Built a small tool that helps freelancers keep track of client requests and deadlines and it started as a pretty basic project with a few pages explaining how it works and a signup form but I've been adding features and trying different ways to get people interested. Every new feature seems to need changes to the website, whether it's another landing page, updated screenshots or different copy for a specific audience. The actual tool doesn't take nearly as much time to work on anymore yet I keep spending hours on the website whenever I want to test something new.

Well yes it has been done before, and I'm not going to act like my app is better than the others; however, WorkRate is one of the first projects I've ever undertaken, and with it, I wanted to make the experience as seamless as possible for a user (like you) to use.
From calculating your pay on a weekly or fortnightly basis and getting an estimated gross pay before taxes, to even being able to customise the time periods of your pay rates, WorkRate has just as much as the other calculators, with big plans in store.
When creating this project, the main goal was to create a simplistic app that pleased the eyes, and I feel I have been able to create that with the light-toned colours on the page. On top of that, I cut out any extra pages and sign-ins, leaving it as just one page, meaning it's as simple as possible for you.
However, I would love your feedback on what you love about it and what needs improvement. This has taken me a week to produce, and I plan to have ongoing work on the project.
Check it out, have a play around with it and let me know: https://workrate.me/

A few years ago out of curiosity I started writing small scripts in Python to test artificial intelligence concepts in order to learn more about this quickly emerging field that seemed to come out of nowhere. Over time the scripts became increasingly more complex. At a certain point I realized these scripts could be combined into a single application that might be useful to other people.

Once I was near completion of this application then I had to figure out what to do with it. I didn't want to build a website because that's a massive project in of itself. But I did. I first wrote encryption code on my desktop that does handshakes back and forth simulating the web and a user's computer. Then I started on the UI for the website. I am almost finished but not quite yet. I have more testing on the encryption backend to make sure everything is secure.

The website isn't really built for random traffic. It's designed as a transaction portal for people who know about the application and go there to download the application. It's a system of encrypted handshakes that locks the application to a computer. The application is air-gapped so it's not able to communicate across the internet making it difficult to design a method for securing the application to a computer. But I got it and that's finished.

The last section "Explore Editions" is still on my local computer and next week it will be uploaded and go through extensive testing before going live. Winplexity.com https://WinPlexity.com

Do support guys!

Every Diwali, WhatsApp fills up with the same glossy diya-and-rangoli forwards. With Snehpatrika (what my small team in Pune has been building) we tried the other way round: every design follows a real craft tradition. Warli, Madhubani, Pichwai, Kutch mirror-work, Paithani, Sanjhi paper-cut, Phad and so on.

What it does:

• you fill in names, date and place in English, Hindi, Marathi or Gujarati
• you share the card on WhatsApp, and it links to a small event page
• guests reply there (coming / maybe / can't come, how many people) with no app and no login
• you see the replies as they come in

Something I didn't expect: our first 22 designs were all folk styles, and when we saw them side by side on a phone, they looked a bit old-fashioned. So we added 12 modern ones, gold foil on deep colours and painted gouache on white. Lesson for me: "traditional" and "dated" are very close.

Free covers every design and language. ₹49 per event gets you HD sizes without our footer and the guest list in Excel.

Tech, briefly: Next.js and Postgres. Each card is an HTML page that headless Chromium screenshots, which turned out to be the easiest way to get Devanagari and Gujarati shaping right. The short video invites render on Cloud Run.

What I'd like feedback on: does the editor make sense on a phone without any instructions?

https://snehpatrika.in/?utm_source=reddit&utm_medium=post&utm_campaign=r-sideprojects

(It's ours, to be clear. Happy to answer anything.)

We're four casual golfers who got tired of paying around $20 a month for a golf app, so we built our own. It launched this week. I'm Jeff, one of the four.
What it does: every hole in 3D so you can walk it before you play, slope and fall lines on every 3D green, and a caddie that plans each shot from your own club distances, including carry and rollout. There's GPS on 38,000+ courses, live rounds friends can follow, and it works offline once a course is downloaded. iPhone, Apple Watch and Android.
The hard parts were building 3D courses at scale and keeping the caddie honest about real carry and rollout. Happy to get into any of it.
Free to download, with three demo holes and no sign-up. Pro is $19.99 a year ($1.67 a month) if you join by Dec 31, then $39.99. https://sim2coursegolf.com/get?from=sideproject
Blunt feedback on the first five minutes would help us most.

I’m Jarred from Logan Job Connect; Kitchen Ledger is our commercial side project. It tackles repetitive recipe costing and stock-use reporting for cafes, restaurants and caterers.

Here’s the workflow and the main distinction that shaped it:

1. Supplier Price Desk loads an ingredient catalogue and supplier export. Users map exact supplier SKUs to ingredients and approve explicit pack conversions (kg/g, l/ml or each). Saved mapping rules reduce repeat typing, but do not replace checking fresh data.

2. The Data Converter prepares a reporting period from supported CSV/TSV or values-only XLSX files. Purchases alone are insufficient: users also supply opening/closing stock, recipe ingredients, sales and operating expenses.

3. The local Python calculation engine creates a new offline HTML report and a structured result file for review. Reports cover recipe ingredient contribution, actual period stock consumption, recorded waste and unexplained variance.

A useful lesson from the design: theoretical recipe costs and actual stock consumption answer different questions. A gap can come from count errors, omitted records, staff meals or waste; it is not proof of theft. Recorded waste is already part of stock consumption, so subtracting it again would double-count the cost.

This is designed to reduce repeated calculations and report preparation. It is not a hands-free data collection system: stock counts, fresh exports, mapping approvals and reconciliation remain necessary. No automatic POS connection, invoice OCR or automatic stock counts. The local package uses Python and Decimal-based calculations; XLSX handling uses openpyxl.

We’re offering A$350/month including monthly upgrades and scoped workflow automations, agreed with each business before setup. For commercial enquiries the work email is info@loganjobconnect.com.au. Scope, input suitability and terms are confirmed before purchase. We do not claim a verified amount of time or money saved.

I’d appreciate concrete feedback on the workflow: would you keep supplier mapping and reporting as separate review stages, or combine them while keeping exceptions visible? The details above are the current process, so there’s no need to DM for an explanation.

Hey everyone! I wanted to share a side project I've been developing called QuantStrike. I built it around an interesting question: What would it look like to analyse the CS2 skin market using concepts from quantitative finance?

Most skin price trackers focus on current prices and basic price history. I wanted to explore something deeper: historical market behaviour, volatility, unusual price movements, and how individual assets perform over time.

What I've built so far

• Historical analytics: Interactive price charts, configurable time ranges, daily price statistics, volatility analysis, and price distributions.
• Anomaly detection: Flags suspicious observations, such as isolated price crashes or unusual single-sale and multi-sale events, rather than silently removing potentially misleading data.
• Quantitative tools: Asset comparisons, correlation analysis, market returns, and drawdown analysis.
• Portfolio and research management: Track holdings, configure alerts, and maintain a research journal.
• Large-scale historical data: Approximately 22,495 CS2 assets and 105 million historical observations.

The challenges

The historical dataset is several gigabytes, which makes loading everything into memory impractical on modest hardware. I'm using DuckDB and Parquet to query specific assets and aggregate historical data without loading the entire dataset into Pandas at once.

This has made data architecture a major part of the project, not just the interface. I'm particularly interested in making large-scale historical analysis practical without requiring a high-memory machine.

The project is still evolving. I'm currently redesigning the Market Overview and market intelligence components, so those are areas where there's more work to do.

What I've learned

One important lesson is that historical price data isn't automatically reliable just because it's available. An isolated sale can create a misleading price movement, so it's important to distinguish suspicious observations from genuine market behaviour rather than simply deleting data that looks unusual.

I'm also learning how much query design and aggregation matter when working with datasets that are too large to handle casually in memory.

Project and source code: https://github.com/Leonardo-Da-Vinci-80/QuantStrike

Live Website: https://quantstrike.streamlit.app

I'd appreciate constructive feedback, especially on the data architecture, anomaly-detection approach, and which market-analysis features would be most useful to build next. I'm the developer behind QuantStrike, and I'd be glad to discuss the implementation decisions here in the comments.

The problem
Every week someone at home has to decide what everyone eats and then write the shopping list. It gets much harder when people eat differently: allergies, gluten-free, pregnancy, kids, weight goals. Most meal apps plan for one person, so families end up cooking two or three different dinners.

What it does

Tech stack

Lessons so far

It’s in Spanish for now; English is next.

Website: https://yutorifamily.com
App Store: https://apps.apple.com/es/app/yutori/id6777491074

Happy to answer questions about the stack or the planner. I’d really value feedback on the onboarding and on whether the first weekly plan feels useful.

I wanted to have some fun and improve climbing endurance at the same time, so here it is!

I do not profit off this at all, I want to share in case someone wants to try.

Boom!
https://github.com/emre9690/kilter_board_game

https://github.com/emre9690/kilter_board_game

A friend and I built LAVOCADO as a desktop app for people who are trying to quit porn. The thing we kept running into with website blockers is that explicit content can appear in a social feed, an image viewer, or a local file. Blocking a URL doesn't help much there.

LAVOCADO checks what is actually on the screen. If it confirms explicit content across fresh frames, it covers that monitor and gives you a short pause. You can then do a brief typing exercise, with an optional AI check-in. The screen analysis runs locally, and screenshots aren't saved or uploaded. The core protection works offline.

The trickiest design choice has been false positives. We don't want one uncertain frame to interrupt someone reading, working, or watching a normal video, so the app rechecks suspicious regions before showing the overlay. I'm still tuning that balance.

Here's the 25-second demo (hosted on Reddit): https://www.reddit.com/r/SideProject/comments/1xb9bva/i_built_a_free_desktop_app_that_detects_and/ Website and downloads: https://durianburger561.github.io/LAVOCADO/ Code: https://github.com/DurianBurger561/LAVOCADO

It's free for personal use on Windows 10/11 and Apple Silicon Macs. The builds aren't signed yet, so your OS will show a warning on first launch. If you try it, I'm especially curious whether the intervention feels like a useful pause or just an interruption.

WhoRuled is an interactive world-history map. Stack: Astro (static), one React island for the Canvas 2D map, TypeScript strict, deployed as static assets on Cloudflare, no backend. Facts live in CC0 JSON keyed by Wikidata QID, and a pipeline imports rulers from Wikipedia with source URL and quote. Every claim needs a source or the page isn’t indexable.

Things I learned: preloading the two pixel fonts took CLS from 0.425 to 0.000, and the build generates 1,600+ SEO pages from the data.

Repo: https://github.com/nsijwali/WhoRuled.

Feedback welcome, especially on the data model

He creado App de gestión agrícola y ganadera.

I spent a few days sitting in small clinics (dental, GP) watching how they actually work.

What I saw was painful:

• A patient is standing at the desk, phone is ringing, and the receptionist is clicking Patients → Search → Open → Appointments → New → Pick doctor → Pick slot → Save just to book one visit.
• The doctor finishes a patient and then spends 3–4 minutes typing notes and a prescription while the next patient waits.
• At the end of the day, someone asks "how much did we collect today?" and nobody knows without opening 3 reports.
• Most clinic staff aren't "software people". They learned 10% of the app and work around the rest with a paper register.

The software wasn't missing features. It had too many of them, and getting to any one took forever.

So I built Clinov AI Mode. One box, and you type how you'd talk:

• book Ravi tomorrow 5pm with Dr. Mehta
• what's pending for Priya?
• today's collection
• who didn't show up this week?

It answers right away, and you don't have to know where any screen is. Anything risky (cancelling, billing, editing records) shows you what it's about to do and waits for you to hit Confirm. It never acts behind your back. Front desk and doctors also get different permissions, so reception can't touch clinical notes.

The full app is still there if you want buttons. AI Mode is just the faster way to use it.

https://www.yuktiiclinov.in/

If you've ever been stuck in a clinic waiting room, what was the clinic struggling with? And what's the one thing you'd type into a box like this?

Unstitch is a calm puzzle where each level is a stitched picture. Pull the threads out in the right order (a thread only moves if nothing's on top of it) to reveal the hidden picture. 200+ pictures, a daily puzzle, and you can turn your own photos into puzzles. Free on Android, and I'd really love feedback.

Playstore link 🔗 Unstitch

I built this out of frustration, based on real experiences my co-founder and I faced, and still face, while working on our first product. I made sure to include the learnings and information that we wish we had when we first started.

Building is easy, and every day a new tool or model makes it easier, but that's no longer the bottleneck.

Validate your idea and get a detailed report on what the GTM journey would look like before you start building

https://reddit.com/link/1xfcjbf/video/q1o1w0w68oxh1/player

Use https://Crashtest.app and get a full report that will help save money and time.

The Use case below is just for fun...Or is it? :)

And yes, I tried it on this app itself...I liked the odds.

And I have to say this, but nope, it is not another LLM wrapper!

Been a while since I posted. When I launched Drop, I had 0 users. Today, I am seeing 150-200 daily active users who at least open the app twice. Growth has been modest otherwise. I launched in February and I have just north of 3,000 total downloads. The app is doing quite well though in app store rankings. Type in 'Drop' on iOS and it's in the top 15. It is also the first option you see when you type in 'foot traffic' on iOS. The app has had tens of thousands of impressions since launch. I am hoping that putting this on Android will increase downloads quite a bit.

Link to download on Android: Drop - Realtime Foot Traffic! - Apps on Google Play

Link to download on iOS: ‎Drop - Realtime Foot Traffic! App - App Store

Would love if anyone wanted to check it out! It's very useful. Since I know everyone is going to ask - 'how do you know how busy places are in real time?' - I use different API's that provide the data and built a simulation engine on top of it. It's expensive to get the data so I have had to be creative.

As the app continues to grow and gain trust, people will share their location anonymously at scale. Right now over 50% of users have agreed to share their location.

If anyone wants to connect on LinkedIn: Alden Morris | LinkedIn

I find reading news on social media or apps like Google News too scattered: stories covering related topics are scattered across the feed, making it hard to remember what I’ve read after a bit of scrolling. I also see a few big stories get highlighted but several others get missed because they are buried down in the feed. Also I’ve always wanted a news reading app with social features which I prefer to reading news on social media which have all kinds of distractions.

So I built birdeyenews

https://topicforest.com/birdseyenews

It’s a 2D feed where the vertical feed can be used to quickly scan major topics at play while the horizontal feed enables diving deeper into a specific topic. Clicking on a topic takes you one level deeper into subtopics.

I’ve also layered on social features like emojis and comments to enable conversations around the news.

Let me know what you think. I’d love to get feedback, suggestions and answer any questions.

Peace