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OpenHabitTracker is a free, open source habit tracker that also holds your notes and tasks. It runs on Windows, Linux, macOS, iOS, Android and in a browser, with no ads and no account. Filtering and sorting habits A habit here is not measured by a streak. It is measured by how much of its interval has gone by. A habit you want to do every ten days, two days late, is at 120%. A habit you want to do every four days, also two days late, is at 150%. Because that is a number, you can filter on a range of it: only habits above 50%, only habits below 150%, or only the ones in between. That last one is everything neither freshly done nor badly overdue. You can sort by it as well, and the sort takes the repeat count into account, so a habit done three times a day and one done weekly are compared against each other rather than the daily ones always sitting on top. There are other ways to sort habits by time: how long you want between repeats, how long it has actually been averaging, how long since the last one, and how much time you have spent on it in total or per completion. Notes and tasks sort by the plain things, category, priority and title, and tasks also by their planned date and duration. Each of the three keeps its own sort order. Filtering by date Tasks have a planned date. Tasks and habits have the dates they were completed on. Both are filtered separately, each before, on, after or not on a date you pick. A filter can also take a number of days from today instead of a date. Minus seven to plus seven is the week either side of now, and it still means that in a month, because the days are counted at the moment you look rather than the moment you set it. Showing what was not done The completed-date filter has a switch next to it. Turned on, the range shows what you finished in those days. Turned off, the same range shows what you did not. Searching notes, tasks and habits Searching a note searches the whole note, not just its title. Searching tasks and habits search

I use WSL2 as my main development environment on Windows. My projects live in Linux: /home/user/Projects/... Node.js, pnpm, Git, Docker, and the rest of my toolchain also run inside WSL. When I started using Google Antigravity IDE, I wanted the same workflow I already had with VS Code: code . Something like: agy . That would have been the obvious command. But agy is already the official Antigravity CLI, so reusing it as a launcher for the Windows IDE would be confusing. So I needed another name. I ended up with: wagy . You can read it as WSL + agy or Windows + agy — both actually describe what it does pretty well. The goal was simple: WSL2 └── ~/Projects/my-project │ │ wagy . ▼ Antigravity IDE on Windows │ └── Remote WSL └── /home/user/Projects/my-project I wanted to launch the Windows Antigravity IDE directly from my WSL terminal, while keeping the project, terminal, and development toolchain inside WSL. Not opening the project through \\wsl.localhost . Not moving the project to C:\ . And ideally, not patching Antigravity every time it gets updated. After a bit of digging, the solution turned out to be quite small. The setup This was tested with: Antigravity IDE 1.107.0 Windows 11 WSL2 Ubuntu zsh Antigravity was installed on Windows under: C:\Users\<user>\AppData\Local\Programs\Antigravity IDE From WSL, that becomes: /mnt/c/Users/<user>/AppData/Local/Programs/Antigravity IDE The missing piece: --remote Antigravity IDE already supports remote targets. From WSL, this works: "/mnt/c/Users/<user>/AppData/Local/Programs/Antigravity IDE/Antigravity IDE.exe" \ --remote "wsl+ $WSL_DISTRO_NAME " \ " $( pwd ) " That was the missing piece. It launches the Windows Antigravity IDE while opening the project through the current WSL distribution. So instead of opening: \\wsl.localhost\Ubuntu\home\user\Projects\my-project the IDE works with the actual WSL environment: /home/user/Projects/my-project This means the integrated terminal can keep using the Linux toolchain: node pnpm git

Using Frore’s air-cooling technology, Lenovo’s Project AeroBlade Concept is an ultralightweight laptop with efficient heat management.

Design engineers increasingly work across two systems: the visual language of a product and the implementation details that make it usable. Skills for Design Engineers from ibelick focuses on that overlap, packaging practical guidance for building interfaces with stronger visual quality, clearer interaction patterns, and more consistent engineering decisions. The project is attracting attention, with +46 stars today . That momentum makes sense: design-focused AI workflows are moving quickly, but many generated interfaces still need human judgment around spacing, typography, responsive behavior, accessibility, and component reuse. The useful way to approach this project is not as a drop-in framework. Treat it as a reference layer for your development workflow. Read the relevant skill instructions, adapt them to your stack, and keep the resulting guidance close to the codebase so it can be applied consistently during implementation and review. A lightweight local setup might look like this: mkdir -p .ai/skills/design-engineering curl -L https://github.com/sponsors/ibelick \ -o .ai/skills/design-engineering/reference.html For a real team workflow, I would convert the useful parts into a checked-in Markdown file: .ai/ └── skills/ └── design-engineering/ ├── interface-quality.md ├── responsive-layouts.md └── review-checklist.md This keeps the process portable across editors and AI assistants instead of tying it to one tool. It also makes design decisions reviewable in pull requests, which is more valuable than keeping them inside an undocumented prompt. Before using the approach in production, watch for: Context drift: generic design guidance can conflict with an existing design system, so define project-specific tokens and component rules first. AI overconfidence: generated UI still requires manual checks for accessibility, keyboard navigation, mobile behavior, and performance. The strongest ROI comes from using these skills as repeatable engineering standards—not as a

At IFA 2026, Nvidia and its partners showed off the first RTX Spark-powered laptops and mini PCs, designed to run AI models right on your computer.

Ever wondered what's happening right now on a beach in Mexico, in Red Square, or at a harbor in Norway? I run Cam-World — a free live webcam aggregator that pulls together 7,000+ public streams from 100+ countries into one searchable place. No registration, no paywall. Here's a tour of what's inside and a few things I learned along the way. 🗺 The world map is the product The heart of the site is a dark globe where every green dot is a live camera. Click a cluster, zoom into a city, open a stream — you never leave the map. Watching it for a while teaches you something: the planet has a rhythm. Webcams go online with the morning sun, and the "online" wave rolls west around the clock. 📊 Honest uptime — you can tell a dead cam from a live one Aggregators usually show you a thumbnail and pray. We check every camera automatically and show a statistics widget: the last 24 hours and 30 days as color-coded slots (online / outage / offline / no data) plus an uptime percentage. The lesson here: webcams are ephemeral. Streams die, hotels turn off cameras, storms break them. Honest stats became our most-loved feature — users check reliability before clicking play. 🔎 Search, cities, collections Search works by name, city, country and tags. There are dedicated hubs for countries and cities, and themed collections: beaches, traffic, mountains, northern lights. 🌙 Small things that matter Dark & light themes (night couch-travel vs daytime browsing), 20 interface languages, "Near me" sorting by distance, live online/offline badges on every card. Try it 🗺 World map — pick a dot, watch live 🔎 Search — find a place you love 🏠 Home feed — a rotating mix of live cameras It's free, works on mobile, and there's always something happening somewhere. What would you check first — a beach, a mountain, or your own hometown square? 👇

The game starts as a reheated Witcher 3, but evolves into something much more focused.

These WIRED-tested indoor and outdoor air quality monitors give you insights into your home’s air quality, warn of potentially harmful pollutant levels, and help keep tabs on your environment.

The idea Every OS ships a calculator. Every one of them looks the same, feels the same, and disappears from memory the moment you close it. So I built ACALCU v3 — an Akhouri Systems product — a scientific calculator that's absurdly, unnecessarily customizable. Not because a calculator needs 30+ themes and per-button styling, but because it was a fun constraint to design around: how far can you push a "boring" utility app before it becomes something people actually enjoy using? What it does At its core, ACALCU is a standard scientific calculator: basic arithmetic, sin, cos, tan, log, √, π, percentages, and a running expression engine built on Python's math module. On top of that core, it layers: 30+ built-in themes — Royal, Liquid Glass, Wild, Cyberpunk, Dracula, Nord, Solarized, Monokai, Windows 7 / Vista / 10, OneUI 8.0, Matrix, Rose Gold, Galaxy, Fire, Ice, Neon, Vintage, Sakura, Midnight, Forest, Candy, Terminal, Gold Dark, and more. Per-button customization — right-click any button to change its color, font, or set a custom image/video as its background. Every button on the grid is independently styleable. A live "Wild" theme — a small animated plant widget that visibly grows every time you run a calculation. Calculation history — a scrollable dialog of your last 50 calculations. Persistent config — every customization is saved to a local JSON file and reloaded on next launch. Full keyboard support — number keys, operators, Enter/Escape, all mapped to the same input pipeline the buttons use. Architecture The whole thing is a single-file PyQt6 desktop app, structured around a few core pieces: python THEMES = { "DEFAULT": { "app_bg": "#0a0a0a", "display_bg": "#111111", ... }, "ROYAL": { "app_bg": "#0a0800", "display_fg": "#ffd700", ... }, "LIQUID_GLASS": { "app_bg": "transparent", ... , "transparent": True }, # ...30+ more } Each theme is just a dict of colors, font, corner radius, and optional flags (transparent, wild). The Config class resolves the active theme

Can I Afford This? 1. The Story Behind the Code ​Every developer knows the late nights, the stubborn bugs, and the quiet satisfaction of seeing a project finally come to life. For the past few weeks, my world has revolved around a single mission: building ToolVerse. ​ 2. Like many of you, I looked at the current landscape of financial tools—cluttered with intrusive trackers, forced sign-ups, and paywalls—and asked a simple question: What if we could do better? ​ 3. What if people could calculate their debt consolidation, check their ACA health insurance premiums, or map out their tax withholding scenarios instantly, securely, and completely privately right inside their browser? ​ 4. What is ToolVerse? ​ToolVerse is a collection of high-intent, lightning-fast financial decision tools designed for the US audience. It runs on a lean, efficient stack: ​ 5. Frontend & Hosting: Hosted seamlessly on GitHub Pages for blazing-fast load times and global reach. ​ ** Backend Intelligence:** Powered by Vercel server-side API execution to handle complex lookups (like ACA subsidy calculations) securely without storing user data. ​Privacy-First Architecture: No mandatory accounts, no email walls, and zero data selling. Calculations happen right where they belong—on the user's device. **​ The Reality of Solo Building** ​Building this as a solo creator hasn't been a straight line. From battling server-side routing issues to optimizing sitemaps for Google Search Console indexing, every single line of code taught me resilience. There were days when things broke, but seeing those first users land on the platform and find actual value in these tools made every sleepless night worth it. ​ 8. Let's Build Together! ​ToolVerse is growing, and its infrastructure is ready for scale. 9. I am currently looking for: ​Collaborators & Open-Source Contributors who are passionate about building useful, privacy-first web utilities. ​10. Sponsors & API Partners in the US financial and health tech space

Ask your Mac anything you saw or heard Discussion | Link

Most engineers who stall at a level have the skill. What they don't have is anyone willing to explain the machine they're inside. The explanation you get from your manager is partial by design. They know their part of the process and not the committee's, so what comes back is "keep doing what you're doing, you're close." Which is true, and useless, and then you're close again next cycle. So here is the machine, reconstructed from what the four big companies publish, what their engineers write up afterward, and what levelling aggregators have pieced together. None of it is your company's internal doc. Check the specifics with your own manager. The ladders don't line up Stage Google Meta Amazon Microsoft Apple Typical YOE Entry L3 E3 L4 (SDE I) 59–60 ICT2 0–2 Mid L4 E4 L5 (SDE II) 61–62 ICT3 2–5 Senior L5 E5 L6 (SDE III) 63–64 ICT4 5–8+ Staff L6 E6 L7 (Principal) 65–66 ICT5 8–12+ Senior staff L7 E7 L8 67 ICT6 12+ Principal / Distinguished L8–L9 E8–E9 L10 68–69 Distinguished rare Google's L5 is a senior engineer. Amazon's L5 is a mid-level SDE II. Recruiters map between them and the map is approximate, so the year ranges are typical rather than required. Two things here matter more than the numbers. The gap between adjacent levels is not constant. Entry to mid is mostly about becoming reliable. Mid to senior is about becoming independent. Then senior to staff, which is where the ladder stops behaving like a ladder: it's a change of job, and the things that earned you the last promotion only partly transfer. And every company has a level it considers a perfectly good place to spend a career. Google's L5, Meta's E5, Amazon's SDE II or III depending on who you ask, Microsoft's 63 or 64. Below that level there is an expectation you keep climbing, and at some companies a clock. Above it, promotion is optional and much harder, and nobody will chase you about it. What actually happens in the room The four processes differ enough that optimizing for the wrong one wastes a year

git reset --hard HEAD~3 — run in the wrong repository window, at 6:40pm, immediately followed by the specific kind of silence that happens when you realize what you just did before your brain finishes processing it. Three commits of uncommitted-adjacent work, gone from the working tree in under a second. The first, most important fact: it's very likely still there git reset --hard moves the branch pointer and resets the working tree, but Git doesn't actually delete commit objects just because nothing points at them anymore — they sit in the object database, unreferenced, until garbage collection eventually cleans them up, which for most repos happens rarely enough that "eventually" can mean weeks. git reflog a1b2c3d HEAD@{0}: reset: moving to HEAD~3 e4f5g6h HEAD@{1}: commit: add retry logic to payment webhook 7h8i9j0 HEAD@{2}: commit: fix currency rounding k1l2m3n HEAD@{3}: commit: initial webhook handler The reflog is a local log of everywhere HEAD has pointed recently, and it survives a reset because a reset is just another entry in it, not an erasure of the ones before it. git reset --hard e4f5g6h Working tree restored to exactly the state before the reset, all three commits back, in the time it takes to read this sentence. When the reflog isn't enough If the commits were never made at all — you ran reset --hard on genuinely uncommitted changes — the reflog can't help, because it only tracks where HEAD and branches have pointed, not file contents that were never committed. That's a real loss, and the only real defense against it is committing early and often, including throwaway "wip" commits you intend to squash later, specifically because an uncommitted change has no recovery path at all. If the commits were committed and the reflog entry has expired — Git's default is to keep unreachable reflog entries for 90 days, reachable ones for longer — git fsck --unreachable can sometimes still find dangling commit objects directly: git fsck --unreachable --no-reflog |

Claude Cowork for high-volume GTM workflows Discussion | Link

1. How this project started? I'm going to be honest, it's been ages since I have written something without the use of AI to fix my writing. English is not my first language so please bear with me! With the rapid rise of AI, I felt that I have been losing passion for what I used to love at some point: learning . Nowadays, we can quickly solve most of our problems with the use of AI, often times, not even reviewing if it correct or not. That's why I decided to take some time daily to learn something new without or minimal use of AI. The first step is deciding, what should I try to learn first? Well, it was quiet easy to find out what. If you are into Linux, you have probably heard of Omarchy at this point. Like it or not, there's no deny that it's getting more popular among developers. So, why not try to build a decent looking Arch workspace? Before continuing, I would like to mention that this is not a guide. There are lot of resources online that teaches you how to install Archlinux and other packages. 2. Why Archlinux? Archlinux has -or had- the reputation of being difficult to get started with. Most of us are used to booting into a nice-looking, functional operating system. Although I have some Linux knowledge, I wanted to have a better understanding of what it takes to have a decent workspace. 3. Installing Archlinux The first step is actually installing Arch on my device. The device I'm going to use is my trusty built PC that I currently use exclusively for gaming. There are a few things to consider before jumping into installing Arch: My PC has an Nvidia RTX 5050 and AMD Ryzen 5 CPU. Need dual boot to switch between Windows 11 and Archlinux. I don't want to change the BIOS options repeatively. With this in mind, I quickly created a bootable USB using RUFUS . 3.1. Booting the USB If you are a Windows 11 user and have dual boot, you may know that Windows requires Windows Secure Boot. In order to boot another operation system, you'll need to change your Secure Boo

Most intelligent workhorse yet for coding and agents Discussion | Link

Amazon just hiked prices on Kindles, Echo speakers, Eero routers, and Fire TV devices ahead of the holiday shopping season.

A three-year group chat is a knowledge base nobody can read. Somewhere in it is how long the tax office actually took, which form replaced the old one, which accountant people quietly stopped recommending. Telegram's search finds a word you already know. It cannot answer a question. The fix is boring in outline: get the history out, turn it into documents, hand them to something that reads — NotebookLM, in my case. I built that pipeline for real chats. The parsing has traps, and I list them below, but the design problem is elsewhere: packing, and making the second run idempotent. Two clients, two shapes Export exists in exactly two places. Telegram Desktop has had it since 2018 and offers JSON or HTML. The native Telegram for macOS app — the Mac-only client, not Desktop — added Export Chat History… in 12.10 (24 August 2026) and writes HTML only; the Mac App Store build was still on 12.9, without the menu item, at the end of August. Telegram Web and the phone apps have nothing. So you have to read both formats: JSON — one result.json with the chat's name at the root and a messages array: {id, date, from, text, text_entities} per message. HTML — paginated. messages.html , messages2.html , messages3.html , one page per file, each a few MB. text is not a string In the JSON export, a plain message has text: "hello" . A message with a link, a bold run or a code span has an array of runs : "text" : [ "see " , { "type" : "bold" , "text" : "section 4" }, " first" ] String(msg.text) on that gives "[object Object]" in the middle of your document, and it does it silently. Join the runs instead: // Telegram writes a formatted message as // text: ["plain ", {type: "bold", text: "…"}, …] — String() gives "[object Object]". function contentValueToString ( v : unknown ): string { if ( v === undefined || v === null ) return '' ; if ( Array . isArray ( v )) { return v . map (( x ) => x !== null && typeof x === ' object ' && ' text ' in x && typeof ( x as { text : unknown }). text ===

The Comfort Zone Trap Most developers hit a point where they know enough to be productive, and then... stop growing. You can build features, fix bugs, ship code — and still be standing still. The comfort zone doesn't feel like stagnation. It feels like competence. This is one of the sneakiest traps in a dev career. Early on, growth is forced on you — every new project throws unfamiliar problems your way, and you have no choice but to learn. But once you've built a solid mental toolkit (a stack you're comfortable in, a set of patterns that "just work"), it becomes very easy to keep reaching for the same tools on every new problem. You're productive. You're shipping. And you're not actually getting better. The danger is that this plateau is invisible from the inside. Nobody sends you a notification saying "you've stopped growing." You just keep doing what you know, at the same level, for years — until you compare yourself to someone who deliberately kept pushing, and the gap feels much bigger than it should. Why "Just Keep Coding" Doesn't Work The common advice is to just build more projects. But volume without friction doesn't teach you much — repeating the same patterns on new ideas just reinforces what you already know. Growth comes from deliberately picking problems slightly outside your current skill ceiling, not from doing more of what's comfortable. Think about it like weightlifting. If you lift the same weight every session, you get very good at lifting that exact weight — and nothing more. Progressive overload works because you're constantly pushing slightly past your current limit. Coding is the same. If every project you build uses the same stack, the same architecture patterns, and the same problem shapes, you're doing bicep curls with the same 10kg dumbbell for five years straight. The fix isn't "build more" — it's "build harder." Pick a project that forces you to learn a new paradigm (functional if you're used to OOP, distributed systems if you've only b

The only app that owns your whole menu bar, in and out Discussion | Link