schmidt 47:55
John Ledesma, thank you so much. you know, enlightening me, educating us and our listeners. last kind of question, off the cuff. who are you listening to? What podcasts?
What are you reading right now? Any books? and where do you get your source of growth and professional development from?
John Ledesma 48:21
Great question..
John Ledesma 48:24
Right now I’ve kind of laid off on podcasts. I’ve listened to lots of different podcasts, especially when it comes to real estate. I have lots of books when it comes to real estate. I’ve got many BiggerPockets books..
Right now I’m actually trying to focus on YouTube Secrets by, what’s his canal? And Benji, I can’t remember Benji’s lasting, but I’m wanting to launch a podcast, a YouTube channel. And so that’s kind of where my attention is going right now just to get the word out. You know, I think it’s so important. Because I think LeasIQ will really.
If I can get the word out, I think LeasIQ can create a tremendous impact for property managers and independent landlords.
Yoni Schmidt 49:32
Yeah. Love it. would love.
Yoni Schmidt 49:34
To see the platform, maybe even demo it for our listeners and our viewers. That would be.
John Ledesma 49:39
Absolutely
Yoni Schmidt 49:41
Next step. John, thank you so much for being here.
John Ledesma 49:45
My pleasure, my pleasure. And that’s going to be where the rubber hits the road. So doing a demo.
Yoni Schmidt 49:54
Yeah. Looking forward to it.
John Ledesma 49:57
Awesome. Well, thank you so much. I really appreciate being on the podcast with you today.
Yoni Schmidt 50:04
Thanks for joining.
John Ledesma 50:05
Alrighty.
Outro 50:10
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