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Rohan Paul· @rohanpaul_ai · X·· 3 小时前AI 评分48
AI 导读

GitHarness 把智能体的每条需求与其对应工作像 Git commit 一样存储,并从最近的有效版本分支,让智能体在用户中途改需求时只重做变化部分。它在全部 30 个测试设置中均优于普通续写,其中 1 个设置下编程任务 token 用量减少 73.6% 且得分更高。用户很少一次给出完整规格,而多数智能体会沿用过期工作或全部重做。

正文

Treating agent memory like a Git repo, with commits and branches, lets agents drop outdated requirements and keep the work that is still valid.

Agents handle mid-task changes from users better when they save versions of their work and resume from the right one, so build that versioning into any agent that takes feedback.

Users rarely give a full spec upfront. They add, fix, or drop requirements as results come in. Most agents then carry stale work forward or redo everything.

GitHarness stores each requirement with its matching work, like Git commits, and branches from the closest valid version. It beat plain continuation in all 30 tested settings. In 1 setup, it used 73.6% fewer tokens on coding tasks while scoring higher.

When a user changes 1 detail, go back to the version that still fits and redo only what changed.

来源:Rohan Paul · x.com