This article compares pricing tiers, credit consumption, and hidden costs of four Chinese AI office agents—WorkBuddy, Doubao, Qwen, and Kimi—using real-world test data to reveal which paid tier truly sustains daily workflows without unexpected overages.
This article analyzes why industry AI projects become harder to cost as model prices drop, identifying four hidden cost categories—context preparation, continuous evaluation, exception handling, and accountability—and argues that sustainable AI systems require shifting focus from per-call pricing to the cost of an acceptable business outcome.
This article reveals why traditional budget-cutting fails in manufacturing, exposing 35% hidden costs, and presents a full-chain methodology with 22 indicators, daily management accounts, and digital dashboards to achieve sustainable cost reduction through value creation rather than mere savings.
The author reflects on the large gaps and hidden costs that hinder AI product adoption in non‑internet sectors, comparing AI software to traditional SaaS, questioning data‑driven moats, and outlining practical steps to bridge these challenges.
