Welcome to the October 2025 edition of the ChatCRE newsletter. Your source for practical tips on leveraging AI in commercial real estate.
Learn to Build AI Automations: We’re now 7 weeks in to our new AI for CRE learning platform, CRE AI Studio, and have launched our first 3 step-by-step lessons on building AI automations for CRE. If you’d like to access to them, just reply to this email to let me know and we’ll get you them to you!
AI-Powered Biz Dev Tips: Check out these 3 actionable tips on leveraging AI in CRE business development.
100 Free Property Owner Contact Lookups 👀: Get 100 free property owner contact info lookups from Terrakotta.AI.
In August we launched a new way to learn to use AI & automations for CRE: CRE AI Studio.
The Studio now has over 7 weeks of step-by-step AI lessons, ranging from Prompting 101, to step by step lessons on building custom GPTs for CRE, to using AI for reviewing & drafting legal docs (taught by a CRE attorney), and we just launched our first lessons on building AI-powered AUTOMATIONS, apps & dashboards for commercial real estate.
Last week we covered 2 key lessons:
I guided a lesson on automations 101, and building what I think is one of the most wide-ranging AI automations in CRE: Automated intel extraction from CRE docs with the Relay App. Think: OM arrives in your inbox, you put it in a folder, AI automatically sucks out the deal intel, sends you a summary of the deal points, and logs the intel anywhere you need it. This can be applied to inbound deals & investment decks leases, P&S’s, any CRE docs that are sucking up your time.
Jonathan Buckelew walked through building apps for generating CRE marketing materials, designing property websites in minutes, and creating asset management dashboards for key property metrics, all common AI platforms like Lovable, Replit, and Base44.
And if you don’t feel like you’re ready for building AI automations and apps just yet, don’t worry, we’re covering how to get started with AI from top to bottom in the Studio. Here’s the rundown of the live lessons so far:
Week 1: Intro to AI for CRE
Quick tips & AI use-cases across CRE
Week 2: Tools of the Trade
A deep dive on our most frequently used AI tools for CRE workflows
Week 3: AI Prompting 101
6 prompting frameworks to help you get the most out of the tools outlined in week 2
Week 4: AI for Legal Docs
LOI drafting, lease & P&S review, version comparison & redline suggestions with AI
Week 5: Building Custom AI Assistants (Custom GPT’s)
Deal summaries, business development, & legal use-cases
Week 6: Deep Research Deep Dive
Using Deep Research & Perplexity Labs to find potential users, identify distressed properties, generate Real Estate Committee Packages, & identify market benchmarks for lease negotiations
Week 6 Bonus Session: Time Saving Automations
Building your AI meeting brief assistant, and your urgent email text alert system.
Week 7: Automations 101 & Building Your Automated CRE Doc Analyzer
Building automations to summarize deals or CRE docs you receive via email, and send the intel wherever you need it.
Week 7 Bonus Session: Building AI Apps, Websites & Dashboards
Watch Jonathan build all 3 and answer questions from the community live.
If any of that sounds like it would be helpful to you, just respond to this email and we’ll get you access. You can learn more about CRE AI Studio here.
I attended a fantastic commercial real estate conference recently. One of the sessions featured a real estate executive from a large tech/AI company. I can’t say who, as part of their agreeing to speak was that the audience was sworn to secrecy. But they gave their take on the best ways to use AI for business development in commercial real estate, based on what it’s actually capable of right now (apposed to the hype.)
Here’s my top 3 take aways from the session on using AI for business development in CRE:
Note: Some of these tips have already been covered in this newsletter. If you’re new here, you might be seeing them for the first time, if not, hopefully it’ll be a timely refresher.
Deep Research
What it Does: Deep Research is a FEATURE of most major large language models (ChatGPT, Google Gemini, Claude, Perplexity all have their own version). It enables you to tell it the kind of information you’re looking for, and the kind of sources you want it to pull from, and it will scour those sources to pull you the relevant information.
The Biz Dev Angle: In the session, the executive gave an example of someone trying to lease office space in Silicon Valley or San Francisco - You could easily ask Deep Research to search media sources that publish recent VC funding announcements, and to pull a list of every tech company that’s received new funding over the past week, and receive a list of companies with fresh capital that are likely to need a larger office space. This could be an opportunity to fill a vacant space, or for a tenant rep assignment. That’s is a great use-case, but it’s pretty specific, so here’s a more general one.
In the example below, I went a little more broad. I asked Google Gemini Deep Research to search for news articles published in the last 6 months, in Ohio, that mention local industrial companies
that have somehow indicated they’re likely to expand. You may have your own expansion indications that you’d search for in the news, but I went with hiring initiatives, recent acquisitions, recent investments, or just announcements that a company may be seeking new locations. The results of Deep Research rarely fail to impress me.
Notebook LM for Pitching Business
What it Does: NotebookLM is one of my most frequently used AI platforms over the past 6 months. It enables you to create AI research assistants (Notebooks), grounded ONLY in the sources that you provide it (sources can be PDF’s, text, links to websites or Youtube videos, or Google Drive files). The benefit of this? It won’t make stuff up (or at least RARELY makes stuff up.) So you can ask your AI research assistant questions and know that it’s much less likely to respond with an AI hallucination, because it will show you in your sources where it got the information.
The Biz Dev Angle: The speaker at the conference gave a great example I hadn’t thought of before. Let’s say you have the opportunity to pitch some new business, but you have limited intel and want to craft your pitch to speak to that company as much as possible. Imagine how powerful it would be to download every piece of useful documentation you can find on that company, and provide it to a research assistant so that you can instantly learn about that company, their pain points, and how your services can solve for those pain points. Heaven forbid you’re pitching a publicly traded company with public filings or one that is constantly in the news, just think of all the publicly available intel on that company that you can provide your AI research assistant, and use it to tailor your pitch.
Example: Imagine you have a client that’s expanding into a market you’re less familiar with, or you’re considering expanding your own business or acquisition criteria into a new market. You could load up Notebook LM with every publicly available market report on that market and immediately have an AI assistant ready to educate you on the market.
Bonus Tip: NotebookLM isn’t just a ChatBot. You can use Notebook LM to create briefing documents about the info (or just some of the info) you’ve uploaded to it, or even podcasts & videos. You can see some additional ways to use Notebook LM in CRE in this recent newsletter.
AI-Assisted Biz Dev Content:
I’ve said this before so hopefully I’m not starting to sound like a broken record, but it has NEVER been easier to create custom-tailored content that speaks to your target audience in the advent of some of these AI tools, and the tech executive speaking at this conference echoed this sentiment. But the truth is this: Most people using these tools are using them to create AI SLOP, content that adds no value and speaks to nobody. Take the time to learn to use one, or a handful of these tools to make content your audience will actually want to consume and engage with, and your ability to get your message in front of those people will improve exponentially.
Example: I used one of my favorite AI content tools, Opus Clips, to analyze this hour long video recorded for CRE AI Studio, identify engaging clips from the video, add captions to them instantly, and make quick edits, all in under 15 minutes.
This video got thousands of impressions from minutes of editing. That might not sound like much, but think about this: That’s more eyeballs than many commercial real estate websites see in a month. Imagine how many people in your target audience you could get in front of if you’re leveraging these tools on a daily or weekly basis.
I don’t want to make this newsletter too long, so I won’t do a deep dive on my favorite AI tools for content. But you can see most of the tools in my personal AI tech stack in this recent edition of ChatCRE. The key updates to this list would be that Google’s VEO, ChatGPT’s Sora, and Grok have recently made astounding progress in their ability to create realistic AI generated videos, with audio included. You can see an example of me using Grok to turn a property image into a video below.
You may be saying to yourself - “Topher, you’ve mentioned most of these tools in previous newsletters.” You’re right, that’s because they actually work! The goal here is to separate the practical applications of AI from the stuff that’s just noise.
And speaking of AI biz dev tools that actually work - The folks at Terrakotta.AI are offering a deal you’ll probably want to check out.
If that sounds familiar, we covered Terrakotta.AI in a newsletter earlier this year. You can get the deep dive on the platform there, But here are the highlights:
Terrakotta allows you to:
Give it a prompt with property criteria, (or just click on a property with their new Chrome extension) have it search public ownership records to find who owns it, pierce the LLC to find the person associated with it, and run that intel to through contact lookup platforms to get their phone number, all from a prompt or a button click.
The numbers it finds won’t all be correct, but if you actually sign up for Terrakotta, it can power-dial through the numbers it finds until you them until you connect with the owner.
Finally, you can leave AI-generated voicemails for the numbers you don’t get connected to. This feature isn’t for everybody, and personally, AI generated voicemails isn’t a use of AI that speaks to me (pun intended), but many find this feature useful.
For a limited time, you can get 100 free AI-powered property contact lookups from Terrakotta through their Chrome exetension, courtesy of your friends at ChatCRE & CRE AI Studio. Just head to this link to get to (you’ll need to set up a short call with the folks from Terrakotta so they can show you how it works.) Feel free to check out the video below if you’d like to see a quick example.
This is not a paid endorsement. But I’m a fan of the platform and the co-founders, and I appreciate that they’re leveraging AI to solve a real pain point in CRE.
That’s it for the October 2025 edition of ChatCRE. I’d love to hear your thoughts on this edition - what you found valuable, what you could do without, or any topics you’d like me to cover in future newsletters. Feel free to comment below, send me an email, or reach out on X.
If you found this newsletter helpful, please consider sharing it with a colleague or friend who could benefit from enhancing their CRE operations, marketing, or pipeline with AI.
P.S.
I’m currently booking private and public presentations on how to leverage AI tools for commercial real estate for Q1 of 2026 (wow, time flies). If you’re interested in helping your team, company, or association learn about powerful AI tools for CRE, please send me an email, and we can set up a time to connect.

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