📁GreenLine — chandlerOS
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GreenLine

GreenLine is a full-stack lawn care business platform built end-to-end by the Ralph autonomous build system. It demonstrates what's possible when a well-designed AI pipeline handles the full development lifecycle.

Next.jsFastAPIGraphQLPostgreSQLDockerAutonomous Build
Overview

GreenLine is a complete lawn care business platform — customer management, job scheduling, invoicing, and route optimization — built entirely by Ralph, an autonomous AI build pipeline. The project served as the proof-of-concept that validated Ralph's ability to ship a full product from spec to deployed application without manual coding.

Key Features
  • Customer management with service history and contact tracking
  • Job scheduling with calendar views and technician assignment
  • Invoicing and payment tracking
  • Route optimization for service crews
  • Client portal for viewing upcoming appointments and invoices
  • Admin dashboard with business analytics
  • User authentication and role-based access control
  • Mobile-responsive design for field use
Tech Stack
Frontend
  • Next.js 15
  • TypeScript
  • Tailwind CSS
  • Apollo GraphQL Client
Backend
  • FastAPI
  • Strawberry GraphQL
  • PostgreSQL
  • Docker
Build System
  • Ralph autonomous pipeline
  • Claude Code
  • n8n orchestration
  • Bash
Infrastructure
  • Oracle Cloud Infrastructure
  • Docker Compose
  • Nginx reverse proxy
Challenges & Solutions
Autonomous Story Decomposition

Ralph had to decompose a high-level product spec into 28 individually testable user stories, implement each one, verify acceptance criteria, and move to the next — all without human intervention or manual code review.

Cross-Machine Orchestration

The build pipeline ran across multiple machines connected via Tailscale mesh network, with n8n monitoring workflows, Discord notifications, and remote SSH execution coordinated from an OCI server.

Maintaining Coherence Across 28 Stories

Ensuring that code written for story 28 remained consistent with architectural decisions made in story 1 — without a human reviewing every PR — required careful state management in the pipeline.

Outcomes
  • Shipped a complete, functional lawn care platform across 28 user stories with zero manual coding
  • Validated the Ralph autonomous build pipeline as capable of end-to-end product development
  • Demonstrated that a well-structured spec + autonomous pipeline can replace weeks of manual development
  • Produced production-quality code that follows consistent patterns throughout the codebase
GreenLine — 6 technologies