Homa keeps their fee of $1,995 and credits back the difference to you (the buyer)I see how they are blending human support with Ai for efficiency.

Bc entropy sets in and as humans we all have a tendency to become lax with time.  

Obviously in real estate there is no replacement for human relationships, but daily, weekly and monthly repetitive tasks can be automated and the case for agents is strong.

Suspected human trafficking into our homes. 

The goal isn’t just enforcement — it’s reducing human error, cutting down disputes, and protecting NOI by making parking simpler and more transparent.I’m here to:• Learn from experienced investors and operators• Better understand the operational pain points owners face• Share insights from the parking/enforcement side of multifamilyFor those managing 50+ units — how are you currently handling parking registration and enforcement at your properties?

His human property manager oversees the AI agents and steps in when needed.

SOmetimes with Zelle venmo etc, as humans we can have a softside and not treat this like a business. 

We tested Monday and ended up building our ops around ClickUp as the system of record, with our PMS and automations feeding it.How we run STR ops (high level)PMS drives the truth (reservations, changes, cancellations).Automation pushes events into ClickUp so humans work from tasks, not inboxes.For example: Guesty → webhook → database layer → create/update ClickUp tasks for inquiries + reservations, with custom fields like check-in/out, guest, listing, status, conversation links, etcWe also automate “edge-case ops” like pool heat, early check-in, late checkout, pets, extra guests by generating subtasks/checklists off a request.Where Monday tends to feel greatFast to set up boards, very visual.Good for simple pipelines: turns, maintenance queues, onboarding checklists.Dashboards and “who owns what” is easy for teams that hate complexity.The biggest hurdles / limitations people hit with Monday in STR (in my experience)When the PMS needs to be the source of truthSTR is event-driven: reservation updates, cancellations, date changes, channel messages.If Monday is the “truth”, you end up reconciling drift constantly.Automation ceilingMonday automations are solid for basic triggers, but once you want “if X then create Y tasks, keep them in sync, dedupe, move between pipelines, update 15 fields, attach links”, you start wanting a real workflow engine + database.Data model constraintsSTR ops has “objects”: Reservation, Property, Guest, Work Order, Vendor, Owner, Conversation.Monday is board/item-first, so relationships can get awkward at scale unless you build a lot of glue.High-volume operational noiseHundreds of small updates (date changes, guest count changes, messaging, payments, add-ons) can turn boards into a scroll-fest unless you are very strict about what becomes an item vs a log.If someone is committed to Monday, this is the way I would set it upBoards by function, not by property:Reservations pipeline (pre-arrival, in-house, checkout, post-stay)Turns and housekeepingMaintenance and inspectionsOwner requests and approvalsOne unique ID field per reservation and treat it like a primary key.Use an integration layer (Zapier, Make, n8n, custom) so the PMS updates Monday automatically, not manually.Bottom lineMonday is awesome if your ops are mostly human-driven and you want speed + visibility.

What people want in this area of the business (STR) is humans.Look at the top STR coaches and they all say that the more you humanize your listing with personal videos and messages, the more you go up in revenue.

I've spent the last few months studying the Erie market intensely and I'm planning to do my first house flip within the next year or so.Here's where I'm at:Stable W2 income ($85K), aggressively saving toward a $35K+ war chest for my first dealTargeting cosmetic-rehab properties in Little Italy, West Bayfront, and the Academy area - $40K-$60K purchase price, $130K-$155K ARV rangeStudying sold comps, driving neighborhoods on weekends, and learning renovation skills through Habitat for Humanity and hands-on practicePlanning to use hard money financing for the first dealWhat makes me a little different: I'm using my AI/software engineering background to build deal analysis tools - automated comp pulling, ARV estimation, distressed property alerts, and rehab cost calculators.