Sony ended its big State of Play showcase with a major reveal: the next God of War. The new title is called God of War Laufey, and is once again developed by Sony's Santa Monica Studio. Currently, the game doesn't have a date, but it's coming to the PS5 whenever it does launch. This time, […]

You can pre-order the Faden siblings' next adventure now.

Caching in e-commerce is never just about speed. A fast storefront is useful only if it still shows the right price, the correct stock level, and the right experience for the current customer. That is why caching in a Next.js storefront can be deceptively hard. Some data should be shared broadly and kept warm for SEO and performance. Some data should be refreshed often. Some should never be shared between users at all. Next.js 16 gives teams a much clearer toolbox for solving this problem with Cache Components, use cache , tag-based invalidation, and explicit cache lifetime controls. Used properly, these features let you keep pages fast without drifting into stale commerce data. In this guide, I will walk through a practical way to think about caching in a modern storefront and show how to combine use cache , cacheLife , and revalidateTag for real e-commerce use cases. Why Caching Is Harder in E-Commerce Than in a Typical Content Site On a standard marketing site, most content changes infrequently. If a page is cached for a few minutes or even a few hours, the business impact is usually negligible. Commerce systems work differently. The same product page may contain: stable product descriptions and category copy semi-dynamic data such as price, availability, shipping estimates, or promotion labels private data such as cart state, recently viewed items, or customer-specific pricing Treating all of that data the same way leads to one of two bad outcomes: You cache too aggressively and serve stale prices or availability. You disable caching everywhere and lose the performance benefits that help SEO and conversion. The better approach is to split your data by volatility and audience. The Three Cache Boundaries That Matter Most For most commerce projects, the cleanest mental model is to divide data into three groups. 1. Stable catalog content This is the part of the page that usually changes only when content editors or merchandisers update the catalog. Examples: product

Control Resonant, the upcoming sequel to Remedy Entertainment's Control, will be released on September 24th, 2026, according to a trailer that premiered during Tuesday's PlayStation State of Play show. The trailer also gave a preview of the game's story, which stars Dylan Faden, who was imprisoned for much of the first game. He will be […]

For the AI artists here who like creating painterly / impasto style work, what generators are you guys using? Just curious since I'm much more into that theme as opposed to realism, but it feels like most generators cater to realism now. submitted by /u/geekedprompts [link] [留言]

Screen Burn is bringing Konami-branded horror to a fictional Scottish island.

Software testing is changing quickly. Teams are dealing with faster release cycles, more AI-assisted development, more complex browser behavior, and higher expectations around product quality. I collected a few practical articles that cover different parts of modern QA, test automation, developer workflows, and testing strategy. Recommended reads How to Test AI Agents for Tool Use, Memory, and Recovery Paths A practical framework for testing AI agents for tool use, memory retention, retries, and recovery paths, with concrete strategies for QA and engineering teams. How to Evaluate a Test Automation Tool for Shadow DOM, iframes, and Other Hard-to-Test UI Surfaces A practical buyer guide for evaluating test automation tools for shadow DOM testing, iframe testing, resilient selectors, and dynamic UI edge cases. How to Reproduce a Flaky Browser Test with Video, Logs, and Network Traces A practical workflow to reproduce a flaky browser test using video, logs, and network traces, then turn intermittent failures into repeatable bug reports. Endtest Review for Small QA Teams: Where Editable Test Flows Save the Most Time A practical Endtest review for small QA teams focused on editable test flows, maintainable test steps, and where no-code QA automation actually saves time. Editable Test Steps vs Generated Test Code: Which Holds Up Better After UI Changes? A practical comparison of editable test steps vs generated test code for UI change resilience, maintenance overhead, debugging, and team handoff, with guidance for QA and engineering leaders. Managed QA Services vs Staff Augmentation: What Changes in Ownership, Speed, and Cost A practical comparison of managed QA services vs staff augmentation, focusing on ownership, ramp time, communication overhead, cost, and maintenance risk. Automation Payback Period: How Long Does QA Test Automation Take to Break Even? Learn how to estimate the test automation payback period, model QA ROI, account for maintenance cost, and identify wh

JPop Demon Hunters? Yes please.

Em 2023, eu arrumei as malas e saí de Recife, minha terra natal, para morar no interior do Mato Grosso. O motivo? Cursar Ciência da Computação. Eu sabia que enfrentaria um choque cultural, o calor do Centro-Oeste e a saudade de casa. O que eu não imaginei é que o maior desafio seria a sensação constante de que eu era uma fraude no meio da minha própria sala de aula. Se você estuda ou trabalha com tecnologia, provavelmente já passou por isso. Você senta na primeira semana de aula e parece que metade da turma já programa desde os 12 anos, fala termos técnicos que parecem outra língua e discute sobre ferramentas que você nem sabia que existiam. Hoje, na reta final da graduação, focando meus estudos em Back-end e Dados, quebrando a cabeça com Go, Python e SQL, eu olho para trás e vejo o quanto essa cobrança silenciosa quase me paralisou. Se você está sentindo que entrou no curso errado ou que todo mundo corre a 100 km/h enquanto você ainda está engatinhando, pega um café e vem ler este papo reto sobre como lidar com a tal da Síndrome do Impostor. O "efeito vitrine" e a falsa ilusão de que somos os únicos perdidos Na faculdade de TI, a comparação é quase inevitável. A gente abre o LinkedIn e vê o colega conseguindo estágio internacional; abre o GitHub e vê códigos impecáveis; na sala de aula, sempre tem quem responda às perguntas do professor antes mesmo dele terminar de falar. O erro está em achar que o ritmo do outro deve ditar o seu. Na Computação, as pessoas vêm de bagagens completamente diferentes. Quem já sabia programar antes da faculdade pode ter facilidade em Lógica de Programação, mas talvez sofra tanto quanto você quando chegar a hora de aprender Álgebra Linear ou Teoria da Computação. Sentir-se perdida não significa incompetência; significa apenas que você está no processo de aprender algo complexo. E adivinha? Todo mundo ali está tentando descobrir como as coisas funcionam, mesmo quem finge que sabe tudo. O que me ajudou a virar a chave Eu não acordei um dia

Privacy-First Personal Finance for iOS Your finances. On your phone. Nowhere else. A privacy-first personal finance app that connects your banks, brokerage, and investment accounts into one unified dashboard — entirely on-device, no backend, no account required, no subscription. View on GitHub At a Glance 🏦 Multi-source 🔒 100% On-device 📊 Full picture Banks, Revolut, Trading 212 and more No server. No account. Your data stays in your Keychain. Net worth, spending, investments — all in one place Screenshots Log Insights Budget Transaction Entry Settings About Escudo Built out of two frustrations: every decent finance app costs a monthly subscription, and none of them support Trading 212. Escudo connects your banks, brokerage, and investment accounts and gives you a single view of your net worth, spending, and investments — without your data ever leaving your phone. Key Features Net worth dashboard — aggregated balance across all accounts and investment portfolio P&L Unified transaction log — every account in one feed, auto-categorised Spending insights — breakdown by category and trends over time Budget tracking — per-category budgets with visual progress dials Multi-currency — EUR, GBP, USD with stored exchange rates Recurring transactions — template-based recurring transaction engine Shortcuts support — deep linking via escudo:// URL scheme Integrations Source Method Trading 212 REST API — portfolio, orders, dividends Revolut Enable Banking OAuth 2.0 Bankinter PT Enable Banking OAuth 2.0 SIBS SIBS Open Banking (PT market) CSV import Revolut & Bankinter statements All credentials live in the iOS Keychain — never in UserDefaults, never in iCloud, never on a server. Known Limitations Enable Banking does not expose credit card accounts — only bank accounts and transactions are available through the PSD2 API; credit card balances and transactions are not accessible No token auto-refresh for Enable Banking — manual re-auth when tokens expire Categorisation rules are hard

I work for a nonprofit that’s had an outdated website for decades at this point. Upper management is kinda desperate and is getting quoted left and right. $15K for a Wix site which includes: event management, volunteer management, shop, donor management, and general blogs, etc. I thought Wix was one of the lower quality sites… especially as I can just go in and drag and drop elements myself. Are we being highballed? How can I convince my management who has zero website experience that this is not the route we want to go for that price point? submitted by /u/breezyb2310 [link] [留言]

The standard version of Rayman Legends Retold will cost $40.

If you've been writing Python for more than a year, you know the ritual. A new project. A fresh terminal. And then: pyenv install 3.12.3 pyenv local 3.12.3 python -m venv .venv source .venv/bin/activate pip install pip --upgrade pip install -r requirements.txt Six commands before you've written a single line of code. And that's if nothing breaks. Enter uv a single binary that replaces pip , virtualenv , pip-tools , pyenv , and pipx . Written in Rust. 10–100x faster than pip. And honestly, one of the most pleasant tools I've used in the Python ecosystem in years. Let's dig into it. What Even Is uv ? uv is a Python package and project manager built by Astral , the same team behind ruff , the linter that everyone switched to and never looked back. The goal is simple: be the Cargo for Python . One tool, one lockfile, no friction. It's a standalone binary with zero Python dependencies, which means it works even before Python is installed. Installing uv # macOS / Linux curl -LsSf https://astral.sh/uv/install.sh | sh # Windows (PowerShell) powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" # Or via pip if you prefer pip install uv Verify: uv --version # uv 0.9.x The Speed Claim Is It Real? Yes. Embarrassingly so. Here's a timed comparison on Apple Silicon (Python 3.14): Operation pip / venv uv Create virtual env ~2 seconds 35 milliseconds Install FastAPI + deps (cold) ~12s ~1.2s Install with warm cache ~8s ~0.1s The warm cache case is where uv really shines it uses a global cache and hard-links packages into environments instead of copying them. If you've installed requests in any previous project, your next project gets it nearly instantly. Starting a New Project This is where uv feels like a completely different world: uv init my-api cd my-api That single command gives you: my-api/ ├── .git/ ├── .venv/ ← already created ├── .python-version ├── pyproject.toml ├── README.md └── main.py No separate python -m venv , no git init , no template c

Hybrid RAG, No-Code AI Agent Memory, & Google Workspace CLI for Agents Today's Highlights Today's top stories delve into advanced RAG techniques, focusing on hybrid retrieval strategies to overcome limitations of vector-only search, and explore practical solutions for equipping AI agents with long-term memory. Additionally, we highlight a new unified CLI that empowers AI agents to automate tasks across Google Workspace, streamlining workflow automation. Why Vector Search Alone Isn't Enough: Hybrid Retrieval for RAG (InfoQ) Source: https://www.infoq.com/articles/vector-search-hybrid-retrieval-rag/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global This article addresses a critical limitation in current RAG (Retrieval-Augmented Generation) frameworks: the over-reliance on pure vector search. While semantic vector search excels at understanding conceptual similarity, it often struggles with exact keyword matching or retrieving information from documents that lack strong semantic context but contain vital terms. The piece advocates for hybrid retrieval, a strategy that combines semantic (vector-based) search with lexical (keyword-based, e.g., BM25) search. This combination significantly enhances the recall and precision of retrieved documents, leading to more accurate and contextually relevant responses from large language models. For practitioners, understanding and implementing hybrid retrieval is essential for building robust, production-grade RAG systems capable of handling diverse queries and document types, thereby improving overall document processing and search augmentation performance. Comment: Anyone building serious RAG apps knows vector search has blind spots. Hybrid retrieval is a non-negotiable step for production, ensuring critical keywords aren't overlooked and improving overall response quality. Give your AI agent long-term memory with MCP (no code) (Dev.to Top) Source: https://dev.to/lrdeoliveira/give-your-ai-agent-long-term-me

My talk “Frontend Ruby on Rails with Glimmer DSL for Web” went well at RubyConf Austria 2026 . Especially given that after the talk, Chad Fowler (the starter of RubyConf and famous book author of The Passionate Programmer , among other books) told me “good job”, and Obie Fernandez (a famous entrepreneur and book author of The Rails Way , among other books) told me he will try Glimmer DSL for Web because he doesn’t like React.js. Presentation Slides Direct Original Long Link: https://docs.google.com/presentation/d/e/2PACX-1vQ9oBnZpzK_eicVLGSqDmVzhsXsblONEKepnw5_xGHGXTM52JSjaS_ObYUJbx-zkb1M2ul9N2A2MnvU/pub?start=false&loop=false&delayms=60000&slide=id.g140fe579a5a_0_0 Glimmer DSL for Web GitHub: https://github.com/AndyObtiva/glimmer-dsl-web I ran a poll at the beginning of my talk, and everyone agreed that they love Ruby and that Ruby is superior to JavaScript, plus the majority indicated that they’d like to write less JavaScript and more Ruby during their Rails web development work. Several attendees told me my talk was great after the talk. Charles Nutter had me help him with his JRuby workshop afterwards by showcasing my other Glimmer project, Glimmer DSL for SWT , which runs on JRuby. In about 1 minute, I scaffolded a Hello World desktop app from scratch and then packaged it as a native executable on the Mac. Attendees were impressed. So, I’ve participated in presenting 2 events at this conference. I am very grateful for having such a great experience at RubyConf Austria 2026 overall, especially given that it uniquely included several classical/neoclassical/jazz concerts in between talks that entertained us and relaxed us. Chad Fowler concluded the conference with a beautiful Jazz piano and sax performance. Shout out to Hans Schnedlitz, Muhamed Isabegovic, and Zuzanna Kusznir (plus everyone who helped out) for organizing and hosting such a special Ruby conference!!! Original blog post version: https://andymaleh.blogspot.com/2026/06/rubyconf-austria-2026-frontend-r

AirDrop only works between Apple devices. Most alternatives require an app install, a cloud account, or route files through a third-party server. I wanted something simpler: Open a URL → discover nearby devices → send files. So I built LocalDrop — a peer-to-peer file transfer app that works entirely in the browser over local Wi-Fi. GitHub: https://github.com/akshaykdadheech/localdrop Live Demo: https://localdrop-4fddd39fb6ad.herokuapp.com How It Works Devices connected to the same Wi-Fi network automatically discover each other through a lightweight signaling server. Once discovered, WebRTC establishes a direct peer-to-peer connection: Browser A ──► Signaling Server ◄── Browser B └──────── WebRTC P2P ────────┘ The signaling server only helps devices find each other. File transfers happen directly between browsers via WebRTC and are DTLS encrypted, so the server never sees your files. Interesting Challenges Backpressure Handling WebRTC DataChannels on Chromium have a ~16 MB buffer limit. Sending data too aggressively can crash the tab. I solved this using: bufferedAmountLowThreshold Flow control based on drain events Cross-Platform Compatibility Different browsers expose different capabilities. Android Chrome supports the File System Access API iOS Safari does not This required separate file-receiving flows for each platform. Large File Transfers Keeping multi-gigabyte files in memory isn't practical. On Chrome, showSaveFilePicker() is triggered after the transfer completes, allowing transfer progress to remain visible throughout the process without buffering everything in RAM. Tech Stack Svelte 5 + Vite TypeScript WebRTC DataChannel Node.js + ws Docker Self-Hosting git clone https://github.com/akshaykdadheech/localdrop cd localdrop docker compose up -d Then open: http://your-ip:3001 from any device connected to the same Wi-Fi network. I'd love feedback from anyone who's worked with WebRTC DataChannels, especially on mobile browsers. If you find the project useful, a

I applied for a role at a mid-sized SaaS company about two years into my career. Strong company, interesting problem, good pay. I sent my application, got a recruiter callback, and then nothing for two weeks. When the feedback finally came: "We went with candidates with a stronger portfolio presence." I had 23 GitHub repositories. I had a portfolio site. I had projects. What I didn't have — and what I didn't understand for another six months — was a portfolio that told a story. I had code. Not evidence of thinking, decision-making, or the ability to ship something real. I've since built, rebuilt, and advised on a lot of developer portfolios. I've seen what gets people calls and what gets them ghosted. This isn't a guide about which framework to use or how to pick colors. It's about what actually moves the needle — the things I wish someone had told me in year one. Lesson 1: Two Great Projects Beat Twenty Mediocre Ones The instinct is to fill the portfolio. More projects = more evidence of experience. This is wrong. A hiring manager or engineering lead looking at your portfolio has about three minutes. They're going to look at your two or three most prominent projects, click one or two live demo links, and form an opinion. If they see twenty repositories and most of them are "Todo App v2," "Weather App," "Netflix Clone," "Portfolio v1 through v6" — they've already categorized you as someone who builds tutorials, not someone who builds things. The better approach: three to five projects, each with: A real problem it solves (not "I wanted to learn React") A live deployment that actually works A README that explains why you made the decisions you made Enough complexity to have generated at least one interesting engineering problem Projects that tend to work: tools you built because you were frustrated with an existing tool, apps solving problems you personally had, projects where you integrated with a real API or real data source, anything with a live user base (even 10