In 2025 Master Kong’s tea drinks generated 206.03 billion yuan, a 5.1% decline, despite launching nearly ten new iced‑tea flavors, because its digital channel system failed to close the data loop, preventing profit from reaching terminal stores and limiting effective product decisions.
The article recounts a failed AI‑powered feature launch, explains why users care about concrete problem‑solving rather than flashy AI, defines a rigorous scenario formula, outlines a five‑step traditional scenario‑analysis SOP, adds five AI‑specific dimensions, and provides a one‑page canvas to help product managers turn AI hype into real user value.
This presentation outlines the development of ChatGPT, the underlying principles of large language models, and how they empower new industrialization in automotive manufacturing, detailing practical implementations, agent architectures, data and model closed loops, and case studies such as intelligent inspection and G8D agents.
