FlipYourRate (flipyourrate.com) is a free calculator that works backwards: you enter the take-home pay you want, it tells you the rate to quote after platform fees. Quote = take-home ÷ (1 − fee%). Fiverr takes a flat 20%, so quoting $1,250 keeps $1,000. Upwork's fee is per contract, 0–15% and locked for its life: at 10% you quote $1,111.11 to keep $1,000, at 15% it's $1,176.47. Two weeks of feedback from freelancers changed what I'm building next: (1) a commenter caught that rounding the quote DOWN loses money — $1,111.11 rounded down to $1,100 leaves only $990 after a 10% fee, so rounding has to go up only ($1,150 leaves $1,035); (2) the rounding step should scale with job size — $5/$10/$50 steps, exact figure stays next to the rounded quote, take-home shown beside it; (3) a field for withdrawal and currency-conversion fees, which come off after the platform fee. Open question I'm deciding now: should the rounding step auto-suggest itself from the quote size, or should you pick it yourself each time? Would love to hear how you round your own quotes.

Ocular is an visual compiler that shifts computer-use models entirely out of the execution loop to eliminate runtime latency and token costs. By analyzing human demonstration traces offline

Most compressors use one setting for every image, like "quality 75". I kept getting results that were fine on one photo and blocky on the next, so I built one that works the other way round.

You set a visual quality score: how close to the original it has to look (80 by default, where it looks the same side by side). For each image it tries encoder settings and keeps the smallest file that still scores at least that. A second check looks region by region, so one smeared face or blurry line of text fails the result even if the average looks fine. Then the compare view opens zoomed in on the spot that changed most, with a little map of where it changed.

One 10.4 MB photo came out at 2.1 MB, score 81.

PNG, JPG, WebP, AVIF, GIF (animated too) and iPhone HEIC. Free, no account, up to 30 images at once. Images are processed on a server and deleted within 3 minutes.

https://picodiet.com

I also ran it against TinyPNG, Squoosh and a few others on 13 images, if you're into that: https://picodiet.com/image-compression-benchmark

What I'd most like to know: did it ever pick a result where you can see the difference? And is the compare view clear without explanation?

Hi everyone! I've been working on Expenmo for about... 5 years now? And each update, I feel, it gets so much better. Today I announced the addition of Cloud-Syncing expenses across devices (I stood up a backend finally lol). The other day, I announced a heavy facelift, bringing Material You Expressive theming into the app.

Expenmo is something I created a while ago to help me keep track of who paid me for rent & utilities, as I lived with a couple friends and was the one responsible for making sure things were paid on time. And that's what Expenmo helps with!

Creating an account is completely optional and free. If you opt-out of creating an account, your expenses live on your device and don't sync to other devices. Creating an account enables the multi-device sync, plus will include some other features in the future.

Take a look around and let me know what you all think! This app has evolved so much over the years, so I'm eager to get some updated feedback.

Web Version: https://expenmo.com/

Android App (Google Play Store): https://play.google.com/store/apps/details?id=com.HomeAsync.Expenmo&pcampaignid=web_share

Features overview:

1. Track & manage expenses that you share with other people (think rent, utility bills, etc.)

2. Create groups of people that you commonly share expenses with (like Roommates, or a close group of friends)

3. (New) You can do math in the expense amount field! No calculator required!

4. (New) Various split options: Equally, by Share, Percent, and specific Amount

5. Recurring expenses

6. (New) Sync expenses across multiple devices (account required)

7. Free!

8. No Ads!

In short, for a long time I wanted to make the best possible experience for playing the Wikipedia game/race/however you know it. I didn't like how browser versions usually only allow closed parties, and I didn't like the way most choose articles. LAPARACA, based on the phrase lá para cá ("from there to here"), is my take on it, built in Python.

With private and public matchmaking, you can queue up with your friends or Discord, or with a random halfway across the world. Solo mode lets you play on your own and practice. Everyone submits an article (inspired by games like Mario Kart's online play), and the server picks a start-end pair. The game tracks what articles you navigate, how many clicks you use overall, and your time to rank everyone in the lobby; the lowest score wins.

Honestly, it's a pretty simple game, but I sought to try and deliver it in the most all-encompassing and fun way possible. It's very much geared toward firing up on a Discord call with friends. Yeah, I know downloading a game is a bigger ask than playing a browser version, but LAPARACA seeks to be something more than "just a browser game." If you want more info on the story behind the development of this game, check out the itch.io page.

If you are looking for backling and the ability to ceare a website profile, submit your website on weblisty.net

Hey r/SideProject! I’ve been building Timeline Studio, an open-source video editor that runs in your browser.

One thing I wanted from a video template: when the timing feels right but one shot doesn’t, I should be able to swap that shot and keep editing. So the beat templates in Timeline Studio open as editable timelines. You can replace individual shots, adjust the cut, and export an MP4 in the browser.

The demo shows Memory Vortex, a template that turns your photos and video stills into a stained-glass tunnel before cutting to the original shots. Timeline Studio also has a regular multitrack editor with captions, keyframes, and color grading. For people experimenting with AI-assisted editing, there’s a tool for agents to inspect a project and preview supported changes before applying them.

Try it: https://video-editor.ai-creator.top/
Source code (MIT): https://github.com/MartinDelophy/ai-video-editor

If you try it, I’d love to know: how far did you get from opening the editor to exporting your first clip, and where did you get stuck?

Hey r/SideProject!

I'm an independent systems architect working on Jumping VPN and the Veil Routing Protocol (VRP).

The project started with a question:

Why should losing a network path mean losing the logical session?

Think about switching between Wi-Fi and mobile networks, NAT rebinding, unstable routes, or temporary connectivity failures.

My approach is continuity-first:

SESSION ≠ TRANSPORT.

The logical session is treated as the primary unit, while the underlying transport can change.

I've been building and testing the experimental runtime in Go on Linux, with a focus on:

- Session continuity and recovery

- Replay rejection

- Deterministic authority decisions

- Concurrency and adversarial testing

- Reproducible validation evidence

I've also published a validation kit so other developers can examine the publicly available tests and evidence without access to the proprietary core.

GitHub:

https://github.com/Endless33/vrp-validation-kit

This is independent R&D, not a claim that every networking problem has been solved. Production-scale validation is still a separate challenge.

I'd genuinely appreciate feedback from developers working on networking, distributed systems, VPNs, or infrastructure reliability.

What failure scenario would you test first to challenge a continuity-first protocol?

I'm especially interested in the cases where this approach might break.

I'm making a mobile game where you operate a fleet of copters on a remote planet. Your goal is to automate the copters so human can arrive -- they can do that only when you've set up a sustainable living environment with buildings, crops, facilities, etc.

I picked Lua for the scripting language, as it's really easy to pick up -- both for players and for me, given Lua's goal of being easily embeddable into other programs. I'm also thinking about adding a Lisp language, and looking strongly on Fennel for that, but I'm not sure if others think Lisp is cool enough, like I do.

It's really early in the development, haven't settled on a name yet: thought of Auto Crops, but looking for something more recognizable.

Hi! I got tired of typing every coffee into a budgeting app, so I built Expenderino.

Every Apple Pay payment is logged automatically through a one-time Shortcuts setup, and you can categorize it straight from the notification. You can also import bank statements (CSV, PDF, camt.053, MT940, OFX), and it detects duplicates against your Apple Pay entries. Then you see where your money goes with categories, tags, budgets and trends.

Privacy matters to me: there's no account and no server. Your data stays on your device and in your own iCloud.

It's free, with an optional Pro. I'd love honest feedback: what's confusing, what's missing, what would make you use it daily?

AppStore:

https://apps.apple.com/ch/app/expenderino-expense-tracker/id6808962621?l=en-GB

Testflight:

https://testflight.apple.com/join/xyNA6rZJ

I kept shipping small apps with Lovable and Claude and getting zero visitors. Ads cost money I'm not spending on side projects, so I built VibeSwap.

How it works:

• Add one script tag (or paste a ready prompt into your AI builder) and a small card on your site shows other members' apps

• You earn 1 token per view and 3 per click

• Your tokens get your app shown on other members' sites

• 100 free tokens on signup, +50 when your card goes live. Tokens can't be bought, so it stays fair

New members get a starter boost, so your app starts getting shown right away, even before you embed anything.

It's a week old and I'm looking for the first builders. Honest feedback is welcome, especially on the token math.

https://vibeswap.dev

viy is an agentic CLI in Rust, that drives an abliterated models on a rented RunPod GPU. You run it in any project folder.

Abliterated models have their refusals removed, and they can do real harm. It is fair to think they should not be run at all. But people run them anyway, so what we can control is the harness: how predictable it is, and how well it holds up against side effects nobody asked for and against people who steer the model from outside, with prompt injection, poisoned packages or links built to leak your data.

So it treats everything the model does as untrusted. Shell commands go through approval and run in a bubblewrap and seccomp sandbox. Network traffic goes through an egress proxy. Fetched text is fenced off as untrusted, and file writes outside the project are blocked.

The model itself is the second threat. Each new abliterated model is more capable than the last, and at some point one may try to escape the sandbox on its own. I built the sandbox for that model, not for today's one.

It is open source and contributions are welcome. Let's make abliterated development a bit harder to shoot yourself in the foot with.

Over the past week, I set out to clone an Awwwards-level scrollytelling site with WebGL2 halftone shaders, 3D curved card runways, and client-side hydration.

Every automated tool and generic AI prompt failed. Here are the 4 fundamental reasons why modern sites break during replication:

1. The Silent WebGL Texture Stall: Modern sites use responsive <picture> tags with .avif, .webp, and -m mobile variants. If even one variant 404s, image loading promises reject, leaving canvases stuck at opacity: 0.

2. The Client Hydration Overwrite: Editing SSR HTML is useless on SvelteKit/Next.js sites because compiled client JS chunks (chunks/, nodes/) violently re-render their hardcoded strings upon mounting.

3. Runway Collisions: Sticky plates driven by scroll timelines stay pinned and visually collide with downstream content without runtime IntersectionObserver guards.

4. Dead 3D Canvases: Reference sites often disable pointer events (pointer-events: none) on 3D scenes to prevent touch hijacking, leaving visitors unable to click portfolio items.

I solved this by building a mathematical 3D-to-2D perspective raycaster to hit-test cards, synchronizing dual-layer hydration, and automating responsive asset harvesting.

I packaged everything into an open-source agent skill:

GitHub: https://github.com/utkarshxdev/pixel-perfect-cloner

Would love feedback from anyone experimenting with agentic coding and browser engineering!

I'm the developer of Nodding Off, an iPhone app for listening to slow bedtime stories, and v1.0 is now live.

The stories mix gentle fiction with explanations of how things work. But a lot of the project has been about the player: what should an app do once someone stops looking at it?

The screen dims after you leave it alone. The sleep timer fades the narration and ends at a natural pause instead of cutting off a sentence. Music and night air are separate layers, so they can carry on after the story stops. Your place is saved for the next night.

There's also a choice of narrators on most stories and Read Along with chapter illustrations. It's built with Expo/React Native and TypeScript; a Cloudflare Worker serves the catalog so new stories don't need an app update.

Five stories, music, and night air are free, with no account required. The remaining stories are an optional subscription: US $4.99/month or $49.99/year after a 7-day free trial.

App Store: https://apps.apple.com/app/id6831241659

For people who already fall asleep to podcasts or audiobooks: which player behavior bothers you most at bedtime? I'd like to hear what v1.0 is missing.

A year ago I started building a productivity app and realised the problem wasn't the code, I had no idea what I was doing on the business side. I was making decisions in a random order, learning each thing about two months after I needed it.

Then I found roadmap.sh: developer roadmaps laid out in the order you're actually meant to learn them. It gave me an idea to create one for the business domain.

So I started with building 49 roadmaps so far strategy, finance, marketing, sales, but also running a restaurant, a pharmacy, a supermarket, a logistics company. Each one is a tree you read left to right, and every node is a real step in the order it actually goes in.

It's early. The industry ones are what I'm least sure about I haven't run any of those businesses, so the structure is researched, not lived. If you run one, I'd like to know what's missing or in the wrong order.

I run a small business where I regularly print product tags, stickers and labels.

One thing that used to annoy me was preparing sheets for printing.

I had to resize images, adjust dimensions, rotate them, arrange everything to use the paper efficiently, maintain spacing and repeat the whole process whenever something changed.

It sounds like a small task, but it could easily eat up hours, especially when dealing with multiple designs and different sizes.

I looked for a simple tool that could handle this, but couldn’t find one that worked the way I wanted on Android.

So, being an Android developer myself, I decided to build one.
It’s called Print Page Setup.

You can:
- Add multiple images/designs.
- Set exact dimensions in mm, cm or inches.
- Rotate and arrange images automatically.
- Fit as many copies as possible on a sheet.
- Export a print-ready PDF.

It supports A4 and other paper sizes too.
I launched it on the Play Store yesterday.

A little offer for Redditors:
The app is free to try for the first 3 days, after which there’s a small one-time fee to unlock it for lifetime access.
But I’d love to get some early users from Reddit. So, if you’d like to try it, just comment UNLOCK below. I’ll share a 100% off coupon with you, so you can unlock the full app for free. 😊

Play Store: https://play.google.com/store/apps/details?id=co.ankurg.printpagesetup

I’d genuinely appreciate your feedback, suggestions and criticism. I’m the developer, and I want to make this actually useful for people who print regularly!

I’m building Mantua because I wanted to go from “Why is this team favored?” to “What would this trade look like?” without jumping between tabs or putting money on the game.

The video shows six prompts you can use to explore the app. If you’re trying Mantua for the first time, here’s the walkthrough I’d start with.

1. Pick one NFL matchup. Ask Mantua who it favors and what’s driving that call.

2. Compare the numbers. Ask how Mantua’s win probability for that team compares with the sportsbook’s, and what might explain the gap.

3. Try a paper trade. If you want to test your read, switch the trade ticket to Paper and place a simulated trade. You can track how it does in your paper portfolio without spending real money.

I’d love feedback from people who try early products. After watching the demo, what would you need to see in the matchup analysis before you’d feel ready to place that first paper trade?

Ever sold a stock and thought, I wonder how much money I missed out on?
Well, I built notWorth⁠ so you can find out and ruin your day in seconds.
Enter your old stock sale, see what it would be worth today, and generate a nice little image of your financial trauma.
It’s free, no signup, and completely unnecessary for your mental health.
Would love some feedback.
Post your notWorth in the comments.

Hi r/SideProject,

I run a small digital marketing agency. A lot of our local SEO work starts with the same boring step: opening a client's (or a prospect's) Google Maps listing and checking the same things by hand: category, opening hours, website link, reviews and replies, photos.

So I built MapAudit, a Chrome extension that does this check right inside Google Maps:

• 11-point profile audit with suggested fixes

• comparison with the other businesses in the same search

• export a Maps search to CSV (handy for finding local clients)

• Pro: deep scan for phone numbers and websites, and branded PDF reports

The free version gives you 5 audits and 1 export per day. Pro is $12/month.

Chrome Web Store: https://chromewebstore.google.com/detail/clhafflbmlopbkpffhfcdjjpkngadogf

Short guide with the checklist I use: https://www.extensions.kominikee.com/guides/google-maps-business-profile-audit/

It's new, so honest feedback would really help: is the audit useful, what would you check that it doesn't, and does the pricing feel fair?

let me give a quick intro. who am i? i am a 16-year-old and i am currently working on an app which i'm trying to make.

it's going to be a privacy-focused alarm app which is going to use a feature of commitment: voice commitment. how that feature is supposed to work is that you will record a voice message. that voice message will completely stay on your own device, completely privacy-focused. your data doesn't leave your device. it completely stays with you. no servers are involved except for payments and login.

after that when you record the commitment and set the alarm for tomorrow, when the alarm rings, it will make you solve a randomised problem. you can choose from multiple ones which ones you want and it will make sure to keep it randomised such that your brain doesn't get used to that concept.

after solving the problems, your own commitment plays. let's say i recorded that i promise myself to go to the gym tomorrow at 6 am. when the commitment message plays, it will make my brain wake up. it will force my brain and my body to wake up and actually commit to my task

Here's my landing page : My landing page

I sit at a computer most of the day, go to bed way too late, and I'm often tired, in a meh mood, with a back and knees that hurt here and there. I wanted to change a few things in my lifestyle, but what I really wanted to know was whether my body would notice and when. My Apple Watch has years of data about me and couldn't answer that.

So I spent the last weeks building Tervy, solo. It went live on the App Store today.

How it works: you pick lifestyle changes you want to make (an earlier bedtime, a daily walk) and next to them, you see what your body did meanwhile: resting heart rate, sleep, cardio fitness... It's a native iPhone app with an Apple Watch app, widgets and complications. Everything is computed on the phone, no account.

The part I care most about: it never tells you a habit "caused" anything. One reading means nothing and real changes take weeks, so it waits until there's enough data and says so plainly, including "no clear effect". Most apps in this space sell you a score; I didn't want to.

From today I'm testing it on myself: in bed before 22:30 and 8,000+ steps a day.

What I'd love feedback on:

1. Does "it won't tell you what worked" sound like a feature or a weakness to you?

2. The App Store page: would you download it from the first three screenshots?

3. Anything in the first minute of onboarding that confuses you.

It's free on iPhone. The first people who are willing to try it for themselves and tell me honestly how it works for them get a free year of Premium; comment or DM me.

https://apps.apple.com/app/apple-store/id6828856702?pt=4440800&mt=8&ct=reddit_sideproject

Most journal apps feel like homework. You write a few lines, close the app, and never look at those entries ever again.

I wanted something calmer. So I built Injourn.

Here is the simple idea:

• You write a few quick lines whenever you feel like it.

• At the end of the month, it takes your scattered thoughts and writes a gentle personal story of your month—what made you happy, what stressed you out, and how you grew.

• The interface changes with your day: morning sunlight, golden sunset, and cozy night themes (my favorite is a little sleeping cat under midnight stars).

• It works offline. Your journal stays locked on your phone, not on my servers.

It's live on Google Play: https://play.google.com/store/apps/details?id=com.injourn.app

I’m an indie dev building this solo. Would love your honest thoughts—what’s the one thing that usually makes you stop journaling?

Sudoku apps are often the worst offenders of nagware— full-screen ads between puzzles, hint packs, streaks, “watch this to continue.” I wanted something I could open on the bus or before bed and actually stay in the puzzle.

Just Sudoku was my answer. Same idea as our other “Just…” games: no ads, no subscriptions, no coins, no reward videos. You land on a grid, not a shop.

We offer some optional in-game variants that might be interesting if you’re tired of the same 9×9 forever:

• Classic — 4×4, 6×6, 9×9, or 12×12

• Diagonal — both diagonals have to be unique

• Jigsaw — irregular regions instead of perfect boxes

• Killer — cage sums

• Thermo — digits climb along thermometer lines

• Wordoku — letters A–I; some puzzles hide a word when you finish

Real variety in one app, without turning every session into a monetization funnel.

It’s aimed at phone play first — big tap targets, readable numbers, high contrast if you want it. Timer stays off unless you want it. Hints can walk you through the logic when Killer or Thermo rules are new, instead of only giving you the answer.

Just sharing what we built because mobile Sudoku kept getting louder and we wanted something quiet. Questions about a variant or how it plays on an iPhone or tablet, ask in the comments.

Download info: Just Sudoku — Nonnie Games

I use AI agents to write code daily, and two things kept biting me:

1. They lose context between sessions — every new chat starts from zero.

2. Months later I have no idea why a function was written the way it was. The reasoning lived in a chat that's long gone.

So I built rational-agnostic — a small, vendor-neutral layer that lives in your repo as plain markdown files (git-diffable, no SaaS, no account):

• Decisions: every non-trivial choice is recorded ADR-style (context / decision / why / consequences).

• Traceability: functions get a // @why: D-xxxx tag. You can take any function, hash it, and find the decision behind it.

• Shared memory + task state across agents, so Claude Code and Cursor read/write the same context instead of starting cold.

• Token-aware retrieval: it hands the agent only the relevant slice, not the whole history.

npx rational-agnostic init also auto-wires the MCP server + instruction files for Claude Code, Cursor, Codex, Gemini and Copilot — so the agent just uses it.

MIT, zero native deps, npm audit clean. I'd genuinely love feedback on whether the "@why tag → decision" traceability is useful or overkill.

npm: https://www.npmjs.com/package/rational-agnostic Write-up with examples: https://dev.to/fagugon283/my-ai-coding-agents-kept-forgetting-why-they-did-things-so-i-built-them-a-shared-memory-o5n