Practical AI workflows you can try yourself
The Walkthrough is a video series showing how to use AI in a simple but useful way, with the AI chat tool of your choice. Each episode includes a free starter kit: the prompts, templates, and steps you need to try the workflow yourself.
Problem first
Each walkthrough starts with an operating question a leader already recognizes, then shows where AI can help.
Existing data
The workflows use the kinds of exports teams already have: CRM rows, job costs, notes, transcripts, invoices, and service history.
Try it yourself
Starter kits include the prompts and review steps so the viewer can run a lightweight version without buying anything.
Spot Service Agreement Churn Before the Non-Renewal Notice
Watch AI combine service visit history, AR data, and service notes to rank which agreements are at risk, why, and what's still saveable. Free starter kit included.
Diagnose Margin Leakage Across Your Closed Jobs
Watch AI analyze your job cost data to identify which jobs lost money, pinpoint the root causes, and surface what's still recoverable. Free starter kit included.
Is Your Team Chasing the Best Opportunities? Know for Sure.
See how AI turns scattered CRM data, call transcripts, and company news into a ranked priority list — with scores, evidence, and suggested next actions. Free starter kit included.
Frequently asked questions
What is The Walkthrough?
The Walkthrough is a practical video series showing how to use AI against familiar operating problems: expansion account prioritization, margin leakage, churn risk, and other decisions where the useful data is spread across systems.
Do I need a custom AI tool to try these workflows?
No. The public walkthroughs are designed for regular AI chat tools. Each starter kit includes prompts, data prep notes, and review guidance so you or someone on your team can try a lightweight version with exported data.
What kind of data do the walkthroughs use?
The examples use realistic synthetic data shaped like exports from CRM, job cost reports, service platforms, change order logs, project notes, transcripts, and similar systems. The point is to show what AI can do with the messy data operators already have.
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