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GitHub Octoverse 2026: Agentic Engineering Drives 5x Commit SurgeSimon Willison 博客T2·Industry

GitHub Octoverse 2026: Agentic Engineering Triples Merged PRs

Original title: GitHub Octoverse 2026
78AI Score

GitHub's 2026 Octoverse report reveals that agentic engineering has driven monthly merged pull requests to triple within a year, reaching 220 million, with commits hitting 7.38 billion. This surge signifies AI coding agents have transitioned from auxiliary tools to core drivers of the software development lifecycle.

Full Report

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.

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