Katie uploaded a venue menu and asked ChatGPT to assemble complete lunch options around category counts, dietary restrictions, and the audience’s preferences. The model returned four themed combinations, reducing an estimated half-hour comparison task to about three minutes.

Upload the venue’s complete menu
State the required number of items in each category
Include dietary restrictions and cohesion requirements
Describe the guests whose preferences matter
Ask for several complete options rather than isolated dishes

“can you create four menus for me from this menu?”
Katie Haahr · 05:50

“So we went from 30 minutes down to three.”
Jasmine Star · 07:24

#event-planning#menus#dietary-restrictions#chatgpt

Tool07:28

Generate a Client’s Recurring Meeting Dates in Seconds

Instead of manually scanning a calendar and typing every other Tuesday, Katie asked ChatGPT to generate all dates between a start and end date. The finished list could immediately be sent to a client for confirmation, supporting a faster white-glove onboarding experience.

Specify the weekday and recurrence interval
Provide explicit start and end dates
Check the generated dates against a calendar
Send the complete proposed schedule at once

“can you give me every other Tuesday from start date to end date?”
Katie Haahr · 07:28

“And it was like, bang, there's the list.”
Katie Haahr · 07:28

#scheduling#calendar#client-experience#automation

Takeaway· 3

Takeaway03:02

Stop Overengineering Every ChatGPT Prompt

Katie says users do not need perfectly polished language before asking ChatGPT for help. She treats it like an assistant, states what she is thinking, and lets the exchange expose missing context or unclear instructions.

Use natural language instead of waiting for a perfect prompt
Let the model’s response reveal missing context
Refine the request conversationally

“With ChatGPT, I just kind of throw it in there.”
Katie Haahr · 03:14

“I don't try to be like, did I say that clearly? I just kind of say it.”
Katie Haahr · 03:14

#chatgpt#prompting#communication

Takeaway08:11

Why Fast, Specific Scheduling Feels Like White-Glove Service

Jasmine connects administrative speed with the perceived quality of a premium client experience. Quickly providing a precise schedule signals attentiveness and reduces unnecessary friction for busy founders.

Operational speed shapes the client’s first impression
Specific dates are more useful than vague scheduling promises
Automation can support personalization rather than diminish it

“how might we wow them immediately with quick, attentive and very specific times and dates?”
Jasmine Star · 08:11

#client-experience#service#scheduling#operations

Takeaway16:30

Build an AI Learning Loop With Other Entrepreneurs

Jasmine recommends sharing use cases with peers rather than experimenting in isolation. Regularly asking what others use AI for can expose practical applications faster and turn individual discoveries into collective leverage.

Connect with other active AI users
Exchange concrete use cases instead of abstract predictions
Share successful experiments back with the group
Use communities to accelerate discovery and adoption

“start seeing how you might be able to learn from each other.”
Jasmine Star · 16:30

“the more we get involved in other AI communities, the more that we're learning and leveraging.”
Jasmine Star · 16:43

#ai-adoption#peer-learning#entrepreneurs#community

Frameworks in this episode

AI-to-Expert Two-Yard-Line Review

Design-Constrained AI Copy Fitting

Siloed Virtual Coworker Method

Insights & moments

✦Tool· 2

Turning a Venue PDF Into Four Cohesive Event Menus

Generate a Client’s Recurring Meeting Dates in Seconds

▲Takeaway· 3

Stop Overengineering Every ChatGPT Prompt

Why Fast, Specific Scheduling Feels Like White-Glove Service

Build an AI Learning Loop With Other Entrepreneurs

Tool· 2

Takeaway· 3