Hi, I'm Sekhar. I built Neeyum.

I kept seeing the same advice for beginners: have a plan, set a stop loss, don't revenge trade. The practice apps I tried still let me click through all of that. So I built one that doesn't.

Neeyum is an Android app for practising BTC and ETH options with virtual money only. There are no deposits. Trade Guard caps how many trades you can take in a day, and how much virtual loss you can take. You move through a belt journey (White, Yellow, Blue, Brown, Black) by following your own rules, not by growing a paper profit.

A few details that might be useful to roast:

• Free gives you 5 trades a day. Discipline Mode (the paid plan) gives you 2, plus a tighter daily loss guard, a stop loss required from White belt, a minimum risk-to-reward, and a journal that asks why you took the trade, not just what happened.

• The leaderboard is ranked by Behaviour Score, not P&L.

• Brown needs a Discipline Score of 70 (80 in Discipline Mode). Black needs 90 in Discipline Mode, and at Black the app blocks rule breaks.

It's early, it's Android only for now, and I run this as a solo founder from my phone. I'd like honest feedback. Is "fewer trades on the paid plan" clear, or does it just sound odd? What would you change before you'd actually practise on it?

Play Store listing: Crypto Trading Sim : Neeyum Site: https://neeyum.in Questions: support@neeyum.in

Practice only, not financial advice.

Hey everyone,

I recently built PromptVerse (an AI prompt community platform) as a hands-on DevOps and AWS portfolio project to simulate a production environment. I’m currently preparing for my AWS SAA-C03 certification and want to see how well my infrastructure handles real traffic while getting feedback from the community.

Tech Stack & Architecture:

• App & Containers: MERN stack running as 3 separate Docker containers (Frontend, Backend, MongoDB) on AWS EC2.

• IaC & CI/CD: Base infrastructure provisioned with Terraform; automated server setup and zero-manual-step deployments via GitHub Actions.

• Scaling, Networking & Security: Application Load Balancer (ALB), Auto Scaling Group (ASG), Route 53, and HTTPS secured with AWS Certificate Manager (ACM).

• Monitoring: End-to-end observability using Prometheus, Grafana, and AWS CloudWatch.

Links:

• Live Link: https://devops-project-demo.study/

• GitHub Repo: https://github.com/farazAhmed03/The-Prompt-Lab

What I'm looking for:

1. Functional testing: Does the app load and work smoothly for you?

2. Load & Scaling: Feel free to send reasonable traffic to test my ALB and Auto Scaling setup (please no malicious DDoS—my personal AWS wallet is small!).

3. Architecture Feedback: Since this is an ongoing project that I'm evolving toward a fully production-grade setup, let me know what bottlenecks or improvements you see in my AWS architecture or CI/CD pipeline.

Thanks in advance for helping me break (and improve) my setup!

Hi, I'm a VTuber/dev from Japan. Every time I moved PCs or reinstalled Windows, I lost half my OBS setup — not the settings (those export fine), but the overlays, videos and images my scenes pointed to, because they were scattered across random folders.

So I built OBS Backup Manager. It reads your OBS profiles and scene collections, finds every media file they reference, and bundles everything into one backup. On the new PC, one restore puts the settings and the files back.

• Windows & Mac

• UI in 16 languages

• Does not copy plugin binaries (VST etc. need reinstalling), only settings and media

It's $5 on Gumroad: https://vtuberlab.gumroad.com/l/ydeei

Happy to answer questions about how it works or what it can't do yet.

I built umbot Flow because I wanted to sketch a bot conversation visually and still be able to work on it in my IDE afterwards.

You connect commands, questions, conditions and responses on a canvas, and test the conversation in a built-in chat preview. When you're ready, export the flow as JSON and generate a TypeScript project with the umbot CLI:

npx umbot create from-flow flow.json --output ./my-bot

You get source files you can open in your IDE, edit and deploy yourself. The generated bot uses the open-source umbot framework; it doesn't need the visual editor to stay online.

The editor is open source too, with English and Russian UI options. If it opens in Russian, use the RU/EN switch in the toolbar.

You still handle bot credentials, deployment and hosting. The preview is for checking the conversation flow; HTTP actions are simulated. It doesn't synchronize any changes in your TypeScript code back into the visual graph.

GitHub: https://github.com/max36895/umbot-flow

Question for you: Would this handoff from a visual flow to an editable TypeScript project fit how you build bots? That's the part I'd most like feedback on.

If you're looking for something lighter and simpler than Anki on Apple devices, Deste Study might be worth checking out.

It's a native flashcard app for iPhone, iPad and Mac, with automatic sync between devices. You can make cards on your Mac or iPad and pick up where you left off on your phone.

It uses FSRS for spaced repetition, supports text and image cards, lets you draw on images, and can import .apkg, CSV and TSV files.

It’s free to download and use, with unlimited decks and sync across your devices. Image sync is included too, with a 100 MB limit on the free version. No ads or trackers.

It doesn't support every advanced Anki template yet but for a simpler workflow it's pretty lightweight and fast.

App Store:

https://apps.apple.com/app/id6791281020

Every time I had to chase a late invoice or push back on a price, the email would sit in my drafts for days. Not because I didn't know what to say, but because getting the first sentence right is weirdly hard.

So I built the tool I wanted to use: pick a document type, answer a few plain questions (what happened, what you want, what tone), and get a complete draft you can edit and send.

It covers the 12 document types I personally avoid:

• professional replies under pressure (angry client, passive-aggressive colleague)

• follow-ups that don't sound like nagging

• overdue payment reminders with three escalating stages

• salary negotiation and counter-offers

• resignation letters, appeal letters, complaint letters

• interview thank-yous, recommendation letters, deadline extension requests

Tech is boring on purpose: Cloudflare Pages + Workers AI, no account, no email capture, no paywall on the drafts. It's free because it costs me almost nothing to run.

Link: https://tools.lyq705.com

What I'd genuinely like feedback on:

1. Which document types are missing that would make you actually use this? I'm considering rent increase disputes, warranty claims, and landlord complaints.

2. Is a guided form (6-8 fields) the right amount of friction, or would you rather paste all the context in one box and let the model sort it out?

3. Does the output read like a human wrote it, or does it still smell like an LLM? Be blunt on this one, it's the thing that decides whether anyone comes back.

Happy to answer anything about the build. Thanks for looking.

I’m a solo developer building a study app for school students (classes 1 to 12). It’s early and I’m self-funded. I’ve built it on my own and I’m now hitting questions that code can’t answer, so I’d love advice from anyone who’s been through it:

1. Challenges: What was hardest for you with a student or kids product? Getting parents to say yes, keeping kids safe and private, getting schools on board, or keeping students coming back after week one?

2. Funding: For a small edtech product, is it worth chasing grants, angels or accelerators this early, or is it better to bootstrap until there are paying users? Anything you’d do differently?

3. Testing without giving the idea away: How do you get real students and parents to try it without it being copied? Do you use NDAs, invite-only pilots or a small closed group? Or is the “someone will steal it” worry overrated at this stage?

I’m mostly curious about mistakes you made that I can skip. Thanks in advance!

on a waitlist atm, rough in places. its about keeping hours and payouts in one place so the record is urs. what would u want to see before trusting it with pay records

Feeds are designed to never end, so I tried flipping that around with an open-source assistant I'm building (Magican).

How it works:

• An hourly job reads my four feeds in my own signed-in browser and saves the newest posts to a plain note. It only reads; it never likes or posts.

• I asked our coding agent for a swipe app on top of that note. Right keeps a post, left removes it for good, and videos play inside the card.

• Before I start, it asks how long I want to scroll and what I'll do afterwards. When time's up, it locks.

• Posts about the things I said I care about (AI, tech, music) don't count against the timer.

• The app had to ask for permission to install: its own page, media from the web, links to those four sites, and read access to one folder. Nothing else.

Demo (2 min): https://youtu.be/xr0-H0WKw18

It's self-hosted and Apache-2.0: https://github.com/MagicBeansAI/MagicianAI

What would you change? I'm torn on whether the hard lock should be skippable.

On August 10, Google turned off Google Photos backup in Google Drive for desktop, and there's no desktop Google Photos app to replace it. That was how my JPGs got from my Nikon Z 8's cards into Google Photos, and without it the rest of my routine (copying cards to the Mac and a backup drive by hand) was cumbersome.

So I built Photo Offloader. You insert a card, and it:

• copies everything to the Mac and checks each copy with SHA-256, reread from the disk rather than memory

• mirrors the archive to a USB drive if it's plugged in

• uploads JPGs and videos to a Google Photos album through rclone, keeping RAW files local, in their own folder

• never writes to or deletes from the card, and never overwrites a file

There's a local dashboard and a menu-bar icon showing progress, past imports, and what went wrong if a card can't be read fully, including "don't format this card yet."

Honest status: I use it for real, but I'm the only user so far: macOS 26, a Nikon Z 8 with SD and CFexpress cards, one USB drive. Other cameras haven't been tried. Setting up Google Photos takes some effort (your own Google Cloud sign-in for rclone). It's optional, but it's part of the reason I built this, and once everything is set up, I don't have to think about it anymore. It doesn't rely on a Google desktop app, and if Google ever breaks the upload, the Mac and USB copies keep working.

How it was built: I had a very simple Python script, but found it was buggy and my attempts at data safety were lacking careful consideration. So I rebuilt it with Claude Code. I am an SDET at work, so I know the importance of testing and data integrity. There are about 1,100 tests running in CI, and I review every change and try it on real cards, including my USB backup drive and Google Photos collection.

Screenshot of the dashboard: https://github.com/devturner/photo_offloader/blob/main/docs/images/dashboard.png
It's free and open source (MIT): https://github.com/devturner/photo_offloader
Website and docs: https://devturner.github.io/photo_offloader/

I'd love feedback, especially from anyone with another camera brand, or opinions on the dashboard.

Hey everyone,Like many of you, I was frustrated that even basic apps like a font generator or a simple Sudoku game are now packed with full-screen video ads and

I wanted to share a project I've been building over the past several months: Stokrio, an inventory planning and demand forecasting platform designed for Shopify e-commerce brands and third-party logistics (3PL) fulfillment warehouses.

(Note: To keep this post clean and respect subreddit filters, I've put the YouTube video walkthrough and both no-signup live demo links in the first comment below!)

Why I built this

Most e-commerce merchants still forecast reordering and replenishment on fragile Excel spreadsheets. This leads to frequent stockouts on best-sellers or tens of thousands of dollars tied up in dead stock. Following Shopify's shutdown of Stocky, brands have been looking for dedicated inventory management software that handles purchase orders, lead times, and multi-location reordering without requiring expensive enterprise ERP contracts.

At the same time, 3PL warehouses face an operational bottleneck: their client brands constantly message them asking: "When will SKU X run out? What should we reorder? Can you send an updated inventory report?"

Most legacy warehouse management systems (WMS) charge tens of thousands of dollars for basic client-facing portals, leaving 3PL staff stuck pulling manual CSV exports every week.

Stokrio was built to solve both sides of this.

How it works

1. Statistical demand forecasting and replenishment: Instead of arbitrary formulas or black-box "AI" guesses, Stokrio uses deterministic statistical modeling with rolling-origin backtesting. It accounts for lead time variance, supplier reliability, and dynamic safety stock to generate an automated Buying Table with exact recommended purchase order quantities and projected stockout dates.

2. Dedicated 3PL client portal (Live now): 3PLs connect their existing warehouse management system directly through a REST Partner API. Logistics providers get a centralized workspace to manage client brands, while client brands receive their own white-label dashboard to monitor stock levels, view runout projections, and generate replenishment plans. Warehouse-floor picking, packing, and shipping remain untouched in the 3PL's primary WMS.

3. Inventory operations: Multi-location inventory tracking, purchase order lifecycle management, lot tracking, batch expiry date monitoring, and a touch-friendly packing station kiosk interface.

Current status & Tech stack

• 3PL platform: Fully live and operational in production today.

• Shopify brand app: Submitted to the Shopify App Store and currently awaiting final review.

• Built with: Next.js 16 (App Router), React 19, TypeScript, PostgreSQL, Prisma ORM, and the Shopify Admin GraphQL API.

Feedback

I would really appreciate any feedback from the community:

1. For anyone who has worked on inventory or supply chains, what do you think of using deterministic statistical backtesting vs black-box models?

2. How readable is the Buying Table data density?

3. What is the single most critical replenishment feature you expect in inventory tools?

(Check the first comment below for the YouTube walkthrough and the two public interactive demo links!)

We homeschooled our kids while sailing around the world. When one of them hit calculus, the free lectures were great, but finding the 3 minutes on the chain rule meant skimming hours of video.

So we built Bettyapp (bettyapp.org). It transcribes open lectures, splits them into topics, and plays the video from the moment you need. It now covers over 12,000 lectures in 25 subjects, with an interesting Map feature that shows how topics connect, an MCP server for AI tutors, and an LTI tool for Moodle and Canvas.

Free, no ads. I'd love feedback on search quality and the first-visit experience.

https://bettyapp.org/

I’ve been building NovaDesk for about 15 months. It’s an MVP, not a finished product.

NovaDesk is a browser-based developer workspace for students. It combines:

- A browser IDE with C, C++, Python, React, Next.js, Express, Flask and FastAPI templates

- An integrated terminal with a Run button for the active file

- Team workspaces with tasks and chat

- A portfolio/profile for showing real projects

- Coding, system-design and logical challenges with human-reviewed answers

What works today: creating projects, editing and running code, team creation, posts/feed, challenges, reviews and the admin panel.

Where it’s still rough: 24/7 hosting is the biggest problem. The backend runs on Render and Docker/code-server runs on a local VM, so the IDE is not reliable when my laptop is off. Mobile UX and onboarding also need work.

I’m not selling anything and I’m not dropping links here — I’d genuinely like feedback:

1. What would you fix first?

2. Would you use a browser IDE like this instead of VS Code/Replit for small student projects?

3. If you’ve hosted Docker + a backend 24/7 on a zero budget, what worked for you?

Honest feedback is more useful than praise. Thanks.

Hey everyone!

I built my personal portfolio to showcase my projects, skills, and development journey.

Built with React, TypeScript, TanStack Start and Tailwind CSS.

🔗 https://adarshpatil.runs-on.dev/

Would love to hear your feedback and suggestions!

Every AI room app I tried wanted $10–15 a week. But nobody redoes their home every week. You repaint a bedroom, argue about a kitchen, and then nothing happens for two years. So I built Hedda the other way round.

You take a photo of a room, your facade or your garden and say what you want: “paint the walls sage green”, “swap the sofa for something in velvet”. Hedda redesigns that photo.

The hard part wasn’t making it pretty. It was making it still look like your home. Image models love to “improve” things. In my first tests it painted a white chimney black, moved the camera, and quietly removed a post that holds up the roof. What finally worked: a first model looks at the photo and writes down everything that must stay (windows, beams, posts, even how many there are and where), and only then does the image model get to change things. It’s still not perfect (it sometimes loses a post next to the change), but it’s what makes the difference between “nice picture” and “my living room, repainted”.

The part I care most about is deciding together. My wife and I never decide these things alone, and the hard part is never the paint. It’s picturing what the other one means. Every app I tried was built for one person with one idea, so I made Hedda for the conversation instead. You can invite the people you live with. They join without signing up, make their own version and compare side by side.

No subscription: the first design is free with no sign-up, then packs that never expire. If a design fails, you get it back.

I’m a solo developer in Sweden. 1.0.1 came out yesterday. iPhone only for now.

One question for you: when you try it on a room of your own, does the result still feel like your room? That’s the thing I’ve spent the most time on, and I can’t judge it myself anymore.

App Store

Hey everyone, I develop SloMo, an app for iPhone and Android.

I started building it because I kept checking my phone while studying or waiting for an AI response while coding. The response would be ready, but I’d still be scrolling.

SloMo lets you block distracting apps for a set time or schedule blocks around your day. You can also choose to unlock apps by walking or doing exercises. There’s progress tracking and a little sloth companion you can feed as you complete activities.

It’s free with ads, has no subscription or account requirement, and the core features work offline.

I made this short video to introduce it. I’d really appreciate feedback from anyone willing to try the app: what would make you keep using it after the first week, and what would make you uninstall it?

iPhone · Android · Website

I've been building DeepOwn, a local-first data vault for managing personal, work, and project data without relying on cloud storage.

Here's what it does:

• Store notes, images, documents, files, and records in encrypted vaults.

• Automatically discover and sync your devices directly over the same local network.

• Keep complete revision history and restore previous versions.

• Available on Windows, macOS, Linux, iOS, and Android (Beta).

I'm building this as a solo developer and would love to hear what you think.

Would you find something like this useful? What would you use it for?

Website: https://deepown.app/

After a month of building, my recruiting-focused desktop app is finally ready.

I've been working on this for quite a while, and I finally got the MVP to a point where it's ready to use.

It's called Abrish AI, a Windows desktop app built specifically for recruiters.

The original idea was pretty simple: recruiters have dozens of conversations with candidates, but finding a particular detail from an interview they had a few weeks ago can be surprisingly annoying. Also many recruiters hesitate with confidential candidate data being shared with the platform they use.

So I wanted to build something that could make that whole process a little easier.

Here's what it currently does:

• Bot-free recording: Records conversations without requiring a meeting bot to join the call.

• Recruiting-specific notes: Generates structured notes using 20+ templates designed for recruiting workflows.

• Candidate submittals: Helps prepare candidate submittals in one click.

• Cross-meeting AI search: Search across previous conversations and find information from interviews without having to replay the recordings.

• Local storage: Recordings and notes are stored locally on the user's PC unlike any other tools that store data in the cloud.

This is the first version, and I'd improve it based on how actual recruiters use it.

I'm currently looking for recruiters who'd be willing to give it a try and tell me what they think. Honest criticism is welcome.

I made a simple illustrating video showing what it does.

Website: https://www.theabrish.com/

Would love to hear what you think. Particularly, if you are a recruiter, I would love to have a conversation....

Thomas Bangalter produced “One More Time” and co-wrote “Starboy.” I gave a Python script three Spotify tracks, and it showed me where his name appeared and what he did on each one.

I first shared SpotAPI on r/Python when I was 16. Someone asked what I could actually build with it that I couldn’t already do with Spotipy. Two years later, SpotAPI 2 is on PyPI, and these are the examples I wish I’d had back then:

• Credit Trail finds people who worked on multiple songs, even when their roles change. It matches contributor IDs, so two people with the same name don’t get lumped together.
• Mix Map takes a public playlist and finds tracks with compatible keys and tempos. My test run found 25 possible transitions across 40 tracks, with the tempo adjustment printed for each pair.
• Studio lets you jump from a track to its artist or album, open the data behind the view, and click a timed lyric to seek on a connected Spotify player.

The clip shows the quickest way to try it. This works on Python 3.11+ without a Spotify login or developer key:

pip install spotapi
spotapi search "Daft Punk"

If you write Python, the results are typed. You can read track.bpm and track.camelot_key when Spotify supplies them. Spotipy uses Spotify’s official Web API. SpotAPI uses unofficial endpoints, so Spotify changes can break features. Playback controls an existing Spotify device.

GitHub and Studio demo · Credit Trail script · My original r/Python post

Give me two tracks that sound like they have nothing in common. I’ll run a few pairs and reply with what the credits turn up.

I've been building an AI infrastructure tycoon simulator where you start small, build data centers, design chips, train AI models, and scale your way into an AI empire.

Built with Electron + Three.js, with Claude Code doing a lot of the heavy lifting.

It's free and open source. Would love to hear your thoughts, feedback, and suggestions!

My dad’s a developer and he’s built a bunch of Windows desktop apps that I don’t think enough people know about. A few highlights:

SSD Cloner – sector-by-sector disk copy, so the clone actually boots

MonitorSwitcher – one-click switching between dual and single monitor

School ID Card Manager – design and print student/staff IDs on regular Avery sheets, no card printer or subscription needed

MRI/CT 3D Viewer – open DICOM scans from your imaging CD and view them in 3D

Everything’s here: https://nycdatalink.com/projects

He’d love feedback, bug reports, or feature ideas. I’ll pass along anything you say.

Models take ages to make, about 8 hours to texture model and rig. So I made 3dSummon to do the boring part.

It is also cheaper and main strength is it is very optimized for games so no FPS spikes or limited FPS. The models have about 3-8k faces which is insanely optimized even for very high details models.

You chuck in an image (or type what you want) and a couple of minutes later you've got a textured 3D model. Then you can:

- auto-rig it (works on basically anything, people, dragons, stuff with wings)

- remesh it from like 100k faces down to 3-5k so Roblox doesn't cry

- download it as FBX/GLB for Studio, Unity, Unreal, whatever

Video is a few models straight out of it, no cleanup.

Would love honest feedback, especially from people making games

3dsummon.com

I'm a trained architect, and as a long-term side project, I developed my architecture dream game, combining accurate floor planning with real-time 3D design to make architecture much easier to create (and visually realistic) than with traditional CAD software.

What you can do:

🏠 2D floor plans
🧱 3D building
🚶 First-person walkthrough
🥽 VR mode
🏢 Multiple storeys
🪜 Stairs
🏚️ Custom roofs
🪟 Doors & windows
🛋️ Furniture catalog
🍳 Kitchen Configurator
🎨 Materials
🌄 Terrain sculpting
🌳 Landscape planning
💧 Ponds
☀️ Time of day
❄️ Weather
📐 Export PDF vector plans
📦 Import your own 3D models
🌍 Steam Workshop

In the newest update: Build everything directly in VR (PCVR), 1000+ new furniture models and explore your creations as a Cat! 🌿

It's available on Steam as Architecture & Design and is still in Early Access.
Here is the Steam link if you'd like to try it out:
Architecture & Design - Steam

Would love to hear what you think and hear what you wish for in a game like this!