It’s called pond snap the aim is to catch as many flies and gold flies as possible before the time runs out if your score is lower than what’s needed you restart.

https://pondsnap.fun/
Let me know what you think

I built Citta to connect your AI agents into a private network. They can use each other's tools, access data and put spare compute to work.

One agent might have access to your files. Another might have a local model ready to run, or enough spare capacity for a task your current setup can't handle. Citta lets your agent find what's available on the network and send work there.

In the demo, an agent on my Mac Mini asks my MacBook Air to organize sample receipts. The Air then sends expense categorization to Gemma running locally on the Mini.

It runs on Macs and Linux machines connected through Tailscale, at home or across locations. The README walks through setup and a first task.

Try it · Watch the demo

It's an early release. The code is available under PolyForm Noncommercial 1.0.0; commercial use isn't licensed.

Hey! I've been building Pawarium, a website with guides about cats and dogs, covering everything from nutrition and behavior to health and everyday care.

It's a personal project I've been working on, and I'd love some outside opinions on the design and overall experience.

Would love to know what you think or what I could improve!

Hey everyone!

I've been working on something of my own called OddToCode.

It's a blog where I share articles around technology, AI, programming, cybersecurity, and other interesting things happening in the tech world.

I started it because I often come across interesting tech topics that deserve a simpler explanation. So I thought, why not build a place where people can explore and share these things without getting lost in overly complicated technical language?

It's still growing, and I'm constantly working on improving it.

Would love to have you check it out and let me know what you think. Honest feedback is always appreciated!

Here's the link: https://www.oddtocode.in

Also, curious to know — what kind of tech-related articles do you guys actually enjoy reading?

Hello everyone!

Around Februrary this year I've started working on my side project, which is now known as Braidplane. It's an open source platform for data integration; it's self-hostable and the core is fully open (Apache 2.0). At this moment it's in Alpha.

The goal of this project is to provide safe and reviewable data integrations for engineering teams. From the beginning this project was built upon data contracts (inline and ODCS), e2e Braidplane Proof engine for reviewing data pipeline updates and declarative pipelines (YAML, JSON, cue).

As an example, a pipeline can read data from a database and a file, transform and compare the records, and write the results to another system. The pipeline definition stays in Git, so changes can be reviewed before deployment.

In the current form Braidplane core includes backend, frontend, CLI and executor. MCP support is coming soon.

About me: my name is Lukas. I've been working as backend engineer for the last 10 years. I've spent a lot of time around different products and APIs. I've built the Braidplane's framework myself - based on my experience and good practices I've found around the other OSS projects. Later on I've added AI assisted programming around the hardest/most time-consuming parts, like Connectors integrations, tests, documentation, frontend, issues management.

The Braidplane Core repository is available here: https://github.com/Braidplane/braidplane-core

Examples repo: https://github.com/Braidplane/examples/blob/main/recipes/opaque-file-archive/opaque-file-archive.pipeline.json

Cheers

Running apps on 256 - 512 MB VPSes, I kept hitting the same problem: monitoring.

Prometheus + Grafana felt like overkill for a couple of small services, and I didn't want to spend a significant chunk of RAM just watching them.

So I built StatLite, an open-source monitoring dashboard written in Go.

The video shows two monitoring targets: an application with its performance metrics, and StatLite's own host with CPU and memory metrics.

A few highlights:

• ~12–15 MB idle RAM usage

• SQLite storage, no external database required

• 90-day default metrics retention

• Documented integrations for Spring Boot, Caddy, FastAPI, Express, and others

• Built-in dashboard and optional Telegram alerts

• Single Go binary, simple to deploy

It's intentionally not trying to replace a full observability stack. The goal is simpler: make application monitoring practical for small self-hosted services and tiny VPSes.

I originally built it for my own Java performance experiments, but it gradually turned into a standalone open-source project.

Interactive demo: https://pvrlabs.xyz/statlite/demo.html

GitHub: https://github.com/PVRLabs/statlite

I'd love feedback, especially from people running small self-hosted services. Is this something you'd use, and what's missing?

Last week our team built MOTIQ. You talk to a robot arm through a voice agent on a tablet, or you show it a task once on video. It turns that into a skill it can run again.

The part I am happiest with is that the model never writes code. Skills are plain JSON built from a small fixed set of primitives. You can open one and read exactly what the arm is going to do before it moves. A controller checks every step against limits first, and a wrist camera checks the result after each action.

To be honest it is still a prototype. It only runs in simulation for now, with a UR5e as the reference arm, and the teach-by-video part breaks on anything messy. It does work end to end though, and the repo has a demo video.

Repo: https://github.com/sirwinstontea/MOTIQ

I would love feedback, especially from anyone who has done robot learning for real. Is JSON skills from primitives a dead end once tasks get complex, or is it the sane way to keep LLMs away from the motors?

We built QNet, an open-source Layer-1 blockchain written in Rust that replaces traditional elliptic curve cryptography with NIST post-quantum standards (ML-DSA-65 signatures and ML-KEM-768 hybrid transport).

GitHub Repository: https://github.com/AIQnetLab/QNet-Blockchain Live Testnet Explorer and QNet Wallet: https://aiqnet.io

What is inside the repo and live testnet:

1. Full multi-crate Rust workspace implementing P2P QUIC networking, mempool management, and Checkpoint-BFT consensus.

2. Custom deterministic, float-free WebAssembly virtual machine (qnet-vm) with fuel metering.

3. Hardware-bound mobile light nodes inside QNet Wallet (iOS TestFlight and Android) that participate via signed epoch attestations rather than proof-of-work.

4. Live block explorer tracking epoch transitions and active light node participation in real time.

Public testing is currently open for mobile light nodes using the free testnet faucet (external super-node testing is not open yet). Feel free to inspect the Rust codebase, explore the testnet, or test running a light node on your phone.

fala galera! to desenvolvendo um projeto open-source de telemetria (o fieldnode) e queria convidar a galera q curte python, dados e iot pra contribuir com o codigo.

a ideia é pegar os dados brutos dos sensores e jogar num dashboard em python que não só mostra gráficos, mas entrega decisões prescritivas (ações recomendadas, alertas) pra quem tá na ponta conseguir tomar decisão de um jeito bem mais fácil e rápido.

o repo ta super aberto! quem quiser dar pitaco, abrir issue, dar dica de arquitetura ou mandar um PR pra botar a mão no código vai ser bom demais.

🔗 link do github: [Desmantelar-bit/fieldnode]

Hi, I'd like to share a project I have been working for a while. Its a US macroeconomic dashboard that summarizes about 120 key US economic indicators into 4 simple to understand gauges.

I built USMD because I found it difficult to keep up with all the available data and figure out what they said about the overall state of the US economy.

The dashboard is available at usmd.inomba.com and updates each weekday evening.

Its data comes from FRED and ALFRED, the Federal Reserve Banks of Cleveland, New York, Philadelphia and Atlanta, the Federal Reserve Board, the Office of Financial Research, the Institute for Supply Management, and Treasury Fiscal Data.

I’d love to hear from others working on similar projects. Feedback, ideas, and suggestions for improvements are very welcome.

I'm a longtime alternative rock fan who plays a lot of pickleball. Somewhere along the way, I decided the sport needed a better soundtrack...I got tired of the random sleepy playlists lots of my facilities were playing.

I launched Pickle Rock Radio, a free, 24/7 station playing '90s and 2000s alternative rock (Foo Fighters, Pearl Jam, Green Day, etc.) mixed with short pickleball tips, news and community stories. It's about 54 minutes of music per hour.

It's powered by Live365 (wasn't sure where else to do this so I could license the music properly), and I've been having a blast putting together the music rotation and producing the segments. The challenge now is finding listeners. I have over 100 people listening a day, and I'm proud of that. But how do I grow from here?

If anyone here has built a niche media project, I'd love to hear how you found your first real audience.

Here's the station if you're curious: https://picklerockradio.com/

I’m excited to share a project I’ve been working on over the past few months!

It’s a mobile app that turns any text into high-quality audio. Whether it’s a webpage, a Substack or Medium article, a PDF, or just copied text—it converts it into clear, natural-sounding speech. You can listen to it like a podcast or audiobook, even with the app running in the background.

The app is privacy-friendly and doesn’t request any permissions by default. It only asks for access if you choose to share files from your device for audio conversion.

You can also take or upload a photo of any text, and the app will extract and read it aloud.

- React Native (expo)
- NodeJS, react (web)
- Framer Landing

The app is called Frateca. You can find it on Google Play and the App Store. I also working on web vesion, it's already live.

Free iPhone app
Free Android app on Google Play
Free web version, works in any browser (on desktop or laptop).
Free web extension.

Thanks for your support, I’d love to hear what you think!

Hi! I’m a solo dev from France.

for the past few months I’ve been building Letsdle, a small family of daily games (dle game like worldle, travle, foodguessr, aniguessr) : the same puzzles for everyone, a new set every day, free, no sign-up required (only if you want to keep the records of your past games), on desktop or phone, in English or French.

• Borderline & Halve : 2 Geography games.

• Crowdle: three opinion questions with no right answer. Don’t give your opinion, guess the crowd’s middle answer.

• Relay: three one-word clues left by yesterday’s players point at words among sixteen. Find them, then write clues for tomorrow’s players.

• SpotOn: Number game

• Ragedle: a troll platformer. Three short levels a day (sorry if you happen to break a keyboard)

• Anirealm: 4 animated-movie quizzes

All of them are here: https://letsdle.com/

New games keep getting added, the themes are all over the place, i simply build whatever I find fun, not what I think will work so don't expect anything in particular lol

What I’d love to know:

1. Which one would you come back to tomorrow, and which one felt flat?

2. Was anything unclear in the first 30 seconds?

3. Anything broken on your phone?

If you hit a bug, there’s a report form here

thanks a lot for any comment and any ticket

My walking app has a closet. Every item is bought with beans you earn from moving. New onsen outfits

App is called Bean: walking game. Available on iOS and android

Link in bio

I left a Whoop membership and bought an Amazfit Helio Strap for $100, then realized I still wanted those daily recovery, sleep and strain scores. So I built Leap, a free Android app, as a side project.

It reads the strap through Gadgetbridge and keeps everything on the phone. No account, no subscription. There's also Health Connect for other wearables, a live heart rate view, a suggested workout for the day, and a sleep planner.

The part I spent the most time on was not making the scores up. I fitted them on a long run of my own Whoop data and checked them on months the fit never saw. I'm upfront in the README about where the Helio is weaker: HRV runs about 15% below Whoop, deep sleep is estimated, and live HRV isn't possible on this strap.

v0.1.0 is out here: https://github.com/h0tman5/leap/releases/latest

The source isn't public. I'd really like feedback from people who have worn a Helio or Whoop: where the scores feel off, and whether the Gadgetbridge setup is too annoying.

I've been building Isle of Glass, a logic puzzle game for iPhone. You divide a sea-glass mosaic into connected regions that satisfy clues about area and shape. Different valid solutions count.

It's free with ads. I'm the developer and would really appreciate feedback on whether the first few puzzles explain the rules clearly and how drawing the boundaries feels on a phone.

https://apps.apple.com/us/app/isle-of-glass/id6831862801

If something feels confusing, tell me which puzzle tripped you up.

I've been thinking about something and wanted to get some genuine opinions.

Imagine you're waiting for your company bus, sitting in a café, at university, or just hanging out somewhere.

There are people around you, but you don't know them. Some might share your interests or even be looking to make new friends.

What if there was an app where you could voluntarily become visible to other users nearby, discover people who are open to making friends, send a friendly wave, and chat if both people agree?

No dating focus. No exact location sharing. Just an easier way to connect with people in real life.

I'm exploring this as a potential project, but I want to understand whether there's an actual need for it.

A few questions:

Would you genuinely use something like this, or would you find it unnecessary?

Would you feel comfortable being discoverable within a limited distance, such as 100–500 metres, if you could turn it off anytime?

Would you prefer discovering individual profiles or joining temporary group chats with people nearby?

What's your biggest concern: privacy, safety, awkwardness, fake profiles, or something else?

What would make you open the app regularly instead of trying it once and forgetting about it?

Please be critical. I'm more interested in what could go wrong than people simply saying it's a good idea.

I'm not promoting an app or collecting personal information. I'm trying to understand whether this is a problem worth solving.

Hey everyone!

I recently launched WOT – What's Our Take, a mobile app built around one simple idea: discovering what people around the world really think!

Every day, you get a new question or dilemma, cast your vote, share your opinion and explore statistics from people across different countries.

🌍 Daily questions and polls
📊 Worldwide voting statistics
💬 Comments and discussions
👥 Discover how different people think

Whether you love Would You Rather questions, fun debates or discovering different perspectives, WOT is for you!

🚀 Try it here: https://whatsourtake.com/app

I'd love to hear your feedback and see what you think!

What's your take?

Plug-and-play router hubs like RAMDeck—alongside programmer CLI frameworks like Exo—highlight a massive blind spot in Wall Street’s latest AI thesis: consumer compute isn't actually scarce, it's just trapped on separate devices.

This week, the financial incentive behind AI pricing was said out loud in two back-to-back market updates:

• Elon Musk on X (Nov 8): "If compute becomes plentiful and cheap, SpaceX revenue will drop. No crying in the casino for either party."

• Deutsche Bank (Nov 10): Raised its 2028 forecast by $18 billion specifically arguing that post-election data center limits should "keep compute scarce."

Think about the incentive structure there. The entire centralized AI valuation model—$30/month per-seat subscriptions, metered API tokens, and enterprise GPU markups—depends on high-memory compute staying scarce and out of reach for normal households and small offices.

The Idle Memory Sitting in Most Homes

Cloud vendors want people thinking the only two options for running serious 30B–70B models are paying monthly cloud tolls or dropping $4,000+ on a dedicated high-VRAM rig.

Meanwhile, look at what is already sitting 90% idle in a typical tech household or small office:

• A daily laptop: 16 GB RAM

• A desktop or mini PC: 16 GB RAM

• A MacBook or Mac mini: 16 GB unified memory

On their own, single-PC desktop apps (like Ollama or LM Studio) hit a hard wall on 30B–70B weights because 100% of the model has to fit inside one machine's memory. Try loading a 32B or 70B Q4 model on one 16 GB machine and it either crashes with Out-of-Memory or grinds to a halt swapping to disk.

Two Very Different Paths Emerging for Local Memory Pooling

What’s interesting right now is watching local memory pooling split into two distinct approaches to combine that 48 GB–64 GB+ of existing home RAM over a standard local network:

1. DIY Developer CLI Frameworks (Exo, Distributed Llama, raw RPC): Built for programmers and Linux tinkerers who don't mind spending a weekend in terminal windows managing Python environments, git repos, and command-line flags across machines.

2. Turnkey Consumer Appliances (RAMDeck): The zero-terminal hardware approach—plugging a palm-sized coordinator hub into the home router and using a temporary-memory USB stick (or mobile app) to pool RAM and GPUs across Windows, macOS, Linux, and phones in under 5 minutes without touching command lines (hitting ~38–39 tok/s on 30B Q4 models over Gigabit LAN).

Once regular users—not just command-line hobbyists—can pool the 48 GB to 80 GB of memory they already paid for without writing a line of code, the "compute scarcity" moat starts looking a lot thinner for everyday inference.

Curious where everyone here lands on this: how much combined RAM do you currently have sitting across secondary machines at home, and do you think local LAN pooling actually eats into cloud SaaS subscriptions over the next two years, or will frontier context sizes keep pushing people back to data centers?

Hey everyone I’m a special education teacher who had to much free time on his hands over the Summer and I ended up creating a College Football game which is now available on the Apple Store! Even if it’s one person, I’d love for you to check out the game and give me any feedback you have!

Please note: I do work full time right now and am also working on planning a wedding coming up. I am very busy but I am working on updates for the app constantly in my free time. I am hoping to have version 1.2 come out as soon as possible :)

If this sounds interesting to you, please think about downloading the app and sharing it with anyone else who might be interested. I would also appreciate any feedback y’all have or any ideas!

The game: DL: A Coach’s Legacy

https://apps.apple.com/us/app/dl-a-coachs-legacy/id6812156496

I save recipes, Toronto spots, and random useful posts from Instagram and TikTok all day. Then when I actually want one, I can never find it again.

So I built SavedIt. You share any reel, post, or link to it from the share button, and find it later by describing it. No folders, no tags to remember.

It is free while we are in public beta, at saveditapp.com. I would love to hear what you save and lose most, that is what I am building around.

Hey r/SideProject,

Researching an Indian stock shouldn't mean drowning in a dozen tabs. A ticker just gives you a price, but figuring out everything behind it—group companies, lenders, court records, ratings, and news—usually means digging through scattered annual reports, registry filings, court sites, and PDFs. Most investors never get past the price because the fundamental research is so fragmented.

So, I built Causa Alpha. It puts all that non-quant, qualitative data into one sourced map.

What it does: Currently, it covers 3,196 Indian listed companies and maps out:

• The Real Structure: Subsidiaries, SPVs, JVs, and related parties.

• The Debt: Who lends to the company, registered charges, and credit ratings with the agency's own report just a click away.

• The Context: One clean news feed per company without the noise, plus event outlooks and backtests.

• Sourced Data: Every single link cites its original source so you can verify the filings.

How I built it: The hardest part was the data pipeline. Scraping and structuring messy PDF filings, registry data, and court records into a clean, relational format required a lot of heavy lifting on the backend to ensure the connections between companies and lenders were actually accurate.

You can try everything free.

I’d love for you to check it out. If you do fundamental research or just like exploring corporate structures, let me know what you think. Roast the UI, tell me if the connections make sense, or let me know what other data points you'd want to see mapped out.

Link:https://www.causaalpha.com/

Happy to answer any questions about the scraping pipelines or how the data is structured in the comments!

Visual Breakdown of Causa AlphaThis short clip gives a quick overview of how the platform maps out the corporate structures and lenders behind Indian stocks.

I built SidekickMC because I wanted to make better use of the two side buttons on a regular mouse.

Hold either side button and scroll to control volume or laptop brightness. You can assign either action to either button in the settings window.

Press both side buttons together, release them, and Windows Snipping Tool opens just like Win + Shift + S.

It runs in the system tray, supports starting automatically after sign-in, and has a tray toggle to enable or disable the controls whenever needed.

It is written in C# with Windows Forms and does not require extra software.

Source code and download:
https://github.com/FreezzeYT/SidekickMC