How do you translate 90-day EOS Big Rocks into AI vibe coding infrastructure for property management?

Question

Tyler Smith · Accepted Answer

Translating EOS Big Rocks into software infrastructure begins by discarding rigid 12-month roadmaps in favor of vibe coding, a natural-language, test-driven approach to software creation. In property management companies running on EOS, a quarterly Rock might state: 'Automate tenant maintenance intake and dispatch by end of Q2.' Rather than hiring traditional software consultancies that overcomplicate requirements, the business visionary or integrator vibe codes a dedicated solution using Anthropic-style prompt chaining and edge compute.

First, break down the Rock into composable agentic patterns as outlined in AI Agent Design Patterns. Use an orchestrator-worker workflow where incoming tenant maintenance requests arrive via a conversational web interface. An initial LLM classifies the urgency of the work order, runs programmatic checks, and routes the ticket to specialized worker models. Non-urgent issues generate automated triage tickets in Supabase, while critical hazards (such as water leaks) trigger real-time Twilio webhooks to preferred vendor dispatchers.

Second, enforce discipline using Eval Driven Development. As detailed in Debugging AI Agents & LLM Applications, treat your property intake workflow like an evolving product. Build deterministic unit tests around vendor matching rules, tenant validation, and property address verification. When an edge case fails, such as an ambiguous description of HVAC failure, log the trace and write a scoped unit test.

By uniting the quarterly accountability of EOS Rocks with lightweight, vibe-coded microservices, mid-market operators deploy custom infrastructure in 14 days rather than nine months, keeping overhead lean while hitting quarterly commitments reliably.