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  • 「Postgres で試した?」と聞き返せるようになるまでもしくはなぜ私は雰囲気で技術を語るのか? — Just use Postgres 読書感想文 - じゃあ、おうちで学べる

    はじめに 「Just use Postgres」という言葉を初めて聞いたのは、いつだったか覚えていません。Twitter か Hacker News か、あるいは社内の Slack か。どこで聞いたにせよ、私の反応は決まっていました。「また極端なことを言う人がいる」と。 「それ、〇〇でもできますよ」——この手のフレーズはもう100回は聞いてきました。そして大抵の場合、その〇〇は専用ツールに置き換えられていきます。技術が専門分化していくのは自然な流れです。 全文検索なら Elasticsearch。時系列データなら InfluxDB。メッセージキューなら RabbitMQ。それぞれの分野に専門家がいて、専用のソリューションがあって、ベストプラクティスがあります。「とりあえず Postgres で」なんて、それは思考停止ではないか、と。でも、心のどこかで気になっていたんです。 www.mann

      「Postgres で試した?」と聞き返せるようになるまでもしくはなぜ私は雰囲気で技術を語るのか? — Just use Postgres 読書感想文 - じゃあ、おうちで学べる
    • The End of Programming as We Know It

      There’s a lot of chatter in the media that software developers will soon lose their jobs to AI. I don’t buy it. It is not the end of programming. It is the end of programming as we know it today. That is not new. The first programmers connected physical circuits to perform each calculation. They were succeeded by programmers writing machine instructions as binary code to be input one bit at a time

        The End of Programming as We Know It
      • Consider SQLite

        If you were creating a web app from scratch today, what database would you use? Probably the most frequent answer I see to this is Postgres, although there are a wide range of common answers: MySQL, MariaDB, Microsoft SQL Server, MongoDB, etc. Today I want you to consider: what if SQLite would do just fine? For those who are unfamiliar, SQLite is a implementation of SQL as a library — this means t

        • OpenAIのBatch APIを使ってお得にプロンプトを一括処理してみる - Taste of Tech Topics

          はじめに こんにちは。データサイエンスチームYAMALEXのSsk1029Takashiです。 最近はOpenAIに日本支社が出来て、日本語対応が加速するというニュースにわくわくしています。 今回はそんなOpenAIから発表されたBatch APIという機能が便利、かつお得な機能だったのでどのように使えるのか試してみます。 Introducing the Batch API: save costs and get higher rate limits on async tasks (such as summarization, translation, and image classification). Just upload a file of bulk requests, receive results within 24 hours, and get 50% off API pri

            OpenAIのBatch APIを使ってお得にプロンプトを一括処理してみる - Taste of Tech Topics
          • Rust Is Eating JavaScript | Lee Robinson

            Rust Is Eating JavaScript 2021 (updated 2026) – Lee Robinson Rust is a fast, reliable, and memory-efficient programming language. It’s been voted the most admired programming language for a decade1. Created by Mozilla, it’s now used at Meta, Apple, Amazon, Microsoft, and Google for systems infrastructure, encryption, virtualization, and more low-level programming. Why is Rust now being used to rep

              Rust Is Eating JavaScript | Lee Robinson
            • Pricing changes for GitHub Actions

              TLDR: We’re postponing the announced billing change for self-hosted GitHub Actions to take time to re-evaluate our approach. We are continuing to reduce hosted-runners prices by up to 39% on January 1, 2026. We’ve read your posts and heard your feedback. We’re postponing the announced billing change for self-hosted GitHub Actions to take time to re-evaluate our approach. We are continuing to reduc

                Pricing changes for GitHub Actions
              • What it was like working for GitLab

                I joined GitLab in October 2015, and left in December 2021 after working there for a little more than six years. While I previously wrote about leaving GitLab to work on Inko, I never discussed what it was like working for GitLab between 2015 and 2021. There are two reasons for this: I was suffering from burnout, and didn't have the energy to revisit the last six years of my life (at that time)I w

                • The Prompt Engineering Playbook for Programmers

                  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

                    The Prompt Engineering Playbook for Programmers
                  • 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

                      GitHub - modelcontextprotocol/servers: Model Context Protocol Servers
                    • Migrating to OpenTelemetry | Airplane

                      At Airplane, we collect observability data from our own systems as well as remote “agents” that are running in our customers’ infrastructure. The associated outputs, which include the standard “three pillars of observability” (logs, metrics, and traces) are essential for us to monitor our infrastructure and also help customers debug problems in theirs. Over the last year, we’ve made a concerted ef

                        Migrating to OpenTelemetry | Airplane
                      • Your URL Is Your State

                        Couple of weeks ago when I was publishing The Hidden Cost of URL Design I needed to add SQL syntax highlighting. I headed to PrismJS website trying to remember if it should be added as a plugin or what. I was overwhelmed with the amount of options in the download page so I headed back to my code. I checked the file for PrismJS and at the top of the file, I found a comment containing a URL: /* http

                        • GPT in 60 Lines of NumPy | Jay Mody

                          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

                          • awesome-scalability

                            The Patterns of Scalable, Reliable, and Performant Large-Scale Systems View the Project on GitHub View On GitHub An updated and organized reading list for illustrating the patterns of scalable, reliable, and performant large-scale systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are taken from battle-tested systems that serve millions to

                            • Introducing Ezno

                              Ezno is an experimental compiler I have been working on and off for a while. In short, it is a JavaScript compiler featuring checking, correctness and performance for building full-stack (rendering on the client and server) websites. This post is just an overview of some of the features I have been working on which I think are quite cool as well an overview on the project philosophy ;) It is still

                                Introducing Ezno
                              • Amazon Bedrock Is Now Generally Available – Build and Scale Generative AI Applications with Foundation Models | Amazon Web Services

                                AWS News Blog Amazon Bedrock Is Now Generally Available – Build and Scale Generative AI Applications with Foundation Models Update October 10, 2023 — Amazon Bedrock is now available in 3 regions globally: US East (N. Virginia), US West (Oregon), and Asia Pacific (Tokyo). This April, we announced Amazon Bedrock as part of a set of new tools for building with generative AI on AWS. Amazon Bedrock is

                                  Amazon Bedrock Is Now Generally Available – Build and Scale Generative AI Applications with Foundation Models | Amazon Web Services
                                • How I Use Every Claude Code Feature

                                  I use Claude Code. A lot. As a hobbyist, I run it in a VM several times a week on side projects, often with --dangerously-skip-permissions to vibe code whatever idea is on my mind. Professionally, part of my team builds the AI-IDE rules and tooling for our engineering team that consumes several billion tokens per month just for codegen. The CLI agent space is getting crowded and between Claude Cod

                                    How I Use Every Claude Code Feature
                                  • 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

                                      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
                                    • Scaling containers on AWS in 2022

                                      This all started with a blog post back in 2020, from a tech curiosity: what's the fastest way to scale containers on AWS? Is ECS faster than EKS? What about Fargate? Is there a difference between ECS on Fargate and EKS on Fargate? I had to know this to build better architectures for my clients. In 2021, containers got even better, and I was lucky enough to get a preview and present just how fast t

                                        Scaling containers on AWS in 2022
                                      • How to create Skills for Claude: steps and examples | Claude

                                        Skills are custom instructions that extend Claude's capabilities for specific tasks or domains. When you create a skill via a SKILL.md file, you're teaching Claude how to handle specific scenarios more effectively. The power of skills lies in their ability to encode institutional knowledge, standardize outputs, and handle complex multi-step workflows that would otherwise require repeated explanati

                                          How to create Skills for Claude: steps and examples | Claude
                                        • LogLog Games

                                          The article is also available in Chinese. Disclaimer: This post is a very long collection of thoughts and problems I've had over the years, and also addresses some of the arguments I've been repeatedly told. This post expresses my opinion the has been formed over using Rust for gamedev for many thousands of hours over many years, and multiple finished games. This isn't meant to brag or indicate su

                                          • Announcing .NET 10 - .NET Blog

                                            Today, we are excited to announce the launch of .NET 10, the most productive, modern, secure, intelligent, and performant release of .NET yet. It’s the result of another year of effort from thousands of developers around the world. This release includes thousands of performance, security, and functional improvements across the entire .NET stack-from languages and developer tools to workloads-enabl

                                              Announcing .NET 10 - .NET Blog
                                            • Replit — How to train your own Large Language Models

                                              Learn how Replit trains Large Language Models (LLMs) using Databricks, Hugging Face, and MosaicML IntroductionLarge Language Models, like OpenAI's GPT-4 or Google's PaLM, have taken the world of artificial intelligence by storm. Yet most companies don't currently have the ability to train these models, and are completely reliant on only a handful of large tech firms as providers of the technology.

                                                Replit — How to train your own Large Language Models
                                              • AWS Certified Machine Learning Engineer - Associate(MLA)の学習方法 - NRIネットコムBlog

                                                小西秀和です。 この記事は「AWS認定全冠を維持し続ける理由と全取得までの学習方法・資格の難易度まとめ」で説明した学習方法を「AWS Certified Machine Learning Engineer - Associate(MLA)」に特化した形で紹介するものです。 重複する内容については省略していますので、併せて元記事も御覧ください。 また、現在投稿済の各AWS認定に特化した記事へのリンクを以下に掲載しましたので興味のあるAWS認定があれば読んでみてください。 ALL SAP DOP SCS ANS MLS SAA DVA SOA DEA MLA AIF CLF 「AWS Certified Machine Learning Engineer - Associate(MLA)」とは 「AWS Certified Machine Learning Engineer - Associa

                                                  AWS Certified Machine Learning Engineer - Associate(MLA)の学習方法 - NRIネットコムBlog
                                                • Functional programming is finally going mainstream

                                                  Functional programming is finally going mainstream Object-oriented and imperative programming aren’t going away, but functional programming is finding its way into more codebases. Klint Finley // July 12, 2022 Paul Louth had a great development team at Meddbase, the healthcare software company he founded in 2005. But as the company grew, so did their bug count. That’s expected, up to a point. More

                                                    Functional programming is finally going mainstream
                                                  • Introducing Project IDX, An Experiment to Improve Full-stack, Multiplatform App Development- Google Developers Blog

                                                    These days, getting an app from zero to production – especially one that works well across mobile, web, and desktop platforms – can feel like building a Rube Goldberg machine. You’ve got to navigate an endless sea of complexity, duct-taping together a tech stack that'll help you bootstrap, compile, test, deploy, and monitor your apps. While Google’s been working on making multiplatform app develop

                                                      Introducing Project IDX, An Experiment to Improve Full-stack, Multiplatform App Development- Google Developers Blog
                                                    • 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

                                                        What We Learned from a Year of Building with LLMs (Part I)
                                                      • The Best Go framework: no framework?

                                                        While writing this blog and leading Go teams for a couple of years, the most common question I heard from beginners was “What framework should I use?”. One of the worst things you can do in Go is follow an approach from other programming languages. Other languages have established, “default” frameworks. Java has Spring, Python has Django and Flask, Ruby has Rails, C# has ASP.NET, Node has Express,

                                                          The Best Go framework: no framework?
                                                        • 100+ Best GitHub Repositories For Machine Learning

                                                          There are millions of GitHub repos and filtering them is an insane amount of work. It takes a huge time, effort, and a lot more. We have done this for you. In this article, we’ll share a curated list of 100+ widely-known, recommended, and most popular repositories and open source GitHub projects for Machine Learning and Deep Learning. So without further ado, Let’s see all the hubs created by exper

                                                            100+ Best GitHub Repositories For Machine Learning
                                                          • PHP is Legacy, in 2024

                                                            A trained actor with a dissertation on standup comedy, I came into PHP development via the meetup scene. You can find me speaking and writing on tech, or playing/buying odd records from my vinyl collection. Ready to start building?Experience seamless connectivity, real-time messaging, and crystal-clear voice and video calls-all at your fingertips. Subscribe to Our Developer NewsletterSubscribe to

                                                              PHP is Legacy, in 2024
                                                            • こいつを待ってた!3万字以上自動的に書いてくれるオープンLLMが登場!三回回せば本一冊分に!

                                                              なんか最近、いろんな会社が「おらが村のLLMが凄いだ」と言ってるが、実際には100万トークン読めても出力が8Kまでだったり、もっとひどいと4Kだったりと、LLMの価値はパラメータ数では決まらず、むしろどのくらい長い文章を出してくれるのかということの方が大事だ。僕がLLMで本を書いたのはもう一年前だが、このときは4Kくらいしか出力してくれなくて往生したものである。 ところがなんということでしょう。ついに出ました。原稿を代わりに書いてくれそうな素敵なオープンソースLLMが。その名も「LongWriter」 Apacheライセンス、しかも訓練コード付き。つまりご家庭で自分好みにファインチューニングもできちゃう。しかもこの言語モデル、なんと8Bしかないんですよ奥さん。24GBしかVRAMのない星飛雄馬のようなご家庭のPCでも動いちゃうというワケですよ。なんという不都合な真実。いいのかおい。 AIち

                                                                こいつを待ってた!3万字以上自動的に書いてくれるオープンLLMが登場!三回回せば本一冊分に!
                                                              • pzuraq | Four Eras of JavaScript Frameworks

                                                                April 25, 2022 Four Eras of JavaScript Frameworks April 25, 2022 I started coding primarily in JavaScript back in 2012. I had built a PHP app for a local business from the ground up, a basic CMS and website, and they decided that they wanted to rewrite it and add a bunch of features. The manager of the project wanted me to use .NET, partially because it’s what he knew, but also because he wanted i

                                                                  pzuraq | Four Eras of JavaScript Frameworks
                                                                • GitHub - punkpeye/awesome-mcp-servers: A collection of MCP servers.

                                                                  Servers for accessing many apps and tools through a single MCP server. 1mcp/agent 📇 ☁️ 🏠 🍎 🪟 🐧 - A unified Model Context Protocol server implementation that aggregates multiple MCP servers into one. tadas-github/a2asearch-mcp 📇 ☁️ - MCP server to search 4,800+ MCP servers, AI agents, CLI tools and agent skills. Install: npx -y a2asearch-mcp. Ask Claude: "Find MCP servers for database access"

                                                                    GitHub - punkpeye/awesome-mcp-servers: A collection of MCP servers.
                                                                  • API Tokens: A Tedious Survey

                                                                    API Tokens: A Tedious Survey Author Name Thomas Ptacek @tqbf @tqbf Image by Annie Ruygt We’re Fly.io. This post isn’t about Fly.io, but you have to hear about us anyways, because my blog, my rules. Our users ship us Docker containers and we transmute them into Firecracker microvms, which we host on our own hardware around the world. With a working Dockerfile, getting up and running will take you l

                                                                      API Tokens: A Tedious Survey
                                                                    • A Language For Agents

                                                                      Last year I first started thinking about what the future of programming languages might look like now that agentic engineering is a growing thing. Initially I felt that the enormous corpus of pre-existing code would cement existing languages in place but now I’m starting to think the opposite is true. Here I want to outline my thinking on why we are going to see more new programming languages and

                                                                        A Language For Agents
                                                                      • The yaml document from hell

                                                                        written by Ruud van Asseldonk published 11 January 2023 For a data format, yaml is extremely complicated. It aims to be a human-friendly format, but in striving for that it introduces so much complexity, that I would argue it achieves the opposite result. Yaml is full of footguns and its friendliness is deceptive. In this post I want to demonstrate this through an example. This post is a rant, and

                                                                        • Wasm-agents: AI agents running in your browser

                                                                          One of the main barriers to a wider adoption and experimentation with open-source agents is the dependency on extra tools and frameworks that need to be installed before the agents can be run. In this post, we introduce the Wasm agents blueprint, aimed at showing how to write agents as HTML files, which can just be opened and run in a browser, without the need for any extra dependencies. This is s

                                                                            Wasm-agents: AI agents running in your browser
                                                                          • PaLM API & MakerSuite: an approachable way to start prototyping and building generative AI applications- Google Developers Blog

                                                                            PaLM API & MakerSuite: an approachable way to start prototyping and building generative AI applications Share Facebook Twitter LinkedIn Mail Posted by Scott Huffman, Vice President, Engineering and Josh Woodward, Senior Director, Product Management We’re seeing a new wave of generative AI applications that are transforming the way people interact with technology – from games and dialog agents to c

                                                                              PaLM API & MakerSuite: an approachable way to start prototyping and building generative AI applications- Google Developers Blog
                                                                            • Python open source libraries for scaling time series forecasting solutions

                                                                              By Francesca Lazzeri. This article is an extract from the book Machine Learning for Time Series Forecasting with Python, also by Lazzeri, published by Wiley. In the first and second articles in this series, I showed how to perform feature engineering on time series data with Python and how to automate the Machine Learning lifecycle for time series forecasting. In this third and concluding article,

                                                                                Python open source libraries for scaling time series forecasting solutions
                                                                              • CUPID: for joyful coding

                                                                                What started as lighthearted iconoclasm, poking at the bear of SOLID, has developed into something more concrete and tangible. If I do not think the SOLID principles are useful these days, then what would I replace them with? Can any set of principles hold for all software? What do we even mean by principles? I believe that there are properties or characteristics of software that make it a joy to

                                                                                • RAG is more than just embedding search - Instructor

                                                                                  RAG is more than just embedding search¶ With the advent of large language models (LLM), retrieval augmented generation (RAG) has become a hot topic. However throughout the past year of helping startups integrate LLMs into their stack I've noticed that the pattern of taking user queries, embedding them, and directly searching a vector store is effectively demoware. What is RAG? Retrieval augmented

                                                                                    RAG is more than just embedding search - Instructor