The AI workflow that made this investor $100k+ profit

July 23, 2026

AI for Real Estate Investors.

Brandon Turner’s weekly guide to using AI for a better life through real estate investing.

Hey, welcome to AI for Real Estate Investors.

Every issue you'll get a quick recap of the AI news worth knowing, plus real examples of how investors are using this stuff in their business (including in mine).

Lets get into this week's issue!

In This Issue

How an AI agent scans the MLS to find deals that you may never see
The new LLM model giving both OpenAI and Anthropic a run for their money
A two-step design workflow turned a blank doc into a full brand system in about five minutes (no designer needed)

This Week in AI

China's Moonshot AI drops a model that rivals top American AI at a fraction of the cost

Beijing-based startup Moonshot AI released Kimi K3 last week, a massive open-weight model (meaning anyone can download and build on it) that the company says nearly matches the best systems from OpenAI and Anthropic on several tests, including coding tasks, and outperforms their second-tier models outright. It still trails Anthropic's and OpenAI's very latest flagships overall, and at least one analyst called the market reaction an overreaction "shockingly similar to the DeepSeek panic" from last year. The gap between China and the U.S. in frontier AI has closed to something analysts now describe as weeks, and Kimi K3 is priced well below comparable American models.

For you as an operator, the practical takeaway is pretty simple: this story is about geopolitics and industry competition more than your workflow today. Kimi K3 is not yet integrated into the everyday business tools most operators use, and its full model weights aren't even publicly available until July 27. What's worth watching is the pricing pressure. When Chinese models match American quality at lower cost, the vendors you already pay, whether that's ChatGPT, Claude, or any AI-powered software in your stack, face real pressure to cut prices or ship better products fast.

Sources: axios.com, Platformer, apnews.com, cnbc.com, finance.yahoo.com, scmp.com, nytimes.com, businessinsider.com, scmp.com, economist.com, vietnam.vn, businessinsider.com

Grok Can Now Runs Tasks on Its Own While You Sleep

xAI launched Automations in Grok on July 16, a feature that lets you describe a job once in plain language, set it to run on a schedule (daily, weekdays, weekly, or monthly) or trigger whenever a matching email lands in your inbox. Grok completes the task using current information and reports back through email, an app notification, or a saved conversation log. It works on grok.com and the iOS and Android apps, with connections to Gmail, Google Calendar, Outlook, Google Drive, Salesforce, and other tools you may already use. Email-triggered automations require a paid SuperGrok subscription.

This is not an entirely new concept. Claude Cowork offers scheduled tasks, and ChatGPT has also expanded its tools for recurring work and monitoring changing information (keep reading for more on this below). The bigger story is that nearly every major AI platform is racing to make everyday automation accessible without requiring technical knowledge or a complicated stack of connected software. For an operator, that means more ways to eliminate the small administrative tasks that chip away at the day: summarizing unread emails, preparing a morning brief, sending monthly rent reminders, or flagging and summarizing messages from a lender or property manager. Grok may not be your primary AI tool today, but this market moves quickly, and an underdog can release a feature that suddenly outperforms the established leaders. Even when a launch does not appear groundbreaking, it is worth testing the tool to understand where it is stronger or weaker than Claude or ChatGPT. Just start with read-only tasks, review the first few runs, and be deliberate about how much access and authority you give an instruction designed to run without you.

Sources: x.ai, blockchain.news, x.ai, rohitai.com, basenor.com, grok.com, docs.x.ai, biztoc.com, Julian Goldie SEO, AI Profit Boardroom, Grow with AI, TECHLENSIVE

From Our Desk

From Purchase to Refi: Funding the Full BRRRR Strategy.

An investor recently found a strong BRRRR opportunity with a $185,000 purchase price, a $41,400 rehab plan, and a projected ARV of $285,000. The deal had real upside, but they needed a funding partner who understood the full BRRRR process, from purchase and rehab to refinance.

BetterLife REF helped structure the value-add purchase loan, then supported the refinance once the property was renovated, rented, and stabilized.

The property hit its $285,000 appraisal target with a 1.24 DSCR, helping the investor free up capital and move into their second BRRRR deal just one month later. Ready to fund your next rental, BRRRR, or value-add deal? See what BetterLife REF can do for you.

Need capital for your next rental, BRRRR, or value-add deal?

Get a Quote

My AI Rabbit Hole

How I’m Using AI This Week

It may not always be about real estate investing — every week I share the AI rabbit hole I’m personally going down.

How I build a full design system, complete logo, fonts, and a polished square ad, using just ChatGPT and Claude.

▶ Watch the walkthrough (5 min) · opens in Loom

Reader Spotlight

2 Deals Closed and $104K Profit in 6 Months with One AI Automation

Submitted by James Doren

WHAT IT DOES

An AI agent scans public MLS data against parameters we set (market, price range, and more), calculates MAO and ARV, and surfaces a short list of genuinely undervalued properties. We never scroll listings ourselves. The tool does the filtering and hands us only the deals worth looking at.

THE PROBLEM

Most of our deals come off-market, but we knew real MLS deals existed. The math on finding them never worked though: two of us spending hours scrolling public listings just to maybe turn up something worthwhile. We needed a way to get the signal without the manual search.

HOW I BUILT IT

We built it in Claude. Our data scientist Aida built an agent that pulls public listing data and analyzes square footage, price, bed and bath counts, zip code, owner history (to filter out recently renovated properties), price drops, current mortgage and deed info, taxes, and more. It compiles comps, calculates the gap between list price and actual value, and sends us a ranked short list on a weekly basis.

THE RESULT

In the first six months, the workflow generated 45 leads, and we closed 2 deals directly from it that we never would have found on our own. Those two deals produced $104K in profit. We also got back roughly 25 hours a week between the two of us that used to go toward manual market checks.

Are you using AI in your business? We want to hear about it. Tell us more here.

Prompt of the Week

Steal this one. Paste it into ChatGPT or Claude and make it yours:

The Prompt

“I want to know how many hours a week I am spending on tasks that AI could realistically do for me. Ask me one question at a time about how I handle [insert a project, process, or your biggest time suck] from first contact to finished, then give me a ranked list of the three steps where I am doing the most work for the least reason, with a detailed breakdown of how I could leverage AI do this instead.”

Why it works: Interviewing you one step at a time about a real process you run surfaces areas where you can implement AI to increase efficiency and effectiveness ASAP.

If you enjoyed this newsletter, forward it along to a friend! See you next Thursday

To a better life,

Brandon Turner • BetterLife Real Estate Funding

P.S. Are you using AI in your business? We want to hear about it! Submit it via the link below, and you may be featured in a future newsletter. Submit an AI Use Case →