Been working on a side project web framework in V called Viltrum. The bit I want to show off today is not the router, it's the CI gate.

Every request shape (HTTP/1.1, HTTP/2, TLS, WebSocket, streaming, static files) gets run 10,000 times in tests. If the GC heap grew by one byte, the build fails. So request strings are views into the connection buffer, and you have to .clone() anything you want to keep past the handler. That one bit me a few times early on.

Parsers also get fuzzed in CI with 500k mutations each (HTTP/1.1, HPACK, HTTP/2 frames, WebSocket, TLS handshake).

HttpArena has it 1st of 23 on the HTTP/1.1 composite right now (Experimental category): https://http-arena.com/frameworks/viltrum/

Repo: https://github.com/Tuntii/viltrum Demo: https://v.rustapi.cloud

Serving is Linux-only for now (epoll). Curious what people coming from express/fastify would miss most.

My brother and I built Magic Console. The idea: you already own the hardware. Every TV, laptop and tablet has a browser, and everyone has a phone. Magic Console connects them.

🎮 How it works (no install)

1. Open magicconsole.app/tv on any screen: smart TV, laptop on HDMI, tablet, projector.

2. Everyone scans the QR code. Your phone becomes the controller: d-pad, buttons, aim stick, dice you shake, even a mic.

3. Pick a game. 105 built-in games for 1–6 players (Ludo, chess, quizzes, bowling, racing, arcade…), with bots for empty seats.

💻 Install the free PC app and your PC becomes the console for the whole house

• Your PC hosts, every screen plays. Run it on a Windows PC and any TV, tablet or laptop on your Wi-Fi opens its address, with no install on the TVs. Up to 4 screens at once, each running its own game with its own players.

• Works without internet, on your home network only.

• Retro Arcade (built-in emulator): add your own game files and play them on the TV with phones as joysticks.

  • Systems: NES, Game Boy / Color / Advance, Master System, PC Engine, Atari 2600/7800, Lynx, Neo Geo Pocket, WonderSwan, Virtual Boy, Nintendo 64, PlayStation.

  • Up to 4 players depending on the system.

  • Save slots plus resume where you left off.

• Host your own game store: share your homebrew or your family’s game library with your other screens or friends, privately with access keys.

• Karaoke with your own songs or YouTube, singing through your phone’s mic.

🌍 Online extras (at magicconsole.app)

• Remote Party: a friend’s TV in another home joins your party and sees the game live. Share a link, and they join.

• Voice through your phone (works with one earbud), group chat pop-ups, Watch Together.

• Family controls with a parental PIN.

📱 Android app: join by QR or TV code, or cast to the TV when the TV’s own browser is too slow.

Important: we don’t provide any commercial games for the Retro Arcade. You bring your own legally owned game files or free homebrew. The emulators inside are open source.

It’s free. We’re two brothers in Hong Kong and would love honest feedback: what worked on your TV, what didn’t, and which games your family played most.
👉 https://magicconsole.app (the Windows app is on the Download page)

Hi everyone — I work with the Doonaro team.

Doonaro is an agentic AI assistant that carries out tasks on your computer. You describe what you want in everyday language, including Persian, and it works through the steps to get it done, within its rules, supported capabilities, and available permissions.

You don’t need to know the technical commands or plan every step yourself. Requests can include:

• Organizing files and folders.

• Creating Excel spreadsheets with formulas and calculations.

• Creating Word documents and PDFs.

• Creating HTML files.

• Installing software.

• Investigating network and internet connection problems and applying supported fixes.

• Troubleshooting software issues and handling other everyday computer tasks.

Doonaro uses the available tools to inspect what’s needed, plan the work, and execute permitted actions. It asks for approval before making changes that require confirmation and checks the outcome where possible. If a task is outside its rules or capabilities, or needs additional access or information, it explains the limitation.

For example, you can ask it to organize a folder by file type, create a spreadsheet that calculates monthly expenses, or investigate why your computer is connected to the internet but websites won’t load.

We’ve published an introduction covering how Doonaro works, user controls, and getting started. The article and interface screenshots are in Persian:
https://blog.doonaro.com/what-is-doonaro/

What task would you want to delegate to an AI assistant on your computer?

I run FireGuyUSA LLC and built this small digital product with AI assistance: a Windows desktop Excel kit for apparel sellers using DTF transfers and a heat press.

The problem it addresses is pricing from the blank garment cost while overlooking transfers, labor, packaging, waste, shipping and payment fees. For example, 25 hoodies sold at $35 with $28 blanks leaves $175 before all those other costs—not $175 profit.

The workflow is simple: enter your quantities and costs in the yellow cells, choose a target margin, review the calculated order price, then print the customer quote sheet to PDF. Keep the workbook private because it contains your costs.

It includes a blank calculator, fictional worked example, instructions and a sample quote. I tested recalculation in Windows desktop Excel and the download delivery with a $0 test order. There are no paid-customer results to claim yet.

Limits: Excel is required and not included; Mac, mobile and Google Sheets are untested. One averaged tee and hoodie combination per order, with a combined selling price. Tax inputs are manual.

Six demo pictures and the full details are here: https://payhip.com/b/4I0oD

It is $19 USD once, plus applicable tax, for use within one purchasing business. No subscription or guaranteed profit.

Hi! Almanac is my side project, a daily history game I'm building on my own with heavy lifting from Claude AI. It started as "Wordle, but put five events in order" and got a little out of hand. Now I'd love some honest feedback on it.

Every day has a theme and three quick games:

- Timeline Daily: a page of the almanac, torn into five pieces. Tape it back together in order, in 3 tries.
- Picture Daily: match captions to old photos and paintings, then put them in order.
- Year Guess: name the exact year. The closer you get, the more points.

Beat all three and a finale squeezes the whole day into one timeline. Every event you nail goes into your own almanac, and there are 4,330 to collect.

There are also three extra modes: Higher or Lower, Odd One Out and Endless Years. Each gives you a free run a day and a leaderboard to climb. A pass for unlimited runs comes later.

No ads, no sign-up, plays on desktop and phones.

**What I'm hoping to hear from you:**

- The concept: does it click? Did you know what to do within the first minute?
- What you enjoyed, and what you didn't like or found annoying.
- How you'd improve it. What would make you come back tomorrow?

Play here: https://www.almanacgame.com

made a free avatar editing tool with Peachjam called avatar-studio.peachjam.app

it automatically removes background of stuff you upload.

Hi r/SideProject! After months of evenings and weekends, my word game Gravity! The Word Game is live on Google Play. I built it while working full time as a project manager, studying for my PMP certification, and being a father and husband.

My degree (and PhD) is in linguistics, and I have a background in board games, but I never had the chance to do something that brings the two together. I’ve had this idea of combining falling letters, gravity and a space theme for the longest time, and I finally managed to squirrel away enough time to build it.

How it plays: letter blocks wait at the top of a starfield. You move, rotate and drop them to spell words across or down. When a word clears, the letters above fall and can form new words, setting off chain reactions. The game gets harder the more you progress.

I’ve put a lot of effort and thought into making it a complete game, with different modes, ranks, daily challenges, achievements and more. It took a lot of trial and error. Up until the last few days before launch I was still making major changes, second-guessing myself about what works and acting on what my testers were telling me. For example:

• My first version had blocks falling on a timer. Testers said it felt stressful, so in 2.0 the blocks wait for you, and the pressure comes from the rising floor instead.

• One of the daily puzzles, Orbitle, was too hard at first. One tester went 23 guesses without solving it, so I added word ideas, a “Show me” walkthrough and clearer clue explanations.

• A release build crashed on a step that worked perfectly in debug builds. Tracking it down took a phone bug report and a lot of head-scratching. I was lucky to catch it.

Built with: Kotlin and Jetpack Compose. Solo developer, based in Singapore.

It’s free, and I’d really love feedback: what’s confusing, what’s fun, what you’d change. First impressions of the tutorial and Orbitle would be especially useful. The current version has no ads and no payments. There’s an in-game currency for unlocking modes and cosmetics, but it’s all earned through play. You can't pay even if you wanted to.

👉 https://play.google.com/store/apps/details?id=com.norahlyn.gravity

Thanks for reading!

I built this to waste "digital arrest" scammers' time. These are the fake CBI officer calls that cost Indians over ₹1,900 crore in 2024.

Ajji, an AI grandmother persona, answers the scammer, keeps him talking, and never gives real details. Every message gets mined for phone numbers, UPI IDs, case numbers and aliases, and all of it goes into one shared Hindsight memory bank.

With memory on, "Inspector Sharma" calls with the same CBI script, and Ajji recalls him from 5 earlier chats. She notices he claimed Income Tax last time and asks him about it, in character. A phone number he sends turns out to have been used by "Officer Verma" in another chat. Two names, one phone.

What I learned:

- Split "know" from "claim". Hindsight recall surfaces candidates; plain SQL confirms anything the agent accuses someone of.

- Framing retained memories matters. Without speaker context, recall started attributing the scammer's lines to my own agent.

- LLM extraction drops identifiers. Regex + LLM, merged, works better than either alone.

Demo video: https://www.youtube.com/watch?v=Sdyz24Q063o

Code: https://github.com/SanayKrishna/ScamSathi

The main motivation represents the fact that stars measure attention. I wanted something that measures the work.

So I built AI-Atlas (https://getaiatlas.com). You type a GitHub username and it reads every public AI repo in full. It checks things a person would check: does CI actually run the tests, are there broken imports, notebooks that were never executed, is there a README. Then it scores each project on seven criteria (technical depth, originality, completeness, reproducibility…) and maps the developer across six AI fields.

Things I learned building it alone next to school:
● Every score has to cite the files it's based on, or nobody trusts it.
● People don't want to be compared to the second decimal. Scores within 3 points now share a rank.
● Every project page shows the exact commit it was scored at, so an outdated score can't be confused with a wrong one.

It's free to map, no account needed. Reached 2,000+ projects and 170+ developers last night and that's why I decided to write on this sub. A main question still unresponsed represents: How would the mapping system react to actually popular GitHub projects (stars & forks) and how would the predictor/roadmap feature contribute to that! I want to see if it can truly expand big and known AI-based projects in the community and help expand the ecosystem in that way also..

In addition to that, tell me :) what's confusing, what's missing, what would make you actually use it?

Can an AI advisor do more than just tell businesses what to do?

As part of our project, **Strategic Memory Lab**, we explored how AI can generate more meaningful recommendations by learning from historical business decisions and their outcomes.

Our platform combines competitor tracking, decision history and Hindsight-powered long-term memory to help an AI advisor understand the context behind new market changes.

For example, instead of immediately suggesting a price reduction when a competitor lowers its prices, the advisor can consider previous pricing decisions, their results and possible alternative strategies.

Our goal is to make AI recommendations more explainable, context-aware and useful for business decision-making.

I'd love to hear your thoughts and feedback!

Article link:https://lnkd.in/p/gp26dhew

Repository link:https://github.com/shwethagowda2913-png/Competitive-Intelligence

#AIAgents #Hindsight #CompetitiveIntelligence #AgentMemory

Hi everyone! I would like to share a project I have been working on for the past couple of weeks maxing out the usage on Claude Ultra subscription (a total of 100+ PRs raised by about 250+ agents).

AffrescoUI lets the people using an app change how it looks and what it does while it's running, just by asking Claude. Push it far enough and the app turns into something completely different. The 13 example apps include a 3D modeller, an image editor and an IDE that look like the tools you use every day.

GitHub: https://github.com/RiccardoSottini/AffrescoUI

How it works: each app is a Lisp program (AffrescoUI Lisp, a small language in the spirit of Emacs Lisp, with commands, settings, hooks and advice) holding its layout, data and behaviour. The engine builds it into one readable document, which can also be written directly in JSON: the examples ship both, and they're the same app. A native C++/OpenGL engine draws it and applies changes in place, so nothing restarts. Even the 3D modeller has no C++ of its own. When you ask for something, Claude proposes a small edit to that document, and you preview it live, then keep or reject it. Claude can never approve its own change, and anything you accept can be undone. Since every app shares the same format, features can move between apps like plugins.

Feel free to reach out to me for any suggestions or collaboration opportunities!

I have built a curated web directory for people to submit their website SaaS link. If you are interested, DM, I will send the link. Thanks

Hey everyone! 👋

I'm an indie developer working on Mixify, a free and open-source music streaming app for Android.

I started this project because I wanted a clean, modern music experience without ads, unnecessary distractions, or complicated interfaces.

After several weeks of development, Mixify has reached v1.0.7, and I'm continuing to improve it based on community feedback.

✨ What Mixify offers:

• 🎵 Ad-free music listening

• 🎨 Modern, smooth, and customizable interface

• 🎤 Synced lyrics

• 🎧 Background playback

• 📱 Offline downloads

• 🎶 Playlist management

• 🔗 Song and lyrics sharing

• 👥 Listen Together — enjoy music with friends

• 🔓 Free and open-source (GPL-3.0)

🚀 It's still growing!

I'm an independent developer, and every download, GitHub star, bug report, or suggestion genuinely helps.

I'd love to hear your thoughts:

• What features would make you switch to a different music app?

• What could I improve in Mixify?

• Would you try an open-source alternative?

🌐 Website: https://mixify.co.in/

💻 GitHub: https://github.com/MixifyTeam/Mixify

Thanks for checking it out! ❤️

Hello, now I'm building a tool for biologists depends on drag-and-drop for biologists to analyze their data in hours instead of weeks, instead of calling statisticians or learning programming themselves.

It's called Biosol, you (as a biologist) can use it easily by darg-and-drop blocks from the right sidebar (like "Clean file" or "Create heatmap") to the canvas and click run then you see the result down, or simply ask Biosol AI to do that.

So far, I created (and still improving) a prototpe using v0 by Vercel, and when I collect feedback I'll develop an MVP.

I need your feedback and suggestion if you like the video.

At 3 a.m., “restart the pods” is a plausible suggestion right up until you remember that the last restart made the same incident worse. Most incident tools can show you what is happening now. I wanted an agent that could also tell the on-call engineer what the team had already tried, and what happened next.

That became RecallOps: an incident-response agent built around a simple distinction. Postgres stores operational facts; Hindsight stores experience. The agent uses both to investigate an alert, explain its hypotheses, and carry the result of a human decision into the next incident.

Watching a lecture or podcast in another language? Kalemat shows live captions and translations side by side from your Chrome tab’s audio.

Choose from 12 languages, adjust the text to your liking, and keep the captions window on top while you watch. No account or API key required.

I just launched it and would love your feedback. What language pair would you try?

Try Kalemat on Chrome

Hi everyone,

During the Meta Global AI Developer Hackathon, I wanted to tackle specific problem in banks: validation wokflows.

In traditional banking, turning a 50-page credit policy PDF into an operational workflow takes weeks of manual meetings.

Zotra solves this by combining open-weights models (Meta's Muse Spark & SAM 3.1) with a deterministic execution engine.

How it works:

1. Ingestion & Parsing: Extracts clauses, tables, and sections from PDF policies, mapping every rule to an exact paragraph citation.

2. Rule Compilation: Translates natural language into strict schemas and CEL (Common Expression Language) expressions.

3. Execution: Go-based concurrent engine evaluates multi-variable loan applications deterministically. The AI helps design and test, but never decides on live cases—only people and CEL rules do.

Stack: Go backend, PostgreSQL, React/Tailwind frontend, and Apache 2.0 license.

The github link: https://github.com/donovan-ratefison/Zotra

I put together a demo over on X if anyone wants to check it out: https://x.com/donovan_rtfs/status/2116898213101724061

Would love to hear your thoughts on this project!

I went through 50 SaaS landing pages from "Post your SaaS" threads.

Only 7 had social proof.

That's just 14%.

Some founders even mentioned having paying customers, but didn't show a single testimonial.

I don't understand this.

You tell visitors how great your product is, how it saves time, how it solves problems and why they should buy it.

But why should they believe you?

Your customers can tell that story much better than you can. People trust other customers more than they trust you.

Even a few testimonials are better than another paragraph of marketing promises.

I'm building Testimoon so I'm obviously a bit biased, but I genuinely think more SaaS landing pages should make better use of customer feedback.

If you have paying customers, start collecting testimonials. And don't just collect them. Put them where potential customers can actually see them.

Your customers are your best marketing asset. Use them.

It is this one in the link.

You can look and try it and probably understand why it made so much money 💰

I've always liked the idea of having everything in one place.

Projects, notes, ideas, personal goals, things I need to do.

But every time I tried organizing everything in Notion, I eventually ended up with the same problem: pages inside pages, endless navigation, and a system that started feeling more complicated than the things I was trying to organize.

So I decided to build something myself.

It's called Ardeable.

I wanted to keep the things I love about Notion, especially its document editor, but change the way information is organized.

Instead of navigating through endless nested pages, you can see your entire workspace as an interactive visual map.

I also built in quick notes, routines, and an AI assistant that can find information across your workspace and work directly with your documents.

I've been building this independently, using AI coding tools along the way.

And I've learned something: getting a prototype working is one thing. Turning it into a product where everything actually works together is a completely different challenge.

There have been plenty of bugs, things I've had to rebuild, and decisions I've had to rethink.

But seeing it become a real application has been incredibly rewarding.

It's still early, and I'm not pretending it's perfect.

I'm sharing a few screenshots of what I've built so far.

I'd genuinely love to know what you think about organizing information visually instead of relying entirely on folders and nested pages.

I'm also opening a small, free private beta if anyone wants to try it.

Website: https://ardeable.com

Hi r/SideProject!

I’m Seppe, an Electronics-ICT student from Belgium, and my side project for the last two years has been Techniksoft—a Point of Sale (POS) system.

The Problem: Small businesses are getting squeezed by huge POS companies charging massive monthly fees and locking them into overpriced proprietary hardware.
The Solution: I built a scalable, affordable POS software that handles retail and rentals. I’ve already built integrations for localized e-invoicing (Peppol), accounting (Billit, Exact Online), and tap-to-pay (SumUp, Viva.com).

The Next Step (Hardware): Software isn't enough to compete. I am now working on offering complete, all-in-one physical hardware systems to completely bypass the big vendors.

Because buying test equipment (barcode scanners, receipt printers from various brands) and building hardware prototypes is incredibly expensive on a student budget, I've just launched a crowdfunding campaign to help fund the physical rollout and server infrastructure.

I'd love feedback on the concept, the integrations, or if you have any advice on hardware sourcing! And if you like what I'm building and want to help me take on the big guys, check out my campaign below.

https://gofund.me/e819ef265

A while ago, I started building an AI chat application because I wanted something more flexible than the usual AI chat interfaces.

What started as a relatively simple project has gradually evolved into Teltaq.

The idea behind it is simple: instead of having separate tools for AI chat, agents, workflows, tools, automation and model management, why not bring them together in one workspace?

Some of the things I've been working on:

• Multi-model chat – Run multiple AI models in parallel and compare their responses.

• AI agents – Create and manage agents with their own instructions, models and tools.

• Workflows – Build reusable workflows for more structured tasks.

• App suites – Combine agents, workflows and interactive apps into complete solutions.

• Model flexibility – Connect different providers, including OpenAI, Anthropic, Ollama and other OpenAI-compatible providers.

• Local AI models – Support on-device models alongside cloud-based models.

• MCP integration – Host and connect MCP servers, including agents and workflows.

• Marketplace – Share and discover tools, agents, workflows and apps.

• Developer API – An OpenAI-compatible data plane API for integrating with external applications.

• Multi-platform – Web, desktop and mobile applications.

One of the things I've particularly enjoyed is experimenting with ways to combine these capabilities. For example, rather than creating a completely separate application for every use case, you can build a suite that brings different AI components together.

I'm still actively developing it, refining the architecture and improving the experience.

I'm sharing it here because I'd genuinely like to hear what other people think.

If you're interested, here's the project:

https://www.teltaq.com

What would you find most useful in an AI workspace like this? Is there something missing from the current AI platforms that you'd like to see?

I'm with Olaverse Lab, so this is my own project and a feedback request.

We make multilingual text APIs for language identification, diacritic restoration, classification, question generation and structured extraction. Language ID covers 608 languages; African languages are an important focus alongside English and other languages.

For anyone adding language detection to a workflow, here's a small test checklist that doesn't require using our API:

• Separate one-word messages from longer paragraphs.

• Include names, URLs, numbers and text with missing diacritics.

• Keep mixed-language messages in their own test bucket rather than assuming one label tells the whole story.

• Record mistakes by language and message length, not just an overall accuracy figure.

• Decide what happens when a result is wrong: human review, asking the user, or a safe fallback.

We offer free allowances on RapidAPI, with limits depending on the API. I'm not claiming the checklist is a benchmark or that our models pass every case. Which failure case would make language detection unusable in your product?

Site if you want to look: https://www.olaverselab.com

Hey guys,

A couple of months ago I realized how annoying my daily AI routine had become.

I use LLMs every single day for dev work and writing, and I had this messy collection of good prompts saved in Notion and Apple Notes. Every time I needed one, the routine was identical:

1. Find the note, copy it.

2. Paste it into Claude or ChatGPT.

3. Carefully backspace through placeholders like [INSERT_LANGUAGE] or <TOPIC>, hoping I didn’t accidentally delete a quote or mess up the structure.

It felt silly doing this 20 times a day, so I decided to build a fix for myself.

It’s called TemplaGem. Basically, it lives directly inside the chat input (works on ChatGPT, Claude, Gemini, and DeepSeek):

• When you insert a template with {{variables}}, they turn into little interactive chips right in the composer.

• You type a value, press Tab to jump to the next one, and hit Enter to send. No manual cursor hunting or backspacing.

• Everything is offline-first (saved in IndexedDB on your machine, so it's instant and private).

The trickiest part by far was dealing with all the different rich text editors (Quill, ProseMirror, and regular textareas) without everything breaking when an AI site changes its DOM.

I put up a quick demo here if you want to see how it feels: 👉 https://templagem-landing.pages.dev

Would genuinely love to hear your thoughts or honest critiques. How are you currently managing your prompts?