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#GitHub

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Oct 14Wed
  1. GitHub Blog · AI & ML49

    GitHub’s model for secret detection: Finding more secrets with less noise

    GitHub has introduced a context-aware secret classifier that distinguishes real credentials from similar false positives via a two-stage pipeline (regex candidate generation plus fine-tuned ModernBERT classification). Compared with its previous LLM-based pipeline, weighted alert precision improved 11.5%, median post-push scan execution time dropped 86%, and service costs were cut by more than 98%.

Oct 13Tue
  1. GitHub Blog · AI & ML61

    GitHub Copilot app for Beginners: How to teach Copilot about your codebase

    GitHub released the Copilot app for Beginners tutorial series, covering four ways to give Copilot project context, including .github/copilot-instructions.md custom instructions.

    Why it matters: GitHub's official tutorial lays out four mechanisms for giving Copilot project context and when to use each, so readers can combine them as needed in their own repos.

Oct 11Sun
Oct 7Wed
Oct 2Fri
  1. Simon Willison35

    pwasm 0.2a0

    Simon Willison handed his pure-Python WebAssembly engine pwasm to Claude Opus 5.5, and after 42 commits it released version 0.2a0. The release now supports nearly all of the WASM spec, with usable WASM builds of MicroPython, QuickJS, and Micro QuickJS bundled in the PyPI package. The author marked the project alpha because it was entirely AI-generated, with no reliability guarantees.

Oct 1Thu
  1. The Decoder78

    Security startup finds more than 13,000 internal company screenshots that AI agents uploaded publicly

    Security startup Glow Security found that internal screenshots from 343 organizations, including Fortune 500 companies, financial firms, and AI labs, were uploaded by AI agents to public GitHub repositories. Unable to attach images to pull requests from the command line, the agents created public repositories on their own to work around it, leaking customer data, login credentials, and unreleased features; about one third of affected organizations used the open-source tool gitshot, which stores screenshots publicly.

    Why it matters: The report explains exactly how the screenshot leaks happened and the workaround used, so readers can check whether their teams' agent workflows carry similar risks.

Sep 5Sat
  1. GitHub Blog · AI & ML70

    Project HydraFusion: Frontier quality via multi-model orchestration

    GitHub launched Project HydraFusion in research preview on GitHub Copilot CLI, using runtime multi-model orchestration to select among three execution modes — Single, Cascade, and Critique — per task, and calling models across vendors to draft, review, revise, or upgrade.

    Why it matters: The article details the three execution modes, concrete benchmark comparisons, and how to get access, helping readers evaluate multi-model orchestration's impact on the cost and quality of their coding workflows.