Mastering AI Workflow Orchestration: Build a Visual LLM Pipeline in 4,500 Lines

Building an AI Workflow Orchestrator in 4,500 Lines: The PaiAgent Story “ Can a two-week, one-person sprint yield a production-ready visual pipeline that chains LLMs and text-to-speech, survives real browsers, and still fits in one Git repo? Yes—if you treat the DAG engine like Lego bricks, not rocket science. 1. Why We Rolled Our Own DAG Engine Instead of Grabbing Activiti Question answered: “Why bother writing another topological sort when battle-tested engines exist?” Scope creep kills deadlines. Activiti, Camunda, Temporal bring history tables, event buses, cluster locks—overkill for “drag nodes, run in order, show logs”. Educational leverage. Implementing Kahn’s algorithm …