From prototype to production: lessons learned taking AI-built software to enterprise scale

This post details the evolution of an AI-driven software development process from a prototype to an enterprise-grade product. It describes the initial multi-agent orchestration for building a prototype, including a planner, coder, and reviewer agent, and the subsequent challenges encountered during production deployment, such as schema differences and lack of architectural guidance. The team iterated by adopting a 'build one feature end-to-end' approach, followed by a more robust 'understand and plan first, then execute' methodology. This involved developing an interactive planner and a PR review buddy to address gaps in domain understanding and improve review efficiency. The post quantifies a 5x output gain compared to traditional builds and outlines key lessons learned, including the importance of human ownership of domain and decisions, treating agents as teammates, and the value of upfront planning and custom tooling.