Using AI‑assisted coding, Qunar’s team transformed a 150,000‑line high‑concurrency core system, tackling system‑level uncertainties through a harness‑and‑loop framework, achieving roughly 70% faster delivery, 70% lower latency, 45% resource savings, and a fault‑free launch without QA intervention.
The article explains that the instability of AI‑generated code stems from treating programming as a stateless conversation, and introduces Harness Engineering—a 2025‑born methodology that externalizes decisions to files, structures work into staged processes, and atomizes tasks to make AI coding repeatable, auditable and evolvable, while outlining emerging frameworks and a 12‑part learning path.
The article argues that the rise of AI‑driven code generation demands a three‑stage Software Engineering 3.0 methodology—context, steering, and knowledge engineering—to turn massive efficiency gains into trustworthy, scalable production systems, making it essential for competitive enterprises.
In this talk, chief architect Li Yanpeng shares his career background, outlines the goals and design principles of distributed service architecture—including high availability, performance, scalability, extensibility, security, and consistency—and offers a methodology for cultivating both technical and personal inner skills for engineers.
