Claude Code 额度回落：Agent 正在制造新的「祖传代码屎山」？

TL;DR - The article argues that coding agents’ token costs and long-term code quality share a root cause: implementation persists exactly, while the design rationale behind it is progressively compressed or forgotten. This mismatch can turn locally reasonable agent edits into opaque technical debt over long sessions.

• Agent cost depends on the number of tool-and-reasoning steps multiplied by the growing working context, not on the final diff size.
• Context compaction, memory, prompt caching, and sub-agents reduce different kinds of overhead but can discard evidence or design constraints needed later.
• Lost rationale can produce “AI legacy code,” where later agents add queues, retries, caches, or bypasses without understanding the original architectural model.
• Critical constraints should be preserved as executable invariants—types, tests, dependency rules, linters, and CI checks—rather than relying only on conversational memory.