The Digital Press

This article describes a personal AI factory setup where multiple AI agents collaboratively plan, execute, verify, and improve code generation workflows by iterating on inputs rather than fixing outputs.

Why it matters: This approach turns AI agents into self-improving collaborators, enabling scalable, automated code production and quality control.

The big picture: The system mimics a self-replicating factory, continuously refining prompts and plans to produce better code without manual patching.

The stakes: Inconsistent agent outputs and complexity of managing multiple AI agents could lead to architectural and style inconsistencies in large projects.

Commenters say: Readers seek more concrete examples and question practical scalability, emphasizing challenges in coordination, consistency, and subscription costs.