Description
Stride: https://go.retipster.com/stride/yt-kUr2GSRwifM
What would happen if your CRM became the central brain of your land investing business?
In this conversation, Mike Balcom and I sit down with JT Olmstead to examine the AI workflows, API connections, and automation systems he has built around Stride CRM.
JT explains how his team consolidated data from multiple old CRMs, property research platforms, call transcripts, mapping tools, and internal databases into one organized system. He also shares how AI now builds many of the connections that previously required developers.
One of the biggest results was reducing lead intake work from roughly 20 minutes to as little as one or two minutes. Instead of copying property details between systems, the automation collects the data, organizes it, and prepares the lead so a team member can respond immediately.
We also discuss where AI should not be trusted. JT explains why land pricing remains too complex and risky to automate completely, how he decides when a human must remain in the loop, and why the best AI agents usually handle narrow administrative tasks.
You’ll learn:
- How to turn a CRM into a central business database
- How APIs connect land investing software
- Where AI agents can reduce administrative work
- Why speed to lead matters more than ever
- How AI can create consistent sales call notes
- Which business decisions still require human judgment
- How to choose your first automation project
- How feedback loops can improve AI performance
0:00 - Introducing JT’s AI-powered system
0:55 - Turning Stride into a master database
1:46 - Creating a central brain for deal data
3:05 - What happens when a new lead arrives
4:37 - Automated property research and enrichment
5:55 - External tools connected to Stride
6:10 - Replacing custom development with AI
8:33 - Building API connections without coding
11:02 - What AI agents and APIs actually mean
11:33 - When AI becomes reliable enough to trust
13:57 - Keeping humans in high-risk decisions
15:20 - What an AI agent really does
16:38 - Why agents work well for admin tasks
18:14 - Why humans still need to use the CRM
19:20 - Cutting lead intake from 20 minutes
20:41 - Eliminating administrative drag
21:22 - Creating automatic sales call notes
22:44 - AI can now solve problems, not just answer
24:33 - How to choose your first automation
26:13 - Problems AI still cannot solve well
26:58 - Why AI should not price land alone
29:39 - Using AI for rough valuation filters
31:50 - Advanced agent and framework design
33:29 - How AI feedback loops work
35:45 - Designing prompts before building systems
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