Testing VictorAI

The Real Estate Espresso Podcast

Testing VictorAI

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Welcome to the Real Estate Espresso Podcast, your morning shot on what’s new in the world of real estate investing. I’m your host, Victor Menasce. On today’s show, we’re doing a comparison of our newly launched AI tool. This tool, lovingly called Victor AI, is a knowledge base constructed from the Real Estate Espresso Podcast and my book, Magnetic Capital.

When it comes to AI, there’s two aspects. There’s the training, and then what’s called inference, which would be the result of any query. If you’re searching in a generic AI tool like ChatGPT or Gemini or Perplexity, you’re going to get a more generic answer. This is a little bit like going to a general family medicine doctor versus going to a specialist. The specialist is almost always going to give you a more specific and more insightful answer than the generalist. The same can be said for AI tools. There are generalists and then there are specialists. What makes the difference is how they’re trained.

We created our own knowledge base and we trained our own specialist. And on today’s show, we’re going to put Victor AI to the test and compare it against three generic AI tools.

The question that I asked is a very simple one. Last week I published a show on the impact of condo reserve rules in Florida on the market. On today’s show, I’m asking a similar question to all of the AI tools. The question is, how did the Florida condo reserve study rules impact the market? I deliberately worded the question in a slightly awkward way to see if the tool could figure out what I was really asking.

For clarity, I’m using the paid version of Google Gemini, which is included as part of the Google Business Suite. And for the others, I used a quick research version of ChatGPT and Perplexity.

Now, spoiler alert, the answer from Victor AI was more nuanced and more thorough than the other generic tools.

So let’s start with Google Gemini. Google’s answer was 540 words in length, and broke down into three different sections. It correctly pointed out that the reserve study rules were enacted after the 2021 Surfside collapse, and it’s having a mixed and dramatic impact on the real estate market, in particular for older buildings.

So it broke down the impacts into three sections: the increased costs and financial pressure, the market and pricing disparity, and then the long-term benefits and market confidence. This answer was fairly superficial.

So next we’ll look at Perplexity. Perplexity’s answer was automatically upgraded to Perplexity Pro for free. They give you a certain number of free upgrades to their pro search engine when you’re using their common browser. This response consisted of 431 words, also broken down into three sections. First section was “What rules changed?” Second was the short-term impact on the market, and then third, long-term and segmentation effects. But then Perplexity also included a long list of sources that it searched in order to produce the answer. I thought the extra references were useful, but here too the answer was fairly superficial.

The third generic AI tool was ChatGPT. It gave the most comprehensive answer of all the generic tools at 760 words, and it also provided references. The answer was broken down into five sections:

1. What were the new reserve study rules and what do they require?
2. The market impacts on both pricing, sales, and inventory.
3. Who is affected the most and why?
4. Next was broader consequences both on safety and affordability.
5. And what does it mean for the near term to medium term?

As with the other AI tools, the response was fairly generic.

So now let’s look at Victor AI and see how the answer compares. The Victor AI response was 640 words in length. The answer focused on things that only a real estate investor or developer would be interested in. And that’s the part that’s interesting. That’s how you know you’re talking to a specialist versus a generalist.

Now, the answer was divided into six sections.

7. As with the others, it talked about the trigger, in this case the Surfside collapse.
8. The mandatory reserve studies and the fully funded reserves, no problem.
9. Then the economic impact. In the first one, this answer was more detailed. It talked about how much monthly dues went up.
10. It talked about special assessments, ranging from $30,000 to $60,000, even $200,000 per unit.
11. It talked about the impact on insurance of anywhere from 100% to 500% in some buildings.
12. And then how older coastal buildings, many of them, became financially distressed overnight.

Then there was the section focused on forced selling and downward price pressure, and that was also covered in many of the other tools.

But then this is where things deviated. It talked about developers stepping in. When associations can’t raise dues enough to fund repairs, only one path remains, and that’s to sell the entire building to a developer, and this is happening increasingly. Developers buy out all the owners, demolish the aging building, and construct a modern new high-rise. In many cases the land is more valuable than the existing structure. Now for investors, this is one of the few opportunities in the distress.

The last section talked about the impact on the Florida condo market. It talked about a durable shift. The fact that living in older coastal buildings will become significantly more expensive. Many buildings from the ’60s to the ’80s will no longer be economically repairable. Insurance costs are structurally higher, not cyclical. And older buildings will continue consolidating into developer buyouts. Lenders will underwrite far more conservatively. And buyers will scrutinize reserves as tightly as they scrutinize the units.

For investors, the key is you no longer underwrite the condo. You underwrite the association. You look at the reserve balance, the structural reports, the insurance premiums, the historical governance. These are all now central to valuation.

So what’s interesting is that Victor AI knows that the audience is investor-focused and parted the answer delivered to investors and not just consumers at large. Now, there was nothing in the question that would lead the AI tool to answer for investors versus consumers.

All four tools had different answers, with some overlap. They all correctly recognized that people on fixed income would be impacted. They all summarized the cause of the rule change and that the structural impact reserve study was the cause in the huge jump in condo fees and special assessments. It was only Victor AI that knew to answer from an investor perspective, and we did not ask a leading question.

So we’ll be doing more testing in the coming weeks and months as we work to improve the capabilities within Victor AI.

As you think about that, have an awesome rest of your day. Go make some great things happen and we’ll talk to you again tomorrow.

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