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RadarAI· Simon Willison 博客·· 7 小时前AI 评分60

GitHub Octoverse 2026：月度合并 PR 一年内增至 2.2 亿

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GitHub EVP Jay Parikh 在 GitHub Universe 发布 Octoverse 2026 报告，月度合并 PR 在不到一年内增至 2.2 亿，月度 commit 增至 73.8 亿，每月新仓库翻倍至 3030 万。

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Simon Willison 博客·2026-10-29 00:45· 53 分钟前AI 评分65

GitHub Octoverse 2026

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Simon Willison 在 GitHub Universe 现场记录 Jay Parikh 发布的 Octoverse 2026 报告数据：2026 年月度合并 PR 一年内增至 2.2 亿，月度 commit 增至 73.8 亿，每月新仓库翻倍至 3030 万，作者称这直观体现了智能体工程对 GitHub 的影响。

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GitHub Octoverse 2026

I'm at GitHub Universe today (GitHub gave me a free ticket through their "GitHub Stars" program). EVP Jay Parikh just announced this year's Octoverse report, and highlighted these numbers in particular:

Photo of a conference keynote stage: a wide curved screen shows three line charts side by side, with a speaker in a black sweater and dark jeans standing at its right edge beneath an overhead lighting rig. Each chart has a large colored headline number above it and a shaded line that runs low and nearly flat across the left side, then curves sharply upward on the right to end in a dot at its peak. Left, in green: "220M" "Merged PRs per month", y-axis 0M, 50M, 100M, 150M, 200M. Middle, in magenta: "7.38B" "Commits per month", y-axis 0B, 2B, 4B, 6B, with the most dramatic, almost vertical final spike. Right, in orange: "30.3M" "New repos per month", y-axis 0M, 10M, 20M, 30M, with a bumpier, more gradual climb. All three share the x-axis labels '23, '24, '25, '26.

This is a pretty stark representation of the impact of agentic engineering on GitHub. In 2026, merged pull requests tripled in less than a year to 220 million per month. Commits more than tripled to 7.38 billion per month, with most of that increase in the second half of this year. New repository rate doubled this year, to 30.3 million per month.

The report includes new numbers by industry, and breaks out numbers for repositories that involve "interoperability or reverse engineering". The methodology section includes notes about how they did this:

Top countries by pushes to public repositories, adjusted by profile location. Pushes from each country were summed across the Octoverse year. To adjust for biases caused by VPN usage, LLM classification was used to extract the ISO 3166-1 alpha-2 code from the profiles of GitHub users who contributed pushes during this period [...]

Industry. Public repositories created 2022 to 2026 were sorted into NAICS sectors by a fine-tuned multilingual embedding model using name, description, topics, and README, from random samples per year. [...]

Interoperability. Counts public repositories created each year whose name, description, topics, or README mention interoperability or reverse engineering, or related terms, such as clean room implementation, drop-in replacement, or protocol re-implementation.

Tags: github, ai, generative-ai, llms, coding-agents, disclosures, agentic-engineering

来源：Simon Willison 博客 · simonwillison.net

来源：RadarAI · aihot.news

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