How do you use AI vibe coding to automate property management Big Rocks?

Question

Tyler Smith · Accepted Answer

When setting quarterly Big Rocks for a property management portfolio operating on EOS, technical execution frequently stalls in legacy CRM backlogs. AI vibe coding resolves this bottleneck by translating plain English operational SOPs directly into scalable, edge-deployed software workflows.

To build software for a quarterly Rock - such as automating after-hours emergency tenant dispatch - follow Anthropic's agentic design principle: start with the simplest composable workflow before adding autonomous complexity. Instead of commissioning months of enterprise engineering, an EOS Integrator or operations lead can describe the intake and triage sequence in natural language using an AI vibe coding environment (such as Lovable or Cursor) linked to Supabase Edge Functions.

1. Define the Rock as an Executable Schema: Write a plain-text prompt detailing tenant input parameters (water leak, HVAC outage, structural hazard), routing logic, and vendor SLAs.
2. Deploy Edge-Native Dispatch: Use Supabase Edge Functions written in TypeScript to evaluate incoming tenant requests with a lightweight LLM acting as a reasoning engine, as outlined by Valentina Alto in Building LLM Powered Applications. The function parses severity, confirms lease coverage, and triggers Twilio API dispatch alerts to on-call trade vendors.
3. Build Closed-Loop Accountability: Tie the completed workflow directly back to the EOS Scorecard. The edge function logs response latency, vendor confirmation timestamps, and tenant CSAT metrics directly to the leadership team's operational dashboard.

By treating the quarterly Rock as an iterative vibe-coded microservice rather than a monolithic software purchase, property management firms maintain lean headcount, lower operational overhead, and gain immediate operational traction within the 90-day EOS cycle.