プロと読み解くRuby 3.4 NEWS テクノロジー部門技術基盤グループの笹田（ko1）と遠藤（mame）です。Ruby (MRI: Matz Ruby Implementation、いわゆる ruby コマンド) の開発をしています。お金をもらって Ruby を開発しているのでプロの Ruby コミッタです。 本日 12/25 に、恒例のクリスマスリリースとして、Ruby 3.4.0 がリリースされました（Ruby 3.4.0 リリース ）。今年も STORES Product Blog にて Ruby 3.4 の NEWS.md ファイルの解説をします（ちなみに、STORES Advent Calendar 2024 の記事になります。他も読んでね）。NEWS ファイルとは何か、は以前の記事を見てください。 プロと読み解く Ruby 2.6 NEWS ファイル - クックパッド開発者
Don't write clean code, write CRISP code — Bitfield Consulting
I’m sure we’re all in favour of “clean code”, but it’s one of those motherhood-and-apple-pie things that no one can reasonably disagree with. Who wants to write dirty code, unless maybe it’s for a porn site? The problem, of course, is that few of us can agree on what “clean code” means, and how to get there. A rule like “methods should only do one thing”, looks great on a T-shirt, but it’s not so
Developers are increasingly relying on AI coding assistants to accelerate our daily workflows. These tools can autocomplete functions, suggest bug fixes, and even generate entire modules or MVPs. Yet, as many of us have learned, the quality of the AI’s output depends largely on the quality of the prompt you provide. In other words, prompt engineering has become an essential skill. A poorly phrased
GitHub - modelcontextprotocol/servers: Model Context Protocol Servers
Official integrations are maintained by companies building production ready MCP servers for their platforms. 21st.dev Magic - Create crafted UI components inspired by the best 21st.dev design engineers. 2slides - An MCP server that provides tools to convert content into slides/PPT/presentation or generate slides/PPT/presentation with user intention. ActionKit by Paragon - Connect to 130+ SaaS inte
This post is about why we need a coroutine package for Go, and what it would look like. But first, what are coroutines? Every programmer today is familiar with function calls (subroutines): F calls G, which stops F and runs G. G does its work, potentially calling and waiting for other functions, and eventually returns. When G returns, G is gone and F continues running. In this pattern, only one fu
January 30, 2023 In this post, we'll implement a GPT from scratch in just 60 lines of numpy. We'll then load the trained GPT-2 model weights released by OpenAI into our implementation and generate some text. Note: This post assumes familiarity with Python, NumPy, and some basic experience with neural networks. This implementation is for educational purposes, so it's missing lots of features/improv
PacketProxyで探るGemini CLIのコンテキストエンジニアリング 〜AIエージェントを信頼できる相棒に〜 | BLOG - DeNA Engineering
2025.07.18 技術記事 PacketProxyで探るGemini CLIのコンテキストエンジニアリング 〜AIエージェントを信頼できる相棒に〜 by akira.kuroiwa #gemini-cli #ai #security #ai-agent #context-engineering #packetproxy 「なんかよく分からないけど、すごい」で終わらせないために こんにちは、DeNA セキュリティ技術グループの 黒岩 亮 ( @kakira9618 ) です。 AIエージェント、とくに Gemini CLI のようなコーディングを支援してくれるツールは非常に強力で、私たちの開発体験を大きく変えようとしています。しかし、その一方で、こんな風に感じたことはありませんか？ 「このファイルの情報、勝手にAIに送られたりしない？ 大丈夫かな？」 と、情報管理・セキュリティ面で漠然と
巨人の肩に乗る
本記事は 仮想通貨 Advent Calendar 2025 の24日目の記事です。 はじめに はじめまして、ymdと申します。普段は、株や暗号資産の分析をし、マーケットが盛り上がったときに落ちているお金を拾っています。 今年のAdvent Calendarを眺めていると、DEXの分析やLLMを活用した自動トレード戦略作成など、非常に有益な記事が目白押しです。 これらを見て思い出したのが、ニュートンの「巨人の肩に乗る」という言葉。本記事では、この精神に倣い、AIの力と先人の知見という2つの「肩」を借りながら、お金拾いの方法を探っていきます。 AIの肩に乗る AI駆動開発の3つのアプローチ AIを活用した開発には、大きく3つの方向性があります： 情報収集の自動化：論文や API ドキュメントの要約 戦略生成の自動化：複数のアプローチを並行生成 コーディングの自動化：コードそのものを AI に
I'm about to share a lengthy tale that begins with Apache OpenDAL™ op.read() and concludes with an unexpected twist. This journey was quite enlightening for me, and I hope it will be for you too. I'll do my best to recreate the experience, complete with the lessons I've learned along the way. Let's dive in! All the code snippets and scripts are available in Xuanwo/when-i-find-rust-is-slow TL;DR Ju
What We Learned from a Year of Building with LLMs (Part I)
It’s an exciting time to build with large language models (LLMs). Over the past year, LLMs have become “good enough” for real-world applications. The pace of improvements in LLMs, coupled with a parade of demos on social media, will fuel an estimated $200B investment in AI by 2025. LLMs are also broadly accessible, allowing everyone, not just ML engineers and scientists, to build intelligence into
Assessing Claude Mythos Preview’s cybersecurity capabilities April 7, 2026 Nicholas Carlini, Newton Cheng, Keane Lucas, Michael Moore, Milad Nasr, Vinay Prabhushankar, Winnie Xiao Hakeem Angulu, Evyatar Ben Asher, Jackie Bow, Keir Bradwell, Ben Buchanan, David Forsythe, Daniel Freeman, Alex Gaynor, Xinyang Ge, Logan Graham, Kyla Guru, Hasnain Lakhani, Matt McNiece, Mojtaba Mehrara, Renee Nichol, A
こんにちは、NTTドコモR&D戦略部の門間です。 この記事では、vLLMのコードを追いつつその中身の動きに迫りたいと思います。 最近、業務やプライベートでLLM関連のいろいろを触っていますが、 OSSのコードリーディングを通じてLLMの推論処理への理解を深めたいというモチベーションです。 🤖 vLLMって? 📚 前提知識 Attention Is All You Need Paged Attention Continuous Batching 📦 vLLMの開発用インストール (Pythonコード開発のみ) Wheelのインストール リポジトリのクローン 起動確認 Pythonコードの改変 デバッガを使ったOSSのコードリーディングのススメ 🧩 vLLMのソフトウェアアーキテクチャ オンライン推論 : FastAPIサーバの立ち上げとEngineClientの生成 1. Engin
1 Billion nested loop iterations
Methodology Timings taken via hyperfine on an M3 Macbook pro with 16 gb RAM. Input value of 40 given to each. Swift version: swift-driver version: 1.115 Apple Swift version 6.0.2 (swiftlang-6.0.2.1.2 clang-1600.0.26.4) Clang version: Apple clang version 16.0.0 (clang-1600.0.26.4) Fortran version: GNU Fortran (Homebrew GCC 14.2.0_1) 14.2.0 R version: Rscript (R) version 4.4.2 (2024-10-31) Kotlin ve
TL;DR; We are changing std::sort in LLVM’s libcxx. That’s a long story of what it took us to get there and all possible consequences, bugs you might encounter with examples from open source. We provide some benchmarks, perspective, why we did this in the first place and what it cost us with exciting ideas from Hyrum’s Law to reinforcement learning. All changes went into open source and thus I can
31st December 2024 A lot has happened in the world of Large Language Models over the course of 2024. Here’s a review of things we figured out about the field in the past twelve months, plus my attempt at identifying key themes and pivotal moments. This is a sequel to my review of 2023. In this article: The GPT-4 barrier was comprehensively broken Some of those GPT-4 models run on my laptop LLM pri
Gamedev in Lisp. Part 1: ECS and Metalinguistic Abstraction - cl-fast-ecs by Andrew
Gamedev in Lisp. Part 1: ECS and Metalinguistic Abstraction In this series of tutorials, we will delve into creating simple 2D games in Common Lisp. The result of the first part will be a development environment setup and a basic simulation displaying a 2D scene with a large number of physical objects. It is assumed that the reader is familiar with some high-level programming language, has a gener
Internet Engineering Task Force (IETF) K. Davis Request for Comments: 9562 Cisco Systems Obsoletes: 4122 B. Peabody Category: Standards Track Uncloud ISSN: 2070-1721 P. Leach University of Washington May 2024 Universally Unique IDentifiers (UUIDs) Abstract This specification defines UUIDs (Universally Unique IDentifiers) -- also known as GUIDs (Globally Unique IDentifiers) -- and a Uniform Resou
Update 1.69.1: The update addresses these issues. Update 1.69.2: The update addresses these issues. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the June 2022 release of Visual Studio Code. There are many updates in this version that we hope you'll like, some of the key highlights include: 3-way merge editor - Resolve merge conflicts wit
Golang Mini Reference 2022: A Quick Guide to the Modern Go Programming Language (REVIEW COPY)
Golang Mini Reference 2022 A Quick Guide to the Modern Go Programming Language (REVIEW COPY) Harry Yoon Version 0.9.0, 2022-08-24 REVIEW COPY This is review copy, not to be shared or distributed to others. Please forward any feedback or comments to the author. • feedback@codingbookspress.com The book is tentatively scheduled to be published on September 14th, 2022. We hope that when the release da
Agents
Intelligent agents are considered by many to be the ultimate goal of AI. The classic book by Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (Prentice Hall, 1995), defines the field of AI research as “the study and design of rational agents.” The unprecedented capabilities of foundation models have opened the door to agentic applications that were previously unimaginabl
AST vs. Bytecode: Interpreters in the Age of Meta-Compilation
233 AST vs. Bytecode: Interpreters in the Age of Meta-Compilation OCTAVE LAROSE, University of Kent, UK SOPHIE KALEBA, University of Kent, UK HUMPHREY BURCHELL, University of Kent, UK STEFAN MARR, University of Kent, UK Thanks to partial evaluation and meta-tracing, it became practical to build language implementations that reach state-of-the-art peak performance by implementing only an interprete
Parsing SQL - Strumenta
The code for this tutorial is on GitHub: parsing-sql SQL is a language to handle data in a relational database. If you worked with data you have probably worked with SQL. In this article we will talk about parsing SQL. It is in the same league of HTML: maybe you never learned it formally but you kind of know how to use it. That is great because if you know SQL, you know how to handle data. However
How I developed a faster Ruby interpreter | Red Hat Developer
In this article, I will describe my efforts to implement a faster interpreter for CRuby, the Ruby language interpreter, using a dynamically specialized internal representation (IR). I believe this article will interest developers trying to improve the interpreter performance of dynamic programming languages (e.g., CPython developers). I will cover the following topics: Existing CRuby interpreter a
Masato Hagiwara Open in Recto Pad Google Colab Github Recto Pad TL;DR Recto is a 2D programming language that uses nested rectangles as its core syntax, encoding structure and recursion directly in space instead of a linear stream of text. Recto explores new ways to write, parse, and reason about code—and even natural language—spatially. Introduction Open in Recto Pad Virtually all the languages w
Show navigation A recent article on WebAssembly Garbage Collection (WasmGC) explains at a high level how the Garbage Collection (GC) proposal aims to better support GC languages in Wasm, which is very important given their popularity. In this article, we will get into the technical details of how GC languages such as Java, Kotlin, Dart, Python, and C# can be ported to Wasm. There are in fact two m
Update 1.80.1: The update addresses these issues. Update 1.80.2: The update addresses this security issue. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the June 2023 release of Visual Studio Code. There are many updates in this version that we hope you'll like, some of the key highlights include: Accessibility improvements - Accessible V
Agent Skills対応Agentを作ろう｜はち
1. はじめに2025年末にAnthropicがAgent Skillsという機能をオープンスタンダード化し、Xなどでもよく話題になっていると思います。MCP然りでAnthropicはこういったスタンダード化をするのが上手いなと感心させられます。 色々議論されていると思いますが、Agentの開発を行っている私的にAgent Skillsのメリットは以下の2点だと考えています。 再利用性：1度作ったSkillを別エージェントでも使いやすい。 段階的開示(progressive disclosure)：そのSkillが必要になったときだけその詳細やスクリプトについてAgentが読み込むことができる。（プロンプトの圧縮につながる。） AnthropicとしてはあくまでClaude CodeやClaude APIでできることを増やしたいがためのオープンスタンダード化ということなのか、自作Agent
Over the course of my Spring 2020 semester at Harvey Mudd College, I developed a self-hosting compiler entirely from scratch. This article walks through many interesting parts of the project. It’s laid out so you can just read from beginning to end, but if you’re more interested in a particular topic, feel free to jump there. Or, take a look at the project on GitHub. Table of contents What the pro
Codestral | Mistral AI
Empowering developers and democratising coding with Mistral AI. We introduce Codestral, our first-ever code model. Codestral is an open-weight generative AI model explicitly designed for code generation tasks. It helps developers write and interact with code through a shared instruction and completion API endpoint. As it masters code and English, it can be used to design advanced AI applications f
Patterns for Building LLM-based Systems & Products [ llm engineering production 🔥 ] · 66 min read Discussions on HackerNews, Twitter, and LinkedIn “There is a large class of problems that are easy to imagine and build demos for, but extremely hard to make products out of. For example, self-driving: It’s easy to demo a car self-driving around a block, but making it into a product takes a decade.”
Join a VS Code Dev Days event near you to learn about AI-assisted development in VS Code. Update 1.70.1: The update addresses these issues. Update 1.70.2: The update addresses these issues. Update 1.70.3: This update is only available for Windows 7 users and is the last release supporting Windows 7. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welc
A Walk with LuaJIT
The following is a chronicle of implementing a general purpose zero-instrumentation BPF based profiler for LuaJIT. Some assumptions are made about what this entails and it may be helpful to read some of our other work in this area. One major change from prior efforts is that instead of working with the original Parca unwinder we are now working with the OpenTelemetry eBPF profiler. If you missed t
This post is an account of why I prefer using the attrs library over Pydantic. I'm writing it since I am often asked this question and I want to have something concrete to link to. This is not meant to be an objective comparison of attrs and Pydantic; I'm not interested in comparing bullet points of features, nor can I be unbiased since I'm a major contributor to attrs (at time of writing, second
What's new in Python 3.11?
What's new in Python 3.11?Built-in TOML support, better exceptions, and typing improvements. By Tushar·InsightsPython The first beta release of Python 3.11 is out, bringing some fascinating features for us to tinker with. This is what you can expect to see in 2022's release of Python later this year. Even better error messagesPython 3.10 gave us better error messages in various regards, but Python
Bringing the power of AI to Windows 11 – unlocking a new era of productivity for customers and developers with Windows Copilot and Dev Home
Bringing the power of AI to Windows 11 – unlocking a new era of productivity for customers and developers with Windows Copilot and Dev Home The team and I are pumped to be back at Build with the developer community this year. Over the last year, Windows has continued to see incredible growth fueled by Windows 11 adoption. In fact, one of the most exciting areas driving that growth for Windows has
Building the fastest Lua interpreter.. automatically!
This is Part 1 of a series of posts. Part 2 is available here: Building a baseline JIT for Lua automatically It is well-known that writing a good VM for a dynamic language is never an easy job. High-performance interpreters, such as the JavaScript interpreter in Safari, or the Lua interpreter in LuaJIT, are often hand-coded in assembly. If you want a JIT compiler for better performance, well, you’
Tier 4 Support § Support for these targets is entirely experimental. If this target is provided by LLVM, LLVM may have the target as an experimental target, which means that you need to use Zig-provided binaries for the target to be available, or build LLVM from source with special configure flags. zig targets will display the target if it is available. This target may be considered deprecated by
cuTile Pythonで始めるGPUプログラミング & 倍精度行列積(DGEMM)エミュレーションを実装してみた。 - Insight Edge Tech Blog
こんにちは、Insight Edgeでデータサイエンティストをしている新見です。 cuTile Pythonとは 背景 特徴 従来のCUDA（SIMT）との違い 文法 TileGymで行列積ベンチマーク 倍精度行列積エミュレーション Ozaki Schemeについて 分解(Split) 行列積の計算 素朴な実装と初回結果 最適化 Fast Mode（GEMMの削減） Fused Split Kernel（分割の融合） 最適化後の結果 dによる精度/速度トレードオフ まとめ 参考文献 今回はNVIDIAが発表したばかりの「cuTile Python」を試してみました。普段は、GPUカーネルを業務で書くことはありませんが、cuTileはPythonで書かれていて、文法もシンプルなようなので、GPUプログラミングの勉強の意味も含めて記事にしました。 cuTile Pythonとは cuTile
Real-world gen AI use cases from the world's leading organizations | Google Cloud Blog
AI is here, AI is everywhere: Top companies, governments, researchers, and startups are already enhancing their work with Google's AI solutions. Published April 12, 2024; last updated October 9, 2025. Automotive & Logistics Business & Professional Services Financial Services Healthcare & Life Sciences Hospitality & Travel Manufacturing, Industrial & Electronics Media, Marketing & Gaming Public Sec
How a simple Linux kernel memory corruption bug can lead to complete system compromise
In this case, reallocating the object as one of those three types didn't seem to me like a nice way forward (although it should be possible to exploit this somehow with some effort, e.g. by using count.counter to corrupt the buf field of seq_file). Also, some systems might be using the slab_nomerge kernel command line flag, which disables this merging behavior. Another approach that I didn't look
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プロと読み解くRuby 3.4 NEWS - STORES Product Blog
The Prompt Engineering Playbook for Programmers
research!rsc: Coroutines for Go
GPT in 60 Lines of NumPy | Jay Mody
Rust std fs slower than Python!? No, it's hardware!
Claude Mythos Preview \ red.anthropic.com
📖 vLLMのコードを読んでみよう - ENGINEERING BLOG ドコモ開発者ブログ
Changing std::sort at Google’s Scale and Beyond
Things we learned about LLMs in 2024
RFC 9562: Universally Unique IDentifiers (UUIDs)
June 2022 (version 1.69)
Recto — a truly 2D language
A new way to bring garbage collected programming languages efficiently to WebAssembly · V8
June 2023 (version 1.80)
Kalyn: a self-hosting compiler for x86-64
Patterns for Building LLM-based Systems & Products
July 2022 (version 1.70)
Why I use attrs instead of pydantic
0.8.0 Release Notes ⚡ The Zig Programming Language