Anthropic 自研版本控制系统 Scion 替代 Git，应对日均 3 万次代码合并
Anthropic 日均合并 3 万次代码，Git 扛不住了，7 个人花五个月造了 Scion，还顺便聊了怎么用 Claude 和 GPT 互相挑错。
Anthropic 发文介绍为何自建替代 Git 的源码管理系统 Scion。2026 年 5 月他们日均合并约 2,500 次代码变更，到 9 月已超过 30,000 次。主分支历史接近 100 GB，压缩工作副本超过 25 GB，每日约 2,500 万次 CI 检出，若直接用 Git 每天将产生超过 600 PB 流量。新系统由 7 人团队开发，从 Git 迁移耗时五个月，Simon Willison 认为其架构类似 Subversion 的集中式版本控制。文中还提到他们的代码评审系统 Antique，以及对 Claude 和 GPT 做对抗式评审时需要工程师防止过度设计。
Redesigning source control at Anthropic Interesting piece from Anthropic describing why and how they built their own custom alternative to Git, based on the dramatic increase in rate of changes to their code after the past six months. In May 2026, Anthropic averaged around 2,500 code changes merged per day; as of September, we merged over 30,000 per day. They included a chart showing those changes. I had Claude modify their chart ( code here ) to add markers for the public releases of each of their models in 2026: This shows public release dates, not the date when models became available for Anthropic's internal use. My guess is that the introduction of Fable/Mythos class models is a key factor in the increased coding velocity. "Antique" is their new code review system. The source control system is called Scion, and sounds to me like a reinvention of centralized source control along the lines of Subversion. They had some pretty extreme requirements: The history of our main branch alone is almost 100 GB, and a compressed working copy is over 25 GB. We perform on the order of 25 million code checkouts per day for CI, before counting developer environments, agent sandboxes, and research jobs. Fetched naively, that would be over 600 PB of git traffic per day. The new system was built by a team of seven people, and the migration from Git was completed in five months. As an aside, I've been trying adversarial review in my own projects recently, where you have a model try and find flaws (I often play Claude and GPT off against each other). This note from the article reflected my own experience with that: Anthropic also makes extensive use of adversarial review, and, while this is incredibly effective in many ways, it can also be myopic, so skilled engineers needed to steer Claude away from over-engineering parts of the system in response to hypothetical concerns. Via Hacker News Tags: git , migrations , version-control , ai , generative-ai , llms , anthropic , agentic-engineering
