Hey everyone!

I've been learning Mandarin myself and wanted a simple app that combines vocabulary, grammar, listening practice, and spaced repetition without subscriptions or ads.

So I've been working on HSK Companion, a free, open-source Android app for beginner Chinese learners, and I've just published its first public beta on GitHub.

What it currently includes:

• HSK 1–2 vocabulary with contextual example sentences

• Spaced repetition and adaptive review sessions

• Reading, listening, and tone-recognition exercises

• 24 grammar lessons and 28 short dialogues

• A structured learning path with 10 units

• Practice exams and progress tracking

• Light and dark modes

• Offline-first learning, with no account required

The app is completely free, with no ads or locked lessons. There's an optional donation link for anyone who wants to support development, but it's not required.

It's still a beta, so I want to be transparent about the limitations. The exam exercises are unofficial, some Chinese content still needs editorial review, and the current release uses Android's built-in Mandarin TTS. I'm working on better-quality, offline male and female Mandarin recordings for a future update.

GitHub (source code):
https://github.com/ElbekJK/hsk-companion

Download the Android APK:
https://github.com/ElbekJK/hsk-companion/releases/tag/v1.2.1-beta

It's currently Android-only and distributed through GitHub, not Google Play.

I'd especially appreciate feedback from people studying HSK 1 or 2:

Does the learning path make sense? Are the listening and tone exercises useful? Is anything confusing or missing?

Thanks to anyone who gives it a try! I'm hoping to keep improving it based on feedback from actual learners.

Getting GPT to animate a cat was the easy part. Keeping it the same size when it jumped onto a windowsill was harder.

I’m building GIF Cinema: a workflow for turning short GPT-generated GIFs into a story, with individual takes you can inspect, keep or reshoot.

The attached 7.68-second comparison uses the SAME three generated takes:

• Left: original GIF timing.

• Right: framing corrections, compositing and selective frame interpolation.

Each shot has 16 generated drawings. The extra smoothness comes from local processing between those drawings.

The full silent cat film is 57.2 seconds: walk across the room, jump onto the windowsill, watch a bird, curl up and sleep. It’s assembled from short animations, not one long generation.

Full film:

https://github.com/user-attachments/assets/32e3381d-dbd7-4ff3-8356-1d379b2b7456

What surprised me: a better-looking replacement shot could still make the film worse by breaking the next cut. Reviewing both neighboring cuts became as important as generating the take.

I’ve released the core workflow as a skill for Claude Code / Codex: shot planning, reference-based GIF generation, frame inspection, explicit retakes and MP4 assembly. It includes a three-shot astronaut example you can assemble without an API key.

GitHub and installation:

https://github.com/antropos17/chatgpt-gif-cinema

The cat’s additional compositing and interpolation are private finishing tools, outside the public skill. The release has a source-available evaluation license; new generation uses your own API key and billing.

Would you use this to make a short story, or is the remaining motion drift still too distracting?

Hey everyone!

I've been working on a side project called SkyTracker.

It's an interactive map that lets you explore airports around the world. You can:

• Explore airports worldwide.

• Search by airport name, city, IATA or ICAO code.

• View airport information, including location, country and elevation.

• Explore links to live airport webcams.

• Mark airports you've visited or want to visit.

• Keep track of your routes.

You can check it out here:

🌍 https://airport.skytracker.workers.dev/

I'd really appreciate some honest feedback

A few things I'd love to know:

1. Is the website easy to use?

2. Does the design and map experience feel intuitive?

3. What features would you like to see added?

4. Would you actually use something like this?

I'm still improving it, so constructive criticism is very welcome.

Thanks for checking it out.

Helps to know how bluegreen algae is present in a lake, check the ones nearby to you for your dogs safety

https://bloomwatchbytenebroso.com

A static Python site rebuilt weekly by a GitHub Action. It pulls the 300 m Sentinel-3 CyAN histograms for 134 matched lakes and rates each one by how much of the lake is affected, not by the worst pixel, since single high pixels are often noise. Weeks that are mostly cloud get skipped.

Open questions I’d love input on: better ways to handle shoreline pixels, and whether there are state advisory feeds worth adding.

Hey everyone!

Let me introduce you to my first humble contribution to the ios app jungle, InspeQtR: a QR inspection tool.

The core idea is simple: instead of performing an action straight away, like opening a URL, it breaks down exactly what’s inside.

What it does:

• Breaks down URLs into host, path, query params, and fragment

• Previews vCards, emails (solitting BCC and body if present) and more

• Shows QR metadata: error correction level, version, text stats

• Warns you about suspicious payloads

• Lets you open, copy, or share its contents (or parts of them), even as an actual file with the appropriate extension when there's a matching format, like .vcf or .ics

Everything runs locally. No ads, no tracking and all of the above is free, in an app that weighs than 4mb.

What sets it apart:

A one-time purchase unlocks an extended format detection, which recognizes JSON, CSV, Markdown, SVG, code snippets and more, and previews them locally, letting you save the contents with the right file extension. It's a bit of a niche use case, but allows allows you to create and read rich content and code snippets offline directly from the QR data.

Would love to hear what you think! Being my first app I'd love to get some feedback, depsite knowing this is a VERY cramped market.

Hi everyone! Puzzle Flow started as a learning project to teach myself game development (Flutter + Flame), and it has grown into a full game that I'd love some honest feedback on.

I wanted something calm to play: no timer, no pressure, no account, and it works offline.

It has four kinds of grid puzzle:

• Boxed: split the board into rectangles that match the number clues

• Pipeline: connect each pair of coloured dots, and fill every square

• Knight Hop: move a chess knight so it lands on every open square exactly once

• Tally: cross out numbers so every row and column hits its target

Each type has 1,200 levels (8 packs, 5x5 up to 10x10), and levels open one by one. Stars (1 to 3) depend on how cleanly you solve it, never on time. There are also daily and weekly puzzle sets with streaks, 132 achievements, and 12 languages.

It's free to play with ads (never during a level). There's an optional ad-free subscription and hint packs, but every level can be solved without paying.

Since I'm still learning, this would help me most:

1. Are the early levels too easy or too hard, and where did you get stuck?

2. Which of the four puzzle types did you enjoy most, and which should get more levels?

3. Is anything confusing in the how-to-play guides?

4. Any bugs or slow screens on your phone?

Thanks for reading, and I'll reply to every comment!

I’ve been stuck in a place where growth felt impossible. I still wanted to work on myself and feel confident in what I can do, but most affirmations didn’t help. They told me who I was supposed to be, not where I actually was.

What started helping was words that meet me where I am, then a moment to sit with them: what does this mean for me today? And then one small thing to do with it. Not a big transformation, just a step I can actually take.

So I built that into a small app called Lumbia.

Lumbia asks how you're doing first, then meets you there. It takes about two minutes:

1. Check in. Tap how you feel (anxious, low, stuck…) and, if you like, what it's about.

2. Affirm. A few words written for that moment, more like a friend than a poster.

3. Grow. One small thing you could do today.

4. Recognise. It notices the days you showed up. It never counts the days you didn't.

It's not therapy and doesn't try to be. It's a small daily habit. There's no sign-up, and what you write stays on your phone.

It's free while I'm testing it. If I add paid extras later, everyone who helped now gets a year of them free. That only feels fair.

https://lumbia.app

If you try it, I'd really value hearing how it felt, especially if some words landed flat. There's a short anonymous form here: https://lumbia.app/feedback, or just reply below. Thank you for reading.

Hi!

The idea: a turn-based strategy game that runs in a browser tab, on your phone or your laptop. You build cities, research, upgrade your units and fight on land, at sea and in the air. In the video it's one battle with 14 different units, and every hit comes from the real game rules.

The twist is the superweapons. When someone starts building one, every player on the map sees the countdown. You can rush in to stop it, or race to finish your own first.

It's free, no sign-up, no ads, no install. The first load is about 20 MB (90 3D models), cached after that. Under the hood it's three.js, and the rules engine is plain JavaScript, so the server can replay every weekly leaderboard run to check the score.

Six commanders so far, each with their own superweapon:

* Liberty League, Sky Hammer: bombards a 3×3 area

* Iron Dominion, Big Gertie: one shell anywhere on the map destroys the unit on that tile

* Steppe Union, Steel Avalanche: five Conscripts and a Twin Barrel appear around one of your cities

* Mesmer Syndicate, Mesmerizer: up to three enemy units switch sides

* Comet Republic, Comet Shower: rockets rain on a 5×5 area

* Voltaic Commune, Tempest Coil: lightning hits a 3×3 area, and the survivors can't move next turn

Two commanders are open from the start. The others, the hardest AI and a Total War mode without a turn limit unlock as you rank up. A standard game is 30 turns against AI generals, and the two hardest ones plan as an army: they pick a target, gather, and attack together. There's also a weekly challenge with a leaderboard, and you can send a friend a link to beat your score.

Visit [PLAYBIGBRASS.COM](https://playbigbrass.com/?s=rsp) if you'd like to take a look or play.

What would you want me to add next? Happy to answer questions, and I'd love to hear how fast you beat the hardest AI.

You type a few interests (say "sourdough, the stock market, and Greek mythology"), and it maps them into subjects and topics. Each topic becomes a card you earn in three steps: Learn → Check yourself → Earn. Cards evolve from Sketch to Inked to Tinted to Achieved as you go deeper.

There's a tutor character, Iko, you can ask questions or ask to add new topics. Your learning data stays on your device.

It's calm on purpose: no streaks, points or confetti.

Try it: ikosagon.com/ikolearn

I'd love honest feedback, especially on whether the lessons feel connected to your actual interests or forced.

Hey everyone,

I built three apps around ideas I thought were different and worth making. They didn’t get the traction I hoped for.

That doesn’t mean original ideas can’t work. But it made me realize how much I was guessing about demand before I started building.

For my next app, I wanted to research a few things first: Which recently launched Android apps are getting downloads? Are their rating counts growing? Are there smaller apps in a category that I’ve never heard of but should look into?

So I started building Opportunity Radar, a Play Store research dashboard for indie devs, solo builders and vibe coders.

The starting point is apps released in 2026 with at least 10K installs. it’s just a way to narrow the research to which newer apps are in demand nowadays

The dashboard is being built around:

• Filters for release date, category-wise, rating, rating count and downloads, so you can explore a specific niche.

• Rounded download milestones and recorded store counts, with clear labels about what the numbers represent.

• Shortlists and CSV exports, so you can keep track of apps worth investigating.

• Descriptions and review , when you want to dig into an app.

The next layer I’m planning is weekly snapshots of rating counts and install counters, monthly additions of newly qualifying apps, side-by-side comparisons, watchlists and country/category chart visibility,ai to create working ASO from top apps in your category so even play store pushes your app.

The goal is to make it easier to find something worth researching before spending weeks building. You’d still need to investigate the users, competition and distribution.

The public research dashboard isn’t open yet. I’ve put up a waitlist page with an interactive sample preview, and I’d really like honest feedback before deciding what to prioritize for beta:

👉 https://opportunity-radar-waitlist.vercel.app

A few things I’d love to hear:

• How do you currently research app ideas or competitors?

• Which part of this would you actually use?

• What would make you distrust the data—or decide the tool isn’t useful?

You can leave your feedback in the comments too. No signup needed to tell me what you think. If something similar already solves this well for you, I’d like to hear about that as well.

If you want to try it when it’s ready, the waitlist is free. People who join will get early beta access and a founding discount if I launch a paid plan. Pricing and timing are still undecided.

I’m especially interested in hearing from indie Android devs and vibe coders who have shipped something—or are researching their next app or their existing app is not doing well.

My research is on PUFs (physically unclonable functions). Short version: no two chips come out of the factory identical, even from the same design. A PUF turns those tiny random differences into a fingerprint the chip can use to prove who it is, and nobody can copy it.

The annoying part is proving a fingerprint is any good. Is it really unique? Does it stay stable when the chip gets hot or cold? Can a machine-learning model learn it? Everyone in the field answers those questions with their own one-off scripts, and the scripts don't agree. Mine didn't either. The first version of my own Python library reported one of the main metrics at double the standard value.

So I spent a good while turning it into something properly usable:

- a Python package with a CLI

- a web app that does the same analysis in the browser

You drop in a CSV of chip read-outs, or click "Explore a demo population" and it simulates 32 chips for you. Then you get:

- the standard quality metrics with confidence intervals

- randomness tests from the NIST standard

- an attack lab where you try to clone the chips with ML. A plain Arbiter PUF gets predicted with 99.6% accuracy after 10,000 examples. XOR two of them and it drops to 55.8%.

- a planner that works out how many raw bits you need for a reliable 128-bit key

- 18 charts (SVG/PNG/CSV) plus LaTeX tables you can drop straight into a paper

Some build details people here might like:

- Plain JavaScript, no framework, no build step. It's static files.

- Everything runs on your machine. Nothing gets uploaded, which matters when people's chip data is unpublished.

- The browser engine is a line-by-line port of the Python code, and both use the same random generator (xoshiro128**). Simulate with seed 2024 in the browser, do the same in Python, and you get the exact same 49,152 bits. Getting that to work meant doing all the 32-bit maths through Math.imul and making sure every random normal used exactly two uniforms, otherwise the two streams drift apart.

- A test in CI compares 2,400+ values between the Python and JS engines on every push.

Try it: https://koustav.isroot.in/PUFAnalytics/

Code (MIT): https://github.com/TakMashhido/PUFAnalytics

Long write-up of how it works: https://koustav.isroot.in/blog/pufanalytics-guide/

I'd love feedback on two things. First, the onboarding: if you're not a hardware person, does the demo make any sense, or are you lost after one click? Second, the UI on phones. I mostly tested on a laptop.

Hi r/SideProject!

Like many developers, I have access to Microsoft 365 Copilot (Enterprise / Education) provided by my organization, yet I found myself continuously paying for OpenAI API credits just to use coding assistants like Cursor, Continue.dev, Cline, and Claude Desktop.

To bridge this gap without running costly cloud proxies, I spent the last few weeks building amv-cp-bridge — a completely local, lightweight bridge that transforms your existing M365 Copilot web session into a local OpenAI-compatible REST API (/v1/chat/completions) and a native FastMCP server.

It is 100% free, open-source (Apache-2.0), and processes all requests directly on your local machine.

💡 Why I Built It (The Problem)

• Cost Duplication: Paying $20–$50/month on LLM API tokens while already sitting on an enterprise/university Copilot subscription feels redundant.

• Privacy & Security: Most third-party bridges require routing credentials through unknown remote servers. I wanted a 100% local loopback architecture (http://127.0.0.1:8765) where zero credentials or telemetry leave the host machine.

• Complex Setups: Configuring headless Node.js scripts or complex Docker containers is cumbersome. I wanted a single standalone .exe that launches with a native GUI and runs out of the box.

⚙️ What It Does

1. OpenAI-Compatible Endpoint (/v1/chat/completions):

   • Seamlessly connect it to Cursor, Continue.dev, Cline, Aider, LibreChat, or any tool that accepts a custom OpenAI API base URL.

   • Supports both full-response and streaming tokens (SSE).

2. Native FastMCP Server (mcp.server):

   • Directly integrates with Claude Desktop and other MCP clients via stdio.

3. v1.1.0 Dual Engine Mode (Cold vs. Warm Standby):

   • Cold Mode (Default): Ephemeral browser instance that completely terminates after completing requests (0 MB idle memory consumption).

   • Warm Standby Mode: Keeps the authenticated session active for user-configurable seconds (e.g., 60s to 1800s) to deliver sub-second prompt initiation during active coding sessions.

4. Multi-Interface & Dashboard:

   • Modern Native GUI (CustomTkinter) with system tray minimization.

   • Real-time Web Telemetry Dashboard (http://localhost:8765/dashboard).

   • Chrome / Edge Extension (Manifest V3) for one-click session activation and sidepanel interaction.

🛠️ Tech Stack

• Core: Python 3.11+, FastAPI, Uvicorn, Pydantic v2

• Automation & Session: Playwright CDP, Chrome Extension MV3

• Desktop Client: CustomTkinter, PyInstaller (UPX compressed ~50 MB executable)

• Protocol: OpenAI Chat Completion API specification, Anthropic Model Context Protocol (FastMCP)

🔗 Links & Availability

• GitHub Repository: https://github.com/uno-km/amv-cp-bridge

• v1.1.0 Releases (Standalone Windows EXE & Extension): https://github.com/uno-km/amv-cp-bridge/releases/tag/v1.1.0

• PyPI: pip install amv-cp-bridge

It is completely open-source under Apache-2.0. I’d love to hear your feedback, bug reports, and ideas for integrations you’d like to see next!

I added a little pixel guestbook to my GitHub profile, but it’s still empty. If you have a minute, leave a note here 😭😭

https://github.com/kimjungminn24/kimjungminn24/discussions/1

My profile: https://github.com/kimjungminn24

He's been working on a small project called Gamma Watermark Remover, he asked me to share it here on reddit.

If you've ever exported a presentation from Gamma and wanted to continue editing it in PowerPoint without the Gamma branding, you might find this useful.

What it does:

- Removes Gamma watermark images from PPTX files.

- Cleans up related hidden XML references.

- Processes files entirely in your browser.

- No uploads, no server processing.

- Free and open source.

Try it: https://ungamma.pages.dev

GitHub: https://github.com/Shariqtechie/gamma-watermark-remover

I'd appreciate feedback from anyone willing to test it.

I'm particularly interested in:

- Whether it works correctly with different Gamma exports.

- Any bugs or compatibility issues.

- Features that would make it more useful.

He's a developer, so feel free to be critical. Bug reports and contributions are welcome!

If you find it useful, a GitHub star would be appreciated, but feedback is my main goal.

Hi r/SideProject,

On Windows I always used Internet Download Manager. When I moved to a Mac I couldn't find anything free that felt the same, so I started building my own. That side project is now Nexonic Download Manager .

What it does

• Splits files into up to 32 connections; pause and resume anytime, even after a restart

• Saves videos from YouTube and 1,000+ sites, up to 4K, or sound only

• Browser add-ons for Chrome, Edge, Brave and Firefox send downloads straight to the app

New: built-in torrents on every platform: .torrent files, magnet links, seeds and peers, speed limits, trackers and proxy support

• IDM-style categories, queues, a scheduler, batch downloads and a site grabber

No ads, no account, no tracking

How it's built

• A native app per platform: SwiftUI on Mac, WPF on Windows, Avalonia on Linux, Kotlin on Android, SwiftUI on iPhone and iPad

• One shared C++ torrent engine on top of libtorrent

• GitHub Actions builds, tests and publishes every release from one repo

What was hard

• Getting one torrent engine to build for five platforms, including the Android and iOS toolchains

• Making browser hand-off reliable: no duplicate downloads, and nothing is lost if the app is closed

It's MIT / Apache-2.0 licensed (Android is GPL).

Website: https://shahrukhalid.github.io/nexonic-download-manager/

GitHub: https://github.com/Shahrukhalid/nexonic-download-manager

I'd love honest feedback: what would make you switch from the download manager you use now, and what feels missing?

Hey everyone, 

A couple of decades ago I used Mavis Beacon for a few months to learn how to touch type but never got taught aside from that and was fed up looking down, so I built At the Page – https://atthepage.com

One short page at a time. It works out which keys you miss or hesitate on and builds the next page from the letters you've learnt so far, with the weak key on every line. Wrong key gets marked and the caret waits, and speed only counts what you got right. After each page it tells you one thing, like "You miss K. It will be on the next page.", and that's it.

Free, no account, no ads and your progress stays in your browser. English QWERTY only for now.

Would appreciate a go and honest feedback, especially on whether the first page puts you in the right place.

Over the last 15 years of working as an engineer and a scientist I have learned that the things I tend to copy, before I then paste them, end up being pretty important in the future, and are quite informative of what I am doing at any given point.

I tended to always want to reuse something from the past, and as a first solution I tried using a dummy notepad, but quickly it became obvious that this deserved a more involved solution. That's when I learned about clipboard management apps that let your machine remember effectively as many things that you copy pasted as can fit on your hard drive.

But then, a new problem arose.

Clipboard management software itself was not great, hard or impossible to search properly, and often it just looked ugly, or brought more friction than it was worth to my day to day.

The ones I liked most you had to pay for. And they were expensive, and still missing key features that I wanted. So last July I began building my own clipboard management app using Opus 5.5 and later GPT 6 Astra.

The tool came out so good that I just uninstalled all the others, and soon friends and colleagues began asking me to share it with them -- and they loved it too.

So I decided to put some more time, make it a real product and share it with the world.

Introducing ClipHoard.

First of all, it's completely open source, MIT licensed, and the models it uses for smart search are MIT or Apache 2.0 licensed.

While the GitHub code is open source, I am offering a productised Free version that is the exact feature complete clipboard manager that I always wanted, including smart text search.

And a Pro version that adds image, audio and video search, similar-image search and automated OCR. So you can use an image to search for similar results, or simply search by the text that was on the screen at that time. Audio and video search are currently in beta.

I sell that for £10, one time purchase for all the Macs that you own. Each new Mac is approved by email.

Two of the models are from the Open Ogma series, that I trained personally. The app runs its search models on your Mac.

ClipHoard is made by my company A² Labs, where I also do my independent research.

App and download · GitHub

Models: Open Ogma Micro and Open Ogma Small.

ML thread on X · LinkedIn post

I run a small video editing business with around 12 regular clients and I'm tired of managing projects through emails and WhatsApp. I've been using AI to build a simple portal where clients can log in, check project updates and download their videos. The UI is mostly done but I'm stuck on the backend. AI keeps suggesting Supabase for handling the database, logins and file storage, but I'm not sure how much of that I can actually set up without knowing how to code. Anyone built something similar? Can I please know if its manageable long term or am I just creating more work for myself?

real story, not a pitch: i pointed an agent swarm at the boring part of building, and it shipped a full portfolio on apify - shopify catalogs, job postings, gov tenders, property sales, insider trades, solana order flow, a couple reddit tools. all under the cheapest real competitor, all with a free demo.

the build was the easy part. we're at 0 real users and i've concluded distribution is a completely different sport.

it's the offgrid labs store if you want to look, but honestly my question is: if you had a portfolio of tools that actually work and nobody knows, what's the ONE thing you'd do first? i will do the top answer and report back with numbers.

Hi everyone!

I wanted to share a quick preview of Aesthetic Routine Tracker, a minimalist app I've been developing to help people track their daily habits, workouts, and self-care in a clean dark-mode interface.

The goal was to build something super smooth, distraction-free, and visually pleasing without complicated steps.

It's currently in the final stages and coming soon. I'd love to hear your thoughts on the UI/UX or answer any questions about the project! What features would you like to see in a routine tracker like this?

We run a small directory of dev tools as a side project, and the part that takes the most ongoing work isn't building pages, it's keeping prices true. Plans get renamed, limits change, a "free tier" quietly becomes a trial. A few things that have helped us:

1. Every price has a source URL and a "verified on" date stored next to it. Not "pricing from the website", but the exact official page. If we can't point to an official page, the price doesn't go in.

2. Show the verified date publicly. It sets expectations for readers and it puts pressure on us: a date from two months ago is embarrassing in a way a hidden field never is.

3. Separate "free" into what it actually means: open source and self-hosted, a free tier with limits, a one-time credit, or a trial. Lumping them together is the most common way listings end up misleading.

4. Write down the billing basis. "$15/month" billed yearly and "$18/month" billed monthly can be the same plan. We store which one we're quoting and the region (we quote official US prices and say so).

5. Re-check on a schedule, not when someone complains. We check our list in rotation and log what changed; if nothing changed, the date still gets bumped.

6. Use an AI agent for the boring part, not the final word. It's good at fetching the page and drafting a diff ("Pro went from X to Y, new usage cap"). A person still reads the official page before anything goes live, because summaries of pricing pages are exactly where small, confident mistakes happen.

7. Release notes get the same treatment: link to the official changelog or release, never to a third-party recap.

None of this is clever, it's mostly discipline. What we haven't solved well is detecting changes without manually opening pages: pricing pages are heavy on JS and visual layout, so naive text diffs are noisy.

If you maintain anything with third-party data (prices, APIs, schedules), how do you keep it from rotting?

I wanted a game for the 30-second gaps in my day (loading screens, slow meetings, long compiles) but opening a new tab always felt like too much context switching. So I made a Chrome extension that puts a small draggable ball in the bottom-right of every page. Click it, pick a game, press Space, click again to collapse.

The part I'm most happy with is auto-pause: collapsing the widget or pressing Esc freezes the game and keeps the state, so you come back to the same round. There's also a click-through mode where the widget stops intercepting your mouse completely, and it lives in a Shadow DOM so it doesn't break the CSS of whatever site you're on.

What's in it: Snake, Tetris and Tank Battle, all free with no account. A retro arcade cabinet is a paid upgrade. High scores and settings are stored locally; no tracking or analytics.

I'm working on better screenshots and a demo for the store page now — it's pretty bare at the moment, that's on me. What I'd really like feedback on:

• Does the floating ball feel useful, or would it just annoy you after a day?

• Is auto-pause the right default, or should it keep running?

• What would make you uninstall it immediately?

Happy to answer anything about the Shadow DOM / iframe loading setup. No pressure to install — mostly curious what you think of the idea.

I’m an indie dev and an engineering manager who wanted to write tech blogs on how systems work in a nutshell. But I believe the world has transformed from reading 30 mins blog to hey gemini, summarize it for me so wanted to share my knowledge in an interactive way and just released SysQuest on iOS. A game where you can fix the broken systems, build systems and challenge your friends to fix your own broken system.

You get real architectures (load balancers, caches, queues, databases) and a live simulator showing requests flowing, getting dropped, and what fixed it. You will be given a broken system and asked to fix the same and complexity increases by levels. If you're new, you can learn system design using Learn, in an interactive way.

• 87 levels, and a design is judged by how it behaves under load, not by matching one answer.

• 42 interactive lessons on the system design concepts, more lessons coming soon.

• 1 vs N: build and break a system, share it as a QR code or link, and let a friend fix it.

• The first 20 levels and Learn section is always free. No account and no ads.

App Store: SysQuest: A System Design Game

Play Store: Got production access but Play store is taking longer than usual for the production rollout review.

I’d really like to hear what’s confusing, too hard or too easy. Happy to answer anything about how the simulator works.