Vibe Coding、Cursor、Claude Code、Codex、Copilot
This collection features articles and community discussions in the AI 编程 space, focusing on real-world engineering scenarios, tool selection, practical paths, and risk boundaries.
The page is continuously updated and serves as a learning roadmap, technology selection reference, and technical review entry point.
Cursor and Claude Code are 2026's two most mainstream AI coding tools, but their form factors and philosophies differ—one is IDE-native, the other a terminal agent. This article compares them across form factor, context, agent capability, MCP ecosystem, collaboration style, and pricing, gives a who-uses-which conclusion, and explains why many use both.
You burned $50K in tokens in a month but can't say which feature or user did it — that's no cost attribution. Learn how to attribute AI cost via request tagging, token metering and aggregation, unit economics (per-user/per-feature cost), and anomaly detection, turning AI cost from an opaque ledger into something optimizable and accountable.
Whether a user experiences value in the first minute decides an AI product's retention. This article covers AI onboarding core: shortening TTFV, guiding the first "aha" moment, avoiding information overload, progressive disclosure, lowering the barrier with templates, and driving optimization with activation metrics.