「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
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
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
Note: This blog post is also available as a documentation page on Transformers. Large Language Models (LLMs) such as GPT3/4, Falcon, and LLama are rapidly advancing in their ability to tackle human-centric tasks, establishing themselves as essential tools in modern knowledge-based industries. Deploying these models in real-world tasks remains challenging, however: To exhibit near-human text unders
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
Front-end maximalism
Here's a question that comes up all the time: Q: I have a front end that calls into a back end. It needs to do things now, and might need to do more things later. How much filtering and preprocessing should the back-end do before it passes the data to the front end? And here's an answer I like: A: As little as possible. Some examples: Suppose you have a product page with a long list of products. T
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
Agent Development Kit: Making it easy to build multi-agent applications- Google Developers Blog
Agent Development Kit: Making it easy to build multi-agent applications The world of AI is rapidly moving beyond single-purpose models towards intelligent, autonomous multi-agent systems. Building these multi-agent systems, however, presents new challenges. That is why today, we have introduced Agent Development Kit (ADK) at Google Cloud NEXT 2025, a new open-source framework from Google designed
I often come across developers who know the mechanics of Python error handling well, yet when I review their code I find it to be far from good. Exceptions in Python is one of those areas that have a surface layer that most people know, and a deeper, almost secret one that a lot of developers don't even know exists. If you want to test yourself on this topic, see if you can answer the following qu
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.”
This post first appeared in The Analytics Engineering Roundup. Business intelligence is on a collision course with AI. The collision itself hasn’t happened yet, but it’s clearly coming. The inevitability of this has been clear roughly since the launch of ChatGPT, but no one knew exactly what shape that would take. Today I want to propose how that collision is going to happen and what will happen i
I first learned Kubernetes ("k8s" for short) in 2018, when my manager sat me down and said "Cloudflare is migrating to Kubernetes, and you're handling our team's migration." This was slightly terrifying to me, because I was a good programmer and a mediocre engineer. I knew how to write code, but I didn't know how to deploy it, or monitor it in production. My computer science degree had taught me a
Edge AI Just Got Faster
When Meta released LLaMA back in February, many of us were excited to see a high-quality Large Language Model (LLM) become available for public access. Many of us who signed up however, had difficulties getting LLaMA to run on our edge and personal computer devices. One month ago, Georgi Gerganov started the llama.cpp project to provide a solution to this, and since then his project has been one o
Introduction Before explaining why I created Oil, let's review what it is. You can think of a Unix shell in two ways: As a text-based user interface. You communicate with the operating system by typing commands. As a language. It has variables, functions, and loops. Shell programs are text files that start with #!/bin/sh. In this document, we'll think of Unix shells as languages. The Oil project a
Welcome to my ::'########::'##::::::::'#######:::'######::: :: ##.... ##: ##:::::::'##.... ##:'##... ##:: :: ##:::: ##: ##::::::: ##:::: ##: ##:::..::: :: ########:: ##::::::: ##:::: ##: ##::'####: :: ##.... ##: ##::::::: ##:::: ##: ##::: ##:: :: ##:::: ##: ##::::::: ##:::: ##: ##::: ##:: :: ########:: ########:. #######::. ######::: ::........:::........:::.......::::......:::: CTF writeups, prog
Anthropic Claudeで英訳したテキストをもとにStability AI Stable Diffusion XL(SDXL)で画像を生成するAmazon Bedrockの使用例 - NRIネットコムBlog
小西秀和です。 以前の記事でAmazon Bedrockの参考資料、モデル一覧、価格、使い方、トークンやパラメータの用語説明、Runtime APIの実行例について紹介しました。 Amazon Bedrockの基本情報とRuntime APIの実行例まとめ － 参考資料、モデルの特徴、価格、使用方法、トークンと推論パラメータの説明 今回はAnthropic Claudeで英訳したテキストをもとにStability AI Stable Diffusion XL(SDXL)で画像を生成するAmazon Bedrockの使用例を紹介します。 ※本記事および当執筆者のその他の記事で掲載されているソースコードは自主研究活動の一貫として作成したものであり、動作を保証するものではありません。使用する場合は自己責任でお願い致します。また、予告なく修正することもありますのでご了承ください。 ※本記事執筆にあ
The Go Programming Language and Environment – Communications of the ACM
Go is a programming language created at Google in late 2007 and released as open source in November 2009. Since then, it has operated as a public project, with contributions from thousands of individuals and dozens of companies. Go has become a popular language for building cloud infrastructure: Docker, a Linux container manager, and Kubernetes, a container deployment system, are core cloud techno
Date: June 23, 2023 | Estimated Reading Time: 31 min | Author: Lilian Weng Building agents with LLM (large language model) as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs; it can be framed as a powerfu
Preface
At the end of Harry’s last book, Test-Driven Development with Python (O’Reilly), he found himself asking a bunch of questions about architecture, such as, What’s the best way of structuring your application so that it’s easy to test? More specifically, so that your core business logic is covered by unit tests, and so that you minimize the number of integration and end-to-end tests you need? He mad
The Architecture of a Modern Startup | by Dmitry Kruglov | Nov, 2022 | Better Programming
workflow — all images by authorThe Tech side of startups can sometimes be very fluid and contain a lot of unknowns. What tech stack to use? Which components might be overkill for now but worth keeping an eye on in the future? How to balance the pace of business features development while keeping the quality bar high enough to have a maintainable codebase? Here I want to share our experience buildi
Solving Quantitative Reasoning Problems With Language Models
Solving Quantitative Reasoning Problems with Language Models Aitor Lewkowycz∗, Anders Andreassen†, David Dohan†, Ethan Dyer†, Henryk Michalewski†, Vinay Ramasesh†, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, Yuhuai Wu, Behnam Neyshabur∗, Guy Gur-Ari∗, and Vedant Misra∗ Google Research Abstract Language models have achieved remarkable performance on a wide range of tasks that require
11th March 2025 Online discussions about using Large Language Models to help write code inevitably produce comments from developers who’s experiences have been disappointing. They often ask what they’re doing wrong—how come some people are reporting such great results when their own experiments have proved lacking? Using LLMs to write code is difficult and unintuitive. It takes significant effort
The Andrej Karpathy episode. Andrej explains why reinforcement learning is terrible (but everything else is much worse), why model collapse prevents LLMs from learning the way humans do, why AGI will just blend into the previous ~2.5 centuries of 2% GDP growth, why self driving took so long to crack, and what he sees as the future of education. Watch on YouTube; listen on Apple Podcasts or Spotify
arXiv:2506.12115v1 [cs.CL] 13 Jun 2025 Eliciting Reasoning in Language Models with Cognitive Tools Brown Ebouky IBM Research - Zurich ETH Zurich Brown.Ebouky@ibm.com Andrea Bartezzaghi IBM Research - Zurich abt@zurich.ibm.com Mattia Rigotti IBM Research - Zurich mrg@zurich.ibm.com Abstract The recent advent of reasoning models like OpenAI’s o1 was met with excited spec- ulation by the AI community
State of the Common Lisp ecosystem, 2020 🎉 - Lisp journey
NEW: 9 videos (86min) about CLOS on my Common Lisp course. Out of 7h+ of content. Rated 4.7/5. Learn more and stay tuned. 🎥 I also have cool Lisp showcases on Youtube . The last ones: how to build a web app in Common Lisp, part 1 and 2. This is a description of the Common Lisp ecosystem, as of January, 2021, from the perspective of a user and contributor. The purpose of this article is both to gi
AWS Lambda Functions Powered by AWS Graviton2 Processor – Run Your Functions on Arm and Get Up to 34% Better Price Performance | Amazon Web Services
AWS News Blog AWS Lambda Functions Powered by AWS Graviton2 Processor – Run Your Functions on Arm and Get Up to 34% Better Price Performance December 13, 2022: Post updated to include all the AWS Regions where Lambda Functions can be powered by the Graviton2 Processor. June 19, 2023: List of AWS Regions updated. Many of our customers (such as Formula One, Honeycomb, Intuit, SmugMug, and Snap Inc.)
Engineering for Slow Internet How to minimize user frustration in Antarctica. Hello everyone! I got partway through writing this post while I was still in Antarctica, but I departed before finishing it. I’m going through my old draft posts, and I found that this one was nearly complete. It’s a bit of a departure from the normal content you’d find on brr.fyi, but it reflects my software / IT engine
prompts.chat
Welcome to the “Awesome ChatGPT Prompts” repository! While this collection was originally created for ChatGPT, these prompts work great with other AI models like Claude, Gemini, Hugging Face Chat, Llama, Mistral, and more. ChatGPT is a web interface created by OpenAI that provides access to their GPT (Generative Pre-trained Transformer) language models. The underlying models, like GPT-4o and GPT-o
Transformer models: an introduction and catalog — 2023 Edition January 16, 2023 52 minute read This post is now an ArXiV paper that you can print and cite. Update 05/2023 Another pretty large update after 4 months. I was invited to submit the article to a journal, so I decided to enlist some help from some LinkedIn colleages and completely revamp it. First off, we added a whole lot of new models,
A year ago, I was preparing a presentation for an event and the title slide asked me to fill in my role. I had been hired as a “Data Analyst”, and when I started the role, I spent my time doing normal data analyst things. I pulled data for finance and marketing, analyzed trends and generated insights, and spent lots of time in Excel and Looker. However, my role had been changing dramatically. Fina
Exactly ten years ago today, we published "Why We Created Julia", introducing the Julia project to the world. At this point, we have moved well past the ambitious goals set out in the original blog post. Julia is now used by hundreds of thousands of people. It is taught at hundreds of universities and entire companies are being formed that build their software stacks on Julia. From personalized me
I’m excited to announce the project I’ve been working on for the last year and a half: Game Bub, an open-source FPGA based retro emulation handheld, with support for Game Boy, Game Boy Color, and Game Boy Advance games. Play Video: Game Bub can play physical cartridges, as well as emulated cartridges using ROM files loaded from a microSD card. Game Bub also supports the Game Link Cable in both GB
Agents for Amazon Bedrock now support memory retention and code interpretation (preview) | Amazon Web Services
AWS News Blog Agents for Amazon Bedrock now support memory retention and code interpretation (preview) With Agents for Amazon Bedrock, generative artificial intelligence (AI) applications can run multistep tasks across different systems and data sources. A couple of months back, we simplified the creation and configuration of agents. Today, we are introducing in preview two new fully managed capab
Reflection is something a lot of people wish the Rust language had: It is not hard to stumble across somebody with an interesting use case for it. People want to use it for serialization, GCs, better interop, and so, so much more. If you can think of a task, there is somebody out there wishing they could implement it using reflection. Sadly, it does not look like it is coming any time soon. Still,
Repurposing e-waste: turning a TV set-top box into a Linux computer
Repurposing e-waste: turning a TV set-top box into a Linux computer door Jasper Devreker Our mobile Internet Service Provider (ISP) has a bundle where they provide a 4G modem for internet access, and a separate TV set-top box that can be used to watch their TV content or to watch streaming services. This device was sent to us as part of the bundle, but at Zeus, we don’t really have a use for it: w
Technology Trends for 2024
This has been a strange year. While we like to talk about how fast technology moves, internet time, and all that, in reality the last major new idea in software architecture was microservices, which dates to roughly 2015. Before that, cloud computing itself took off in roughly 2010 (AWS was founded in 2006); and Agile goes back to 2000 (the Agile Manifesto dates back to 2001, Extreme Programming t
CORS is a necessity for many APIs, but basic configurations can create a huge number of extra requests, slowing down every browser API client, and sending unnecessary traffic to your backend. This can be a problem with a traditional API, but becomes a much larger issue with serverless platforms, where your billing is often directly tied to the number of requests received, so this can easily double
A professional programmer delivers value through the authoring and maintaining of software that solves problems. (There are other important ways for professional programmers to deliver value but this post is about programming.) Programmers rely on various tools to author software. Arguably the most important and consequential choice of tool is the programming language. In this post, I will articul
Plan 9 Desktop Guide
PLAN 9 DESKTOP GUIDE INDEX What is Plan 9? Limitations and Workarounds Connecting to Other Systems VNC RDP SSH 9P Other methods Porting Applications Emulating other Operating Systems Virtualizing other Operating Systems Basics Window Management Copy Pasting Essential Programs Manipulating Text in the Terminal Acme - The Do It All Application Multiple Workspaces Tiling Windows Plumbing System Admin
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The Prompt Engineering Playbook for Programmers
Things we learned about LLMs in 2024
Optimizing your LLM in production
API Tokens: A Tedious Survey
The Ultimate Guide to Error Handling in Python
Patterns for Building LLM-based Systems & Products
How AI will disrupt BI as we know it | dbt Labs
Solving common problems with Kubernetes
Why Create a New Unix Shell? (2021)
The Quest for Netflix on Asahi Linux | Blog
LLM Powered Autonomous Agents
Here’s how I use LLMs to help me write code
Andrej Karpathy — AGI is still a decade away
Eliciting Reasoning in Language Models with Cognitive Tools
Engineering for Slow Internet – brr
Transformer models: an introduction and catalog — 2023 Edition
What is analytics engineering? | dbt Labs
Why We Use Julia, 10 Years Later
Game Bub: open-source FPGA retro emulation handheld
Rust, reflection and access rules
Cache your CORS, for performance & profit
Gregory Szorc's Digital Home | Rust is for Professionals