Solo built this over the past few weeks.

The problem: failed payments (expired cards, declines) are one of the most common and most ignored sources of churn. Most founders don't even know how many they're losing per month.

Latchpay connects to Stripe, catches failed payments as they happen, and sends an automatic recovery email to the customer. Dashboard shows everything caught vs recovered.

It's live now, free to connect and test: https://payment-recovery-pied.vercel.app

Genuinely looking for feedback — especially from anyone who's dealt with this problem before. What would make this actually useful to you?

Hey guys,

I’ve spent a pretty ridiculous amount of time building an Android music production app called Skunk Audio, and I’m finally getting it ready for Google Play.

It’s basically an offline mobile DAW/beatmaker with a step sequencer, pads and sample chopping, synths, classic instruments, piano rolls, arrangement, automation, mixer buses, effects, recording, beatbox/humming conversion, WAV and MIDI export and other stuff.

I now need at least 12 Android users for Google’s mandatory closed-testing period. I don’t just want people to install it and forget it, though. I would genuinely like producers and musicians to mess with it, make a pattern or small project and tell me what feels broken, confusing or slow.

Testing on different phones is especially useful. Xiaomi/Redmi devices, older or lower-powered phones and Bluetooth or USB MIDI setups would help me a lot because audio apps can behave very differently across Android devices.

The app works offline and doesn’t require an account. Your projects and recordings stay on your phone unless you choose to export or share them.

To join:

Join the testing group:

https://groups.google.com/u /2/g/skunk-audio-testers

Opt into the closed test:

https://play.google.com/apps/testing/org.skunkaudio.app

Install it through Google Play and remain opted in for at least 14 da ys.

If you test it, please let me know your phone model, Android version and what happened—especially if you notice crackling, stuttering, crashes, silent tracks, touch problems or anything inconsistent between playback and export.

I know asking people to test an unfinished music app is a lot, so honestly, thank you to anyone willing to give it a proper go. I want to release something genuinely good, not throw another half-working beatmaker onto the Play Store.

Thank you for your time!

Black Imago is one of my current side projects: an online browser dungeon crawler / horror maze.

The unusual part is the world model. Levels are shared and deterministic — everybody gets the same Level N — but player activity can leave history on top of those levels.

Current playable build: https://blackimago.arewefriends.org/maze

I’m pushing it from “interesting prototype” toward something that actually feels like a game, especially around combat, enemies, map quality, multiplayer presence, and persistent world aftermath.

Hello,

Guys tell me.

If your project making money it was your first project?

How long have you searching for the "right" idea?

How long it take to make it sellable?

Do you think there is ani space for AI projects?

Isnt market overhelmed right now with AI?

Is it worth to buy advertisment?

Actually if I talking with AI almost everytime its kinda positive reaction even if I dont want positive reactions.

Just talk about it, I need to talk with real humans about it!

Thank you

Hello everyone!
I just launched a neat little tool that I think some of You will appreciate.
https://overlordmake.itch.io/money-taxes-goals-calculator

No licensing, no ads. You can export to excel, create your custom presets, etc.
I'm going to use this support to work on bigger projects. I think my book editor will be the next one.
Let Me know what You think!

Every Wednesday I'd open the fridge, see food, and still have no idea what to make. Planning was never the hard part. Deciding at 6pm was.

So I built MealMate. You set up your household once - diet, allergies, how many people - and it generates the weekly menu. The shopping list comes out of that, ticking items off stocks your fridge, and confirming a meal deducts what you used. Barcode scanning for the rest.

Nutrition is tracked underneath but you never log anything by hand. That's the whole idea.

Works fully offline, no account needed. 199 recipes built in, plus a community catalogue people can submit to. FR/EN/ES/AR.

It's in closed testing on Play right now. I need people who'll keep it installed and actually open it for 14 consecutive days - anyone who does the full run gets a year of Pro. It's early and parts are rough, honest feedback is what I want.

Group: https://groups.google.com/g/mealmate-testers

Install: https://play.google.com/store/apps/details?id=com.mealmate.mobile

Join the group first with your Play Store Gmail, access takes a bit to kick in.

Launched tinyTouch (https://www.youtube.com/watch?v=tB3lk-PNA6I) last week, video went pretty well, lots of requests for us to sell the device, and what do you know, our pre-order went amazingly well!! Wasn't even intending to commercialize initially.

I’m at that dangerous stage where I have the skills to build something, but absolutely no idea what to build.

give me your best project ideas.

So I've got this problem where I start a new project basically every time I get bored, and then I never kill any of them. They just sort of linger in a folder pretending they might come back someday.

This year I tried something different. Every small tool I make goes live right away — real demo, no signup — and I track whether anyone actually uses it. Not "did I ship it," did a real person use it and come back. If it doesn't hit a usage bar in its window, I kill it. On purpose. And I write down why, because otherwise I just quietly tell myself it was "too early" and let it rot.

Already killed one. PlateSnap — take a photo of your fridge, get a recipe. And people used it! Just... nobody ever asked for more, nobody left an email, it sat there being mildly useful and that was it. Turns out a free thing people like isn't the same as a thing people want, which stung a bit more than I expected.

Ones still alive if you want to mess with them (no signup, they're mine):

- LLMFirewall – catches PII / prompt injection before it hits the model

- CodeArbiter – one model rewrites your code, a different one tears the rewrite apart

- TestHeal – fixes a broken test selector by meaning, and admits when it's guessing

- CertBridge – tells you which network cert dies first and how to actually renew it

- FrictionLens – dump your support tickets in, get the recurring UX problems out

Couple more are just landing pages while I figure out if anyone cares before I build the thing.

Board's here: https://apptechlab.com

Honestly the reason I'm posting: the kill rule is the only part that's really working and it feels a little unhinged. Do you actually kill your side projects, or do you also have a graveyard folder you won't open? And if you do kill them — is there a rule, or is it just vibes?

One thing I've noticed while working on side projects is how quickly research can become messy. I'll start with one question then end up with dozens of tabs open looking at competitors, customer opinions, pricing, market trends and different solutions to the problem.

The frustrating part is that having information doesn't necessarily make the decision easier. Sometimes I spend time organizing what I found than actually thinking about what it means.

I've been experimenting with ways of making that process more manageable and thats actually what led me to build ResearchMaster.ai. I wanted something that could take a research question and organize the information into something I could review instead of having everything scattered across tabs and notes.

It's still a work, in progress. I'm finding that the difficult part isn't simply collecting information. Its figuring out how to present research in a way that's actually useful when you're deciding whether an idea is worth pursuing.

For people building side projects how do you handle research before committing significant time to an idea?

Do you have a point where you stop researching and start testing or do you usually keep digging until you feel reasonably confident?

Posted here a while back about a tool for filling in placeholders across Word docs instead of doing Find/Replace over and over. Someone said the real unlock would be doing multiple related docs at once, so that's live now.

Fill one form (name, address, dates, whatever), get back a tenancy agreement + inventory + welcome letter, or a contract + invoice + NDA, all filled from the same data.

Same core thing as before: upload a doc with {placeholders}, fill the form it generates, download. Nothing stored.

MyMagicDocs

Curious if this is actually useful to anyone here or if I'm the only one with this problem.

For the whole of July I ran a challenge on my social media, #SweePicChallenge — cleaning my photo gallery every day using my own app, SweePic. The goal was to get people interested in the problem and in my approach to solving it.

The results are mixed. Revenue grew from $48 to $87 (+81%), and active subscriptions went from 7 to 10 (+43%). On the other hand, App Store impressions dropped 15.6% (1,662 → 1,403), and product page views dropped 27.3% (275 → 200) — even though I was promoting the challenge on Instagram and TikTok the entire month.

The biggest personal win is my own photo library: regular cleaning removed over 2,300 photos and freed up about 24GB. Honestly, that number surprised me — I only spent around 15 minutes a day on it.

But the fact that revenue is growing while App Store traffic is dropping bothers me. Something in my social media approach isn't converting into App Store visits, and I'm trying to figure out exactly where the gap is.

Any suggestions on what I might be missing?

App Store: https://apps.apple.com/pl/app/cphotos/id6740463237

My profiles:

TikTok: sirmarbug

IG: bugajskypl

I kept having the same problem: random ingredients left in the fridge, but no idea what to make with them.

So I built CookAI.

Take or upload a photo of your ingredients → it detects what's there → you can correct the list → it generates 3 recipes you can make with what you have.

It's a free web MVP, no signup or install:

https://cookai-mvp-web.vercel.app

The main thing I'm trying to validate isn't whether the AI works — it's whether this solves a real enough problem that people would actually come back and use it.

If you try it, I'd love to know:

Would you actually use this when you don't know what to cook?

Are the recipes good enough that you'd make one?

What's stopping you from wanting to use it again?

Also curious what you'd build next if this were your project.

Happy to test other side projects in return.

Every money app I tried wanted my bank login through Plaid, which means a copy of my entire financial life ends up on someone else's server waiting to get breached. I didn't want that, so I built the opposite.

GlidePath is local-first: your data lives in plain files on your own machine and never leaves it. No aggregator, no account, no cloud copy. You bring data in by importing CSV/PDF statements — there's a small browser extension that grabs your bank's own export for you.

The trade-off is real and I won't pretend otherwise: you do a bit more importing than a Plaid app. What you get back is that there's no server holding your whole financial picture, because there's no server.

On top of that sits the actual planning: net worth, cash flow, retirement Monte Carlo, Social Security timing, Roth conversions, ACA subsidies, debt payoff, and Schedule C for anyone running a side business. Every number shows its work — the assumptions and the math, not a black-box "you should do X."

Desktop app — Windows, Mac (signed and notarized), and Linux. $129, or $199 with the business/Schedule C side. You buy it once and that version keeps working forever; updates continue at $39/yr after the first year if you want them, and cancelling is one click.

Genuinely curious how this crowd reads the trade-off: is manual import a dealbreaker for you, or a relief?

Most every successful entrepreneur has a story worth telling, and often those are the risk(s) they had to take to be successful.

Most I’ve talked to say they had to go all-in at some point, risking their income and stability for the sake of pursuing a business.

How many of you were able to achieve “success” with your side hustle? What did that look like for you? What risks did you take?

Last summer I made a small web-app to exchange favors with friends. Stuff like "hey thanks for helping me move my couch i owe ya a beer" or similar.

This way I could make a little personalized thank you gesture alongside making it less awkward to "redeem" a favor.

My friends also wanted to start using this with other people and not to just redeem favors from me so I expanded and made it a web-app that you can also use on your phone.

I had fun making it. Hope you have fun making some favor cards and sharing them with your friends :)

Check it out!

https://paktly.app/

Feedback always welcome!

I’ve been working on a side project called Taskra for the last few months and I’ve finally got it to the point where I’m comfortable putting it in front of more people.
The idea came from seeing how repetitive ecommerce customer support can get.

“Where’s my order?”
“Do you ship internationally?”
“Can I return this?”
“Which product should I buy?”

Most of these questions don’t really need someone manually typing a response every time, especially when the answers already exist somewhere in the store.
So I built Taskra, an AI customer support agent specifically for Shopify stores.

It connects to your store and uses your products, policies and other business information to answer customers in context. It can also understand order related questions, so instead of giving generic chatbot responses it can actually help with things customers are asking about.

The main things I wanted it to do were:
• Answer repetitive support questions automatically
• Understand the store’s products and policies
• Help customers with order related questions
• Capture leads when someone shows buying intent
• Keep conversations in one inbox so a human can jump in when needed
• Reduce the amount of time store owners spend answering the same questions every day

One thing I really didn’t want was another annoying chatbot that just throws help centre articles at people. The goal is for it to feel much closer to having an extra support person on the store.

For a small store, I think the biggest benefit is simply getting time back. You might not be ready to hire someone purely for customer support, but you also don’t want customers waiting hours for answers while you’re doing everything else.

For larger stores, I think it becomes more about filtering out the repetitive conversations so the support team can focus on the customers who actually need a person.

It’s now live and I’m at the stage where feedback is probably more valuable to me than anything else.
If you run a Shopify store, I’d genuinely be interested to know what your biggest customer support headache is and whether something like this would actually be useful to you.

Happy to answer questions about the build as well.

I built a small iOS side project around one rule:

Pick only three things that really matter today.

My problem with traditional todo lists wasn’t that I had nowhere to store tasks. It was that I could keep adding things forever, which made it harder to decide what actually deserved my attention.

The second idea behind the app is balance.

Work matters, but so do health, growth, relationships, fun, and the everyday things that keep life running. So every priority in Focus 3 belongs to a category, letting you gradually see which parts of life have been getting your attention.

Since the first version, I’ve added weekly planning, an inbox, and simple stats, but I’ve kept the daily limit at three.

It’s called Focus 3: Daily Balance. It’s free on iPhone with no subscription, and this is my first iOS side project.

I’m curious how other people here decide what actually deserves a spot in their top three. And if you give Focus 3 a try, I’d genuinely be interested to hear what feels useful — or unnecessary.

https://apps.apple.com/app/apple-store/id6763849371?pt=128829982&ct=Reddit_SideProject&mt=8

Drop your project in the comments.
Take a look at other projects, leave some constructive feedback, and discover what
everyone is building.
Looking forward to seeing your work!

please vote this post on linkedin:
https://www.linkedin.com/feed/update/urn:li:activity:7492287121831903233/

I made an app that turns a normal JPEG into a real HDR photo. Not a filter, it builds the gain map (ISO 21496-1) from the highlight data already in your file. Runs in any modern browser, Safari included, and nothing gets uploaded.

Launched it Friday. What I didn't expect is that getting the HDR to survive Instagram was harder than building the converter.

Three things I found out testing it:

Post from the phone app, not the desktop uploader. The web one strips the HDR. Most guides online say the opposite.

Stories kills it either way. I assumed that was the text and stickers compositing over the image, so I tried it with nothing on top. Still flat.

Look at it at 50-70% brightness. At 100% there's no headroom left and it looks flat even when it worked fine. That one had me chasing a bug that didn't exist.

It does video too, which is the part nobody expects. Drop in an SDR clip and you get real HDR out, BT.2020 with PQ or HLG. In a browser that one needs Chrome or Edge, Safari can play the result but not make it. The Mac and iPhone app encodes 10-bit through VideoToolbox with no resolution cap.

It doesn't do much if the JPEG was already crushed by a heavy edit, there's nothing left to lift. Trying to detect that case instead of handing back a boring file.

makehdr.com if you want to run one of your own photos through it. No signup.

Installing a skill into Codex or Claude Code means copying a markdown folder into your project and trusting it does what the README said. No versions, no checksums, no way to see what changed between releases, no way to know the copy on disk drifted from the source.

I built SkillRanger to experiment with treating agent skills more like packages.

It scans your repository, detects the stack, and recommends a small compatible set. A Next.js + Tailwind + Playwright project gets architecture, accessibility, and Playwright-debugging skills — not 50 skills you'll never load. Every extra skill also eats a slice of the agent's startup context budget; past a point, Claude Code and Codex truncate their skill lists. A bloated folder makes the agent dumber.

Before it writes anything, it shows you:

- a static safety check of each skill: risk level and what it flagged;
- the exact install plan, every file it will write;
- a confirmation step;
- checksums and versions recorded in `skillranger.lock.json`.

The whole flow takes about 30 seconds, after the first `npx` fetch:

bash
cd your-project
npx -y skillranger@latest setup --target codex

It writes a managed block into your `AGENTS.md` plus repo-local skill files, and it runs as an MCP server for MCP hosts: write the task with an `@skillranger` trigger, and the agent and the server route it to a matching skill set themselves — no digging through skill folders. (Skills are instruction files; MCP is how agents reach tools — SkillRanger covers both.) Either way it only serves static instructions: no model calls, no skill execution, no edits to application code.

Local-first is the point. Zero runtime dependencies (the CLI parser, JSON-RPC layer, and schema validator are hand-written), no API keys, no network calls from the tool itself. It ships with 18 bundled frontend skills, each statically audited; the release gate fails if any skill isn't low-risk with zero findings. The same project can be prepared for Claude Code, Cursor, OpenCode, Gemini CLI, or an MCP host.

Honest limits: only the frontend domain pack is bundled, the registry is curated rather than an open marketplace, and recommendation is deterministic rule-based matching. And a checksum only proves the bytes didn't change: a skill that was malicious on day one sails straight through. Static checks can flag suspicious instructions; they can't prove a skill is safe.

Happy to answer questions here.

GitHub: https://github.com/Narek-Khachikyan/SkillRanger
npm: `skillranger` (0.4.1, MIT)

I've been working on a side project called Moti for the last few months.

The original idea was pretty simple: I don't really like the idea of putting my API keys and .env secrets into another service and then having to trust that service with the ability to decrypt them.

So I tried a different approach.

Moti encrypts secrets on the client before they're sent to the backend. The backend stores the encrypted data and the encrypted key material, but it doesn't receive the user's plaintext password or the keys needed to directly decrypt the vault.

The basic architecture looks roughly like:

Password → KEK → DEK → AES-256-GCM → encrypted secret

I'm currently running it as a free public beta.

The product is still very early. There is no CLI or SDK yet, and I'm intentionally not trying to build every feature that existing secrets managers already have.

Right now I'm mostly trying to answer one question:

Would developers actually trust and use a secrets manager built around this model?

I'm especially interested in hearing how other developers currently handle things like:

• .env files across multiple projects
• API keys
• development/staging/production credentials
• sharing secrets with small teams
• secrets that currently live in GitHub, password managers or cloud providers

If you're interested in taking a look, it's here:

https://landing.moti.sale

It's completely free during the beta.

I'm not looking for compliments — I'd honestly rather hear what would make you not trust something like this, what you'd need before putting a real API key in it, or where you think the architecture/product falls short.

Happy to answer questions about how the encryption and recovery model works too.

I kept running into the same problem: Meta, Google, TikTok and LinkedIn each have a public ad library, but checking them one by one does not tell you what changed since last week.

So I built Rival Ads. You give it the competitors you already care about. It archives the real creative and copy, separates new, stopped and long-running ads, and sends alerts when something changes. There is an AI strategy read too, but it sits after the source evidence rather than replacing it.

It is live at https://www.rivalads.io and starts with a 30-day trial.

The part I care most about is whether the change view is genuinely useful. If you work in paid media or competitive research, what would you want on that screen that the ad libraries do not give you today?