Property management runs on conversations. BetterWho coaches the owners who run it, and shows them how to turn every call and walkthrough into knowledge their AI can use.
“As consultants, the most valuable use for us is once the meeting is done, Timeless imports into the database inside of Notion. Now we have the source of truth for our company and our meetings.”
Jay BerubeOwner, BetterWho
Challenge
In property management, the know-how is spoken, not written
Jay Berube spends his week with property management business owners. His firm, BetterWho, coaches and consults them, recruits their remote teams, and runs an AI mastermind where each owner builds their own AI sidekick. Beyond property management, Jay also does AI consulting for businesses and one-on-one coaching for owners in other industries.
He knows their days. Owners are stuck working in the business. The work happens on the phone, at the property and in person: owner calls, showings, move-out walkthroughs, vendor calls. Very little of it is on video, and almost none of it is written down.
That’s the catch with AI in this industry. The judgment that makes a good property manager good lives in their head and in their conversations. And most owners, Jay says, can’t keep up with which AI tool to use this month, let alone write a knowledge base for one.
“There’s so many changes in AI that are happening constantly that they don’t know, should I be using ChatGPT or Claude?”
Jay Berube, on his property management clients
The security deposit
A recorded interview became an AI’s rulebook
One of the owners in Jay’s mastermind wanted her AI to handle a job every property manager knows: security deposit returns. Do the move-out inspection, hand it to the AI, and get back what the return should be.
The model wasn’t the problem. The rules were. What counts as normal wear and tear, what she charges for what, and when she lets something go: none of it was written anywhere. It lived in her head, built over years of walkthroughs.
So Jay interviewed her on a recorded call, asking the questions a new hire would ask. Afterwards his AI went through the transcript, pulled out what her sidekick needed, and drafted the deliverables they had agreed on.
1 · Jay interviews the owner
Jay When is worn carpet your cost, not the tenant’s?Owner If it’s over five years old, I don’t charge for it.
Jay And holes in the walls?Owner Small nail holes are fine. Big anchors, I bill the patch, about $85 a wall.
recorded in Timeless
2 · Her rules, pulled from the call
1Carpet over 5 years old: no charge
2Small nail holes: normal wear, no charge
3Wall anchors: patch, $85 per wall
4Left dirty: professional cleaning, $120
written by AI from the transcript, not by her
3 · Her AI applies themMove-out inspection, Unit 4B
Deposit held$1,500
Professional cleaning rule 4−$120
Patch, bedroom wall rule 3−$85
Carpet, 8 years old rule 1$0
Deposit to return$1,295
How one recorded interview teaches an AI to draft deposit returns. Illustration: the questions, rules and amounts are examples, not the client’s.
“I just got off of a call with a coaching client. I interviewed her and just asked her a bunch of questions, and afterwards my AI goes in there and pulls the deliverables. It just takes a lot of work off of my plate.”
Jay Berube, Owner, BetterWho
The meeting wasn’t really a meeting. It was how an operator’s knowledge got written down, without her writing anything.
Where the knowledge lives
Every conversation an operator already has is a lesson for their AI
The deposit interview is one conversation. A property management business has dozens like it every week, and each one holds rules and context that never reach a system of record.
Said out loudThe AI it teachesProspective owner callShowing or leasing callInterview about move-outsVendor callOwner reviewTimelessOwner follow-upWhat owners ask, what wins themLeasing follow-upResident questions, what convertsDeposit returnsA BetterWho clientMaintenance triagePreferred vendors, prices, response timesOwner reportingDecisions, promises, who owns what
The conversations a property management business already has, and the AI each one can teach. Deposit returns comes from a BetterWho client; the rest are what operators can capture the same way.
The operator playbook
Take the call, tap record, find the work waiting
Jay’s rule for his clients is to skip the clever features and find the one use that sticks.
“If you can get people to use it, then you can start building out more use cases. But you have to find the simplest, most effective and unique use.”
Jay Berube, Owner, BetterWho
For property managers, he describes it like this.
The prospect calls. A prospective owner calls in. The call is captured, and the follow-up is based on what they actually asked.
The appointment. At the in-person meeting, the manager taps record in the Timeless app on their phone. Nothing else about the meeting changes.
Afterwards. The follow-up tasks and the deliverables from their templates are waiting, with nothing to type up.
RecordingOwner appointment24:18
1 the first callA prospective owner callsThe call is captured, and a follow-up goes out based on what the owner actually asked.
2 in personTap record at the appointmentThe manager opens the Timeless app on their phone. Nothing else changes about the meeting.
3 afterwardsThe work is already waitingFollow-up tasks and the deliverables from their templates, without typing anything up.
The workflow Jay proposes for property management operators.
The meeting is the prompt
Timeless feeds the tools BetterWho already runs on
BetterWho doesn’t treat a meeting as notes to go back and read. It treats every meeting as input. Timeless sends each transcript out to the tools the team already works in, and those tools do the work.
Every call into Notion. When a BetterWho call ends, Timeless sends the full transcript into a meetings database in Notion.
The Meeting Labeler. A Notion agent tags each transcript as internal, coaching or consulting.
The Task Finder. A second agent “will look for tasks and deliverables that were stated in the transcript, and then it will create those tasks,” Jay says.
The consulting co-pilot. Once a week, a scheduled Claude task reads every coaching call and looks across his property management clients for what came up.
1 · the callClient call ends
2 · timeless sends itThe transcript, as input
3 · notion · meetings database
WhenMeetingTypeTasks
Mon 9:00Weekly coaching · Client ACoaching3
Mon 11:30Team syncInternal5
Tue 14:00Ops review · Client BConsulting4
Wed 10:00AI mastermindCoaching2
Meeting Labeler sets the typeTask Finder creates the tasks
4 · every weekConsulting co-pilotClaude reads every coaching call and looks across clients.
How a BetterWho coaching call becomes work. Client names are anonymised.
That’s the pattern Timeless is built for. The same meeting memory is open through the Timeless API and MCP, so any tool, agent or workflow can take a conversation as its prompt: a Notion agent, a scheduled Claude task, or the property management software an operator already pays for.
What’s next
Less setup for operators who will never build an agent
Jay’s clients won’t wire up Notion agents, so his asks are about removing every step: tasks and the follow-up email straight from Timeless after a call, “without me having to have another AI involved,” prep for every recurring call, and a brief every morning.
Jay’s list
01Follow-ups straight from TimelessTasks and the follow-up email after a coaching call, “without me having to have another AI involved.”
02Prep for the recurring callSame client every week: what was covered last time and what is still open, before the call starts.
03A brief every morningToday’s meetings, with the history behind each one.
Jay’s list, in his words.
Bring Timeless to your property management business.
Capture the calls and walkthroughs you already have. Five meetings free, no card to start.
