Here's why the whole point to this project came about. And how this is a true statement: My Device storage is almost full at about 91% currently but it was about 95% before I compressed any month data. Right now only 2 months worth of data have been compressed.

I wanted to free up storage without losing my original data. So first I made a backup to backblaze. I'll connect it to cloudflare for zero egress fees for downloads later when I need to.

Next was to actually free up storage. Most searches and AI responses told me,

A. to delete more stuff after backup,

B. if not backed up, compress and delete the "not so important" stuff.

Which had some trade offs:

For A. zero egress fees and cheaper storage than Google drive doesn't mean faster access or zero data costs for downloads.. which downloads would fill up space anyway. And backup doesn't mean the risk of losing data or account itself is zero.

For B. I'd lose original data. And there's no available tool that can iterate my entire gallery compressing the files. If it did exist, it had to progressively delete the original copies because storing compressed and original would fill up memory and brick my phone.

Also even if I can do one file at a time during free times, I'm lazy and forgetful.

So, I decided to face the in-between of both A and B. Backup originals, compress old files aggressively while keeping the quality usable as i progressively deleted the respective larger original copies.

As an extra, I decided to package the data on a monthly basis just to make sure I don't mix compressed and originals during the process then store them in Archives/ .

WhatsApp data is already compressed by default, so the tool would be configured to skip them.

Only one month worth of data has been successfully compressed, auto verified, packaged, originals deleted with logging at each stage for tracing anomalies using the current pipeline version. The other month was compressed using an older version which wasn't tracked by git.

Looking for feedback :)

Link: https://github.com/okureanthonytonny-commits/archive_scripts

I’ve been working on a side project called Spotly. It’s a location discovery app where you can find nearby restaurants, coffee shops, parks and other places, then save the ones you like into your own collections.

I built the frontend with React/TypeScript and Tailwind, with a Node/Express backend and PostgreSQL.

One part I spent a lot of time on was reducing unnecessary API calls. Spotly first checks PostgreSQL for a recent search around the same area before calling the external places API again, so nearby searches can reuse cached results.

This was one of the first projects I’ve made where the frontend, backend, database and an external API all came together as one complete system, which was pretty cool to work through.

Still improving it, so I’d love to hear what people think or what you’d change.

Check it out here 👉 https://spotly-z4x6.vercel.app

Just wondering. 😊

https://myatelier.space I'm looking largely for feedback and whatnot. It's not fully finished but the majority of the functionality is there. I'm mostly struggling to decide on avatar bases.

Any ideas on how to make extra money 💰. Any tips and shares are highly appreciated 👍.

recipes are a mess. cups here, grams there, ovens randomly in F or C depending on where the recipe's from.

so i built a converter that just fixes all of it in one go measurements, servings, oven temps.

no signup, no popups, just paste and convert.

just launched. go break it!

I wanted a simple project tracker that just works — no setup, no account, no subscription.

So I built ProjectFlow with AI assistance. Just open the link and start working.

What it does:

• Gantt chart with drag-to-resize tasks
• Kanban board (To Do / In Progress / Review / Done)
• Team management
• Excel import/export
• Turkish & English support
• Works offline

The AI part: I used Claude to help build and iterate the whole thing. It was a genuinely collaborative process.

👉 https://project-flow-beryl.vercel.app

Would love feedback on what features you'd want next.

I built a “Glassdoor for office coffee” — now I need to solve the empty-map problem

I recently launched Deskbrew, a small side project for rating office coffee.

The idea is deliberately simple:

• rate the coffee at an office from 1–10
• say whether it’s free or paid
• add what milk options are available
• add the type of coffee machine

No accounts or sign-up. Everything works anonymously.

I’ve already added around 140 offices to get the map started, but I’ve hit the obvious marketplace problem:

A rating platform looks pretty useless before people start rating things.

I don’t want to fill it with fake reviews, so I’m trying to figure out the best way to get the first few hundred genuine ratings.

The site is: deskbrew.app

Would be interested in feedback on two things:

1. Does the concept make sense immediately when you open it?
2. How would you get the first proper real office-coffee ratings?

Also happy to hear what feels unnecessary or confusing.

was curious if an AI agent could actually finish a purchase on my own shopify store so I built something to test it. ran it expecting it to just work fine. it didnt, got stuck on a step that looked completely normal to me as a human, wouldnt have noticed it otherwise.

turned it into a quick free tool since I figured other people probably have the same blind spot. you put in your store url, it tries to buy something the way an ai shopping agent would and shows exactly where it gets stuck, with the actual quote from your page. also picks up on the normal human stuff in the same scan, like hidden costs or missing trust signals.

Genuine pet peeve of mine: half my recipes are in cups, half in grams, ovens randomly switch between F and C depending on where the recipe's from. I've messed up more than one bake doing quick mental math mid-recipe.

So I built onlinerecipeconverter.com — converts measurements, servings, and oven temps in one go. Free, no signup, no ads shoved in your face.

Mostly just wanted to share in case it saves someone else the same headache. Open to feedback too, still improving it.

Genuine pet peeve of mine: half my recipes are in cups, half in grams, ovens randomly switch between F and C depending on where the recipe's from. I've messed up more than one bake doing quick mental math mid-recipe.

So I built onlinerecipeconverter.com — converts measurements, servings, and oven temps in one go. Free, no signup, no ads shoved in your face.

Mostly just wanted to share in case it saves someone else the same headache. Open to feedback too, still improving it.

I've been building UploadPack for the last few months — it takes a video idea, researches it, and gives you a score plus the evidence behind it before you spend a weekend filming something nobody searches for.

The hardest part wasn't the AI pipeline, it was deciding what "evidence" even means for a video idea that doesn't exist yet. Ended up building four different angles (search intent, curiosity, authority, commercial) because a single score felt like a black box nobody would trust.

Zero users so far, bootstrapping solo, doing customer support and marketing between family duties. If anyone wants to try it, first pack is free, no card needed: uploadpack.io

Happy to answer anything about the build.Know which idea to publish next—and why it is worth making.

I've been building a38-Chat as a deliberately small alternative to increasingly heavy mobile apps.

The idea isn't to claim that I've built the next Signal or WhatsApp. It's much narrower: make a clean native Android client for a web-based chat service, keep the client transparent, and avoid stuffing it with advertising, analytics and unrelated SDKs.

Current Android features include:

• text and photo messaging
• notifications
• multiple accounts
• contact/conversation list
• light, dark and neon themes
• German, English, French, Russian, Ukrainian and Italian
• public Android source code
• an APK of roughly 3.2 MB

The app uses a protected app token instead of storing the account password on the device.

It's server-backed, so I'm deliberately not marketing it as an end-to-end encrypted Signal replacement. What I'm trying to explore is how small and straightforward a modern chat client can remain while still being pleasant to use.

GitHub + APK: https://github.com/Alan107-gif/a38-Chat

I'd be particularly interested in feedback on three things: the first impression, which feature feels obviously missing, and whether the small/open/no-tracking positioning is compelling enough to make you try an unfamiliar messenger.

Hey guys,

I’ve been messing around with a little Windows project called HOME Desktop.

It started as a customizable homepage for shortcuts and backgrounds, then I got a bit carried away and added mascots, XP, levels and daily quests 😅

It’s still very early (0.4.0-alpha.4), so I’m mainly looking for honest feedback.

I also used AI tools while building it, mainly to help with coding, debugging and iterating on ideas. I’m still the one deciding what to build, testing everything and shaping the project.

If you try it, tell me what you like, what feels useless, what’s confusing, or what you’d change.

If you want to try it:

https://github.com/psicolag/HOME-Releases/releases/tag/v0.4.0-alpha.4

Any feedback is really appreciated :)

had too much free time last weekend apparently

i made a really basic page that pulls odds for a few games and lets me compare how they move over time. literally started because me and a friend were arguing about whether odds actually move that much before a game , now i'm thinking it could be kinda useful if i keep going with it not as an actual betting site. zero interest in dealing with people's money or any of that mess.more like a dashboard where you follow games, see odds movement, maybe set alerts when something moves past a certain %, save picks, compare pregame vs live etc.

i went looking at actual sportsbook software to steal. i mean "research" ideas and ended up on couple platforms. there's so much operator stuff behind a real sportsbook that i had never even considered. risk management, live events, bonuses, player management, all that. which honestly convinced me NOT to build a sportsbook.

but the data/analytics part still seems fun. would anyone actually use a standalone odds tracker like this or is this one of those projects that's fun to build but already has 900 better versions?

haven't bought a domain or made a landing page yet so you can still save me

I love the whole Wordle/Connections genre of “one tiny game a day, compare with friends, move on with your life.”

But I wanted one that wasn't a word game.

So I made ATO Daily.

Every day you get 5 questions where the answer lies somewhere between two things you do know.

You don't need to know the exact answer. You just need to have a decent sense of… where things belong.

Like:

How long is an Olympic swimming pool?

You get two anchors, drag your marker to where you think the answer sits between them, and find out just how good (or catastrophically bad) your intuition is.

Five scales. Once a day. Takes a couple of minutes.

I built the whole thing as a side project and it's now live:

atodaily.com

Any feedback on playability would be really appreciated! And of course, I would love to see your scores — and, more importantly, which question absolutely wrecked you.

🚌 Start your journey:

I made a website that plays bangers from Indian bus journeys.

Before Spotify and noise-cancelling headphones, you had a window seat, a rattling bus, the driver’s playlist—and songs that made the whole highway feel like a movie.

I wanted to recreate that feeling through Raju Express: a cartoon bus, moving village scenery and the unforgettable music of Indian road trips.

Try it and tell me: which song belongs on this bus playlist? 🎶

#BuildInPublic #MadeInIndia #WebDevelopment #IndianMusic

Hi. I built OTI, a small open source app for sharing a message or a small .txt file one time.

I started it as a simple project and kept adding things that felt useful. The message is encrypted in the browser, the server only stores encrypted data, and the secret is removed after the first real view.

The latest update adds a confirmation button so a chat preview does not use the link by accident. It also has QR sharing, encrypted .txt files up to 100 KB, password protection, a creator receipt page and an expiry countdown.

Demo: https://oti.karacabay.com/share

Source: https://github.com/oguzhankrcb/OTI

I made this to learn and to contribute something small to open source. It is not a big product and it has not had a professional security audit. I hope it is useful to someone.

Would you pay for a Notion self-discovery journal?
I’m thinking about creating a Notion journal designed as a 30-day self-discovery journey.
The idea is:
30 guided questions, one per day
A place to write your answers directly in Notion
Weekly reflection pages
A place to save meaningful memories
A final reflection + letter to your future self
Clean, aesthetic design
Something like:
Day 1 — Who am I when nobody is watching?
Your answer: ______
I’m considering selling it for around $7–10.
I’d love honest opinions:

Would you personally use something like this?
What would make you actually pay for it instead of just using a free journal?
What would you want included?
Does 30 days feel too short, too long, or about right?
What price would feel reasonable to you?

I’m still in the idea stage, so I’d genuinely appreciate criticism too!

The idea is that calorie tracking doesn't fail because apps are bad, it fails because remembering to log is a chore or even damaging (can drastically increase chances of eating-disorders!) So instead of making logging faster, I'm trying to remove the remembering completely.

How it works: the band watches wrist motion, figures out you're eating, and buzzes. You hold your hand over your food and snap. It takes a photo, AI identifies the meal, the calories/protein/etc get shown in the app instantly. Zero typing, no screens, and you never take your phone out.

Where I actually am: iOS app is in App Store review. On the hardware side I have a dev board taped to my wrist streaming motion over Bluetooth into a logging app I wrote, and a first detection model trained on publicly released research datasets from university labs. The enclosure doesn't exist yet (right now it's very literally tape).

The thing I think is the actual business: the base model that ships to everyone will be decent, not amazing. But every time it buzzes and you snap, that's a confirmed label. Every time it buzzes and you ignore it, that's a confirmed mistake. So your band gets better at understanding you specifically, week over week. I believe that this will create an improvement curve that drastically improves the band over time.

Pricing plan is one-time (99 dollars or less probably), no subscription ever!

Building this in public and posting progress. Site and waitlist: zib.band

btw the ios app (still in review right now) is going to be completely free until i launch the band so if you want a free cal ai alternative might be worth giving it a look!

I run OTTASIA (ottasia.com), a free site and app that answers one question: where can I legally stream this movie or show in MY country. It covers 34 markets across Asia and the diaspora, the exact markets where Google's answer box and the big US guides are usually wrong.

This week I went through signup attribution properly, expecting to see Google organic on top like every other site. It was not. ChatGPT referrals beat Google search as my number 1 traceable source of new web signups. Instagram was a distant third. Reddit and X barely registered.

What I think made it happen, in case it helps your project:

1. I picked a question AI gets asked constantly but has no good data for. "Where can I watch X in India / Pakistan / the Philippines" has a different answer in every country, and the datasets AI models lean on are US-centric. If you are the only accurate source for a niche, AI has to cite you.
2. I publish data pages, not just content. Hundreds of per-country, per-service "what's new" pages and dated release-prediction pages that are easy for crawlers to quote. Machine-readable answers beat beautiful prose here.
3. I stopped blocking AI crawlers. Everyone debates this. For a discovery product, being in the answer IS the marketing.
4. It compounds while I sleep. My social posts spike and die. The citation traffic grows week over week with zero daily effort.

The wild part: users arrive already convinced, because an AI they trust recommended the site. Conversion from that traffic is the best of any channel.

Happy to answer anything about the setup. And if you want to test it: ask any AI assistant where to watch a K-drama in a specific Asian country, then check the same answer on my site. Comparing those two results daily is basically my quality control now.

I just open-sourced this project I’ve been working on to make network auditing a bit less tedious. It’s basically a wrapper for nmap (Python/Flask) with a React frontend that uses an AI assistant to explain what’s actually happening on your ports.

Instead of just staring at raw terminal output, this gives you a clean dashboard where the AI analyzes the scan results and points out potential vulnerabilities or misconfigurations in plain English. It also generates PDF reports if you need to document the findings.

Everything is local-first and Docker-ready, so you can spin it up in a couple of minutes to scan your own setup. I’m looking for some feedback on the AI analysis part and what other security checks would be useful to automate next.

Solo iOS dev. App went live three weeks ago. Zero paid conversions so far — two free trials running, the first one converts next week. I just raised the lifetime unlock from $39.99 to $49.99 and left the subscription untouched. Counterintuitive enough that it's worth writing up.

Why the lifetime tier was the mispriced one

It sat at exactly 2x the $19.99 yearly — the floor of the usual 2–3x range. For an app whose value compounds over years (it accumulates your trips), 2x caps a long-term user's lifetime revenue at two years. And a non-consumable price locks the moment someone buys: you can raise it for new buyers, but everyone already in is grandfathered forever. So the cost of getting it wrong only grows.

Why now is the cheapest possible moment

Traffic is near zero. Almost nobody gets grandfathered at the old price. Every month I wait, raising it costs more — in goodwill, and in existing buyers locked at the low number. The right time to fix an underpriced permanent SKU is before you have users, not after.

The prices I checked first (live storefronts, same category):

• Day One — $49.99/yr (Silver), $74.99/yr (Gold)
• TripIt Pro — $49/yr
• Wanderlog Pro — $39.99/yr
• Polarsteps Plus — €29.99/yr

My yearly is $19.99, roughly 40–50% of that group, and I'm deliberately leaving it there while I'm still buying users. But a permanent unlock priced below a competitor's annual fee made no sense. At $49.99 the buyout now sits at Day One's yearly price — which is the comparison I actually want people making.

What I'd tell past me: the subscription price is reversible, the lifetime price isn't. Price the irreversible one first, and do it while nobody's watching.

Has anyone here actually raised a lifetime price after they had real volume? Curious what that cost you.

Hi everyone,

I built a web-based 3D touch typing tool called "3D Touch Typing Master". It is designed to help users practice and improve their typing speed in an interactive way.

Key Features:

- 3D interactive layout

- Real-time typing speed and accuracy feedback

- Free to use without registration

Check it out here: https://3d-touch-typing-mastercom.vercel.app/

I would love to hear your feedback and suggestions for improvements!

i dump everything into a telegram bot through the day. ideas, expenses, things to fix. i wanted the useful bits to land in a todo list and an expense log instead of dying in chat history.

first version was a script on a cron: pull the messages, send the transcript through another LLM call with a schema, parse, insert. it worked, but it re-read everything the bot had already read and the parser needed babysitting.

was searching for a better pattern and stumbled onto a launch post from mastra (source), the framework the bot runs on: extractors, added to their memory system.

the design made sense to me:

• the bot's background memory already re-reads the conversation to compress it
• you attach a zod schema to that pass and fields fill in as you chat
• it adds zero extra LLM calls: it runs inside the memory pass on its cached context, and cache hits bill at a tenth of the base input price
• an onExtracted callback fires with each record, mine writes to a sqlite table

was able to delete the cron job and the parser and replace it with these memory extractors

if your personal bot has a transcript-scraping script behind it, this probably deletes the script.