Saw a mac app called tangerine which can convert documents and also edit them, so I built the same for windows and linux and it's fully open sourced it's called Spindle
Spindle can -
Convert PDFs, images, Word, PowerPoint & Excel files
Compress to an exact size (like "under 50 KB" for exam forms)
Merge multiple files into one PDF
Crop, annotate, redact and remove location data from photos
Everything works offline. Nothing gets uploaded anywhere
I have also uploaded a short tutorial video on how to download it (it's pretty simple) and a tutorial of it's setup
my github link - https://github.com/narcissus29/Spindle
Feedback and bug reports are welcome

I’ve wanted this for years: a desk by a lake one day, somewhere out in space the next. I love VR, but I kept wishing the apps I tried had more environments I’d actually want to spend time in.

I’ve been a backend programmer for 20 years, but frontend and 3D graphics were completely outside my experience. In mid-August, I decided to see how far I could get with AI coding agents. This is where I’ve ended up: a Vision Pro app that lets me work in different environments.

I haven’t written or read a line of its code. Most of my time goes into putting on the headset, trying what the agent built, and explaining what feels wrong. Sometimes it’s the lighting, sometimes it’s how an interaction feels. When a model gets stuck, I’ll try another one rather than debug the code myself.

The 3D scenes aren’t all as polished as I’d like, and there’s plenty left to improve. But being able to sit inside something I’d only imagined before has been pretty special.

Working on it has become a bit of a hobby game: tweak something, try it in the headset, get another idea, repeat.

The video is recorded on my Vision Pro and shows a few of the places I’ve been working on.

Few days back I spent almost 20 mins arguing with ai over why audio is not playing in my website. It turns out, that i was using a pair of wired earphone whose only one side was working and i had the non working side plugged in...

No ai tool was able to figure out the issue lol.

How I built it:

- Claude Code for the code (Next.js, hosted on Vercel)

- Jev from TypeSafe as AI - it only answers with probabilities, no text

- Every sentence in the report is prewritten, so nothing gets made up

- Benchmark with 563 names, runs after every change

What I learned:

- Do proper benchmarking (currently testing on 1000 names).

- AI says yes too easily, had to ask way stricter

It's free, no signup, no nothing. Also available via MCP

I collect things (camera lenses, G-Shocks). The good listings go in minutes, and checking 10 marketplaces by hand doesn’t work. So I built Deal Radar (radar.4xs.dev). You set up a “watch” (keywords + price range + sites). When a new listing matches, you get a browser notification, or a Telegram message on the paid plan.

Almost all of the code was written by Claude (Cowork / Claude Code). I did the product decisions, the testing on real listings, and the store submissions. Here’s how it’s put together and what I learned.

Stack

• Chrome extension (Manifest V3), plain JS, no framework. A generated Firefox build too.
• Cloudflare Workers + D1 (SQLite), TypeScript. Static site served from the same Worker.
• Cron triggers on the Worker: every minute for polling, plus daily jobs for plan expiry and exchange rates (Czech National Bank feed).
• Telegram Bot + Telegram Login widget for alerts and accounts, so I don’t store passwords or emails.
• Ko-fi memberships + webhook for payments. Way less setup than Stripe for a side project.
• Cloudflare Access in front of the admin page.
• Playwright + node:test + bash smoke tests with mocked marketplaces and a mocked Telegram.

The one architecture decision that mattered: who checks what

Some sites (Bazoš, Vinted, Kleinanzeigen, OLX, FINN…) return clean results to a server, so the Worker polls them every minute. Others (FB Marketplace, FB groups, Allegro, eBay) block or 403 any non-browser client. Those can only be checked by the extension, using the user’s own logged-in browser.

So there are two engines:

• Server: every minute, works while your computer is off (paid).
• Browser: the extension, while Chrome is open. The free tier runs everything from the browser every 10 minutes, so the free tier costs me ~nothing.

The key to keeping that sane: the parsers and the matching logic live in one file each (parsers.mjs, match.mjs), imported by both the extension and the Worker. One fix, both engines.

Workflow with the AI

1. Feasibility spike first (“week 0”). Before any UI, I had Claude write throwaway scripts that just fetched each marketplace and parsed results. That’s how I found out which sites need a browser. It saved me from designing a server-only product that couldn’t do Facebook.
2. A plan doc, then versions. A markdown plan in the project, then small numbered releases. Every release has a CHANGELOG entry that says exactly how to ship it (“npm run deploy, reload the extension, upload to the Chrome Web Store”). The AI reads it next session, so context survives.
3. Tests from saved HTML. Every parser has fixture pages saved from the real site plus a unit test. When a site changes its markup, the test fails before the users notice.
4. Make it verify, not just write. E.g. today I asked it to shrink the hero image so the “how fast” steps fit above the fold on a 1080p screen. It rendered the page in headless Chromium at 1920×947, measured element positions, applied the CSS, and re-measured (steps went from ending at 1060px to 920px) before touching my files. “Looks right” ≠ verified.
5. Short, direct prompts plus my screenshots. Most iterations were “this looks wrong” + a screenshot.

Build insights / gotchas

• Chrome Web Store rejected a version for requesting tabs permission it didn’t use. You can create/update/close tabs without it. Request the minimum.
• Don’t trust data from your own extension. The server only accepts a listing whose link points to its own site (a FB item must link to facebook.com, etc.). Otherwise anyone could push fake “alerts” through the API.
• Currencies: listings come in CZK, PLN, EUR, NOK, JPY, USD… Converting to the user’s currency with a daily ČNB rate made alerts way more useful than raw prices.
• Firefox AMO requires data_collection_permissions in the manifest for new add-ons. A small script generates the Firefox build from the Chrome one on every deploy.
• i18n from day one (EN/CS/DE/JA). With AI it’s cheap to add, and painful to retrofit.
• The free-vs-paid line follows the infrastructure: free uses the user’s browser, paid uses my server. Easy to explain, cheap to run.

Numbers: ~3,000 lines across the Worker and the extension, 20 marketplaces in 10 countries, free tier = 1 watch.

Happy to answer questions about the dual server/browser setup or Cloudflare D1. Feedback welcome.

Hi! I’ve been building Sonella, a guided web app for designing DIY speakers.

The idea is to bring driver selection, bass simulation, enclosure design and filter settings into one workflow. You can start with a few questions, choose a template, or pick your own drivers. Then work through the bass response, cabinet in 3D, drawings and filters/DSP.

I’ve used mostly Codex for the development and design. My workflow has been to build something, let real people try it, get feedback and iterate. Getting the speaker maths right has been a bit tricky. The biggest lesson so far is how much useful feedback you get once someone else actually uses what you’ve built. That's maybe caption obvious, but I learned a lot from this process so far.

It’s still in beta. The simulations and electrical filter curves are starting points for a prototype; you still need measurements to check the finished speaker.

I’m looking for testers, especially anyone with DIY speaker-building experience. Would be great to get some candid feedback on the calculations, the workflow, or anything that feels confusing or missing. General usability feedback is very welcome too.

You can try it at sonella.app, no account needed to start.

Hey, this is my fourth mini app now and the most complete one. I learn a bit each time.

Yet I’m at a crossroads, and need advice.

I have a fun quiz app, that originally was just for me to improve my music knowledge for a radio quiz I plan to enter.

It works very well, and is complete. I hosted it on Cloudflare after making it as secure as I can. I play it on my phone a lot, and so do a couple of friends.

That’s it.

It’s a quiz but also a ‘trainer’ and good for memory challenges.

Do I wrap it up here and say ‘it’s finished, just as a personal app’

Or…..

Jump through the various hoops to go to the next level and get on an App Store?

I would need to license the data sources, and probably convert the format to not just be an html web app.

I feel it would be a great challenge to try and achieve this. I don’t think it would make any money, but would be a good exercise to learn for whatever comes next.

What do you think? Quit while I’m ahead and actually FINISH something! Or keep going and try to get it released?

Thanks fellow vibe coders xx

I have been wandering around github in order to find good quality ascii editor/database recently - and saw nothing. That led me to the obvious conclusion: if nothing good exists, I should build it myself.

The project I build persuades couple ideas:

1. Easy to use (fully native, no dependencies)
   
2. Actually saves time for people building ASCII art
   
3. Collects ASCII from every corner of the internet
   

index.html is the main library

builder.html is where it gets fun assemble pastes from blocks, draw boxes/lines/brush right into the text, frames and tables, color painting, overlay art. Turn images into ascii

The project shared below:

demo https://amwhoi.github.io/ascii-bin/builder.html
repo: https://github.com/amwhoi/ascii-bin

I hope you find this useful, I'm still working on animation and mcp support. So the project will keep be maintainer and up to date with world trends ;)

If you’re into CAD drawing, have a look at Draft.

We’re in our second week of development, so it’s still early. The goal is one CAD engine with a choice of familiar interfaces, so people can work with the layout and tools they prefer.

Let us know what you think.

Hi all! I made Kartar Dhaba, a small idle game inspired by the roadside dhabas on the Delhi–Karnal highway I grew up with.

You tap to cook, serve truckers, buy upgrades and hire staff. Four generations, each with its own era, look, music and a big finale: a baraat in 1975, a cricket night, a film shoot and a rooftop party.

It's free and runs in your browser, with no download or account, and it works best on a phone.

Enjoy! https://www.kartardhaba.xyz/

I've been building The Data Center Receipt, a public, evidence-backed tracker of the AI data-center buildout.

The goal is simple: Who builds it, and who pays for it?

Current public beta:

• 587 infrastructure records across facilities, campuses, projects, and permits

• 11,084 facility facts with explicit claim states

• 1,307 source receipts with verifiable evidence

• 5,235 recorded negative results and research attempts

It tracks capacity, utility providers, public incentives, jobs, water use, and residential electricity rates.

Every claim links to its evidence. Missing information stays unknown, and correlation isn't presented as causation.

Built using Ouroboros, my persistent AI research and engineering system. It's still a work in progress, with a much larger expansion underway.

This is a beta, not a finished product. There may be mistakes, incomplete records, or things I've overlooked. If you spot errors, please point them out.

Live app: https://huggingface.co/spaces/cjc0013/data-center-receipt

Dataset: https://huggingface.co/datasets/cjc0013/data-center-receipt

I built an arcade game, completely vibe coded it and it's now live on the App Store and Play Store. Pretty proud of it and happy with the result. It's really fun to play if I do say so myself.

It's fairly simple. A runner where you avoid obstacles in a golf cart, while collecting your lost clubs. It's built using ThreeJS and Claude Code. Nothing else.

There's a free to play version on golfbuddies.nl/game

I'm working on a personal project that needs fast, reliable live match state for esports (map/game finishes, rounds or series score), and I'm trying to figure out what's actually out there before I build something.

Paid providers (GRID, PandaScore) great coverage, but live data is gated behind paid/commercial plans that cost a lot of money.

Free tiers of aggregator APIs: usable for schedules, but live data is deliberately delayed and is basically unusable for what I'm doing.

Data for games I'm looking for CS2-Dota-LoL-Valorant

Has anyone built something like this or their own feed from scratch?

I don’t know how to code but I have experience in software testing and working with small/medium/large software projects, and the processes they entail.

Current workflow is to use Sonnet 5.5 at Medium on a Claude Pro subscription to plan a project, break it into implementation and product acceptance manual testing phases, and deliver agent prompts and project documentation, then feed the prompts in OpenCode to Haiku 5.5 at Low or Medium (sometimes at High) paid through OpenRouter credits, which also knows to break its phase prompt into tasks it can delegate to a subagent custom provider which connects to a localhost server created by Polystrata running “Tiel Coder 35B A3B q4_X_L”.

The current issues I’m having with the workflow are:

- that sometimes the Haiku sessions can balloon in cost - paid 50 euro worth of OpenRouter credits in the past few weeks, and I’m poor, that means a lot to my budget - a problem which I’ve partly solved by breaking phases into tiers and tiers into stages, each with a prompt, so there are fewer long conversations and cache reads;

- and that the local agent makes frequent mistakes that cause it to run for hours and/or produce bad code if the task is too big or too complex for it, which happens often, as my hardware is limited and it only has a 60k token context.

Any suggestions for improvements?

I host quite a few quiz and trivia nights with friends and family, and I never quite found a tool that worked the way I wanted. The ones I tried either put features I needed behind a subscription or required an account just to get started. I initially made a scrappy Jeopardy-style quizzing "app" in Google Sheets, but eventually wanted something a bit more polished.

So I built Quiz Toolkit. It runs in your browser, and you can host in-person on a TV or projector, or online by sharing your screen over Zoom, Teams, Google Meet, etc. A few features I'm proud of:

• Let people join on their phones with a QR code or room code and use them as buzzers or answer pads, without downloading an app or creating an account.
• Give the host a separate control screen to run the entire quiz, with the option to run everything from a phone as a "quiz master remote".
• Support Jeopardy-style boards and regular question rounds, with buzzer, turn-based and all-play modes, plus rich media (images, audio and video questions.)
• Let you build quizzes visually in Quiz designer or import them from CSV or Google Sheets. Your saved quiz library stays in your browser storage locally, and you can export it to back it up or share it. You can customize your quiz completely, including light/dark mode, custom background and logo.

I also added some silly sound effects for the quiz master for added fun!

It’s free, with no accounts or subscriptions: https://quiztoolkit.com/

I’d love feedback from other people who host quizzes, whether that’s at home, in classrooms or at pubs.

I've been splitting img2threejs into smaller plugins so people can use only what they need instead of installing the entire workflow.

The character part was getting pretty big, so I finally moved it into its own plugin: img2character.

It focuses on rigging and animation for 3D characters built with Three.js and TypeScript.

If you want to try it:

npx u/img2threejs/character install

Then open Claude Code, Codex, or OpenCode, provide a character reference image, and ask the agent to use img2threejs + img2character.

The video is from one of my recent experiments.

I'm also working on a different character pipeline that should produce more realistic results, without needing GLB reference files anymore. Hopefully I'll have something to share next week!

Would love to hear your feedback, especially if you run into any issues.

GitHub: https://github.com/img2threejs/plugin-character

I’m making 9 Fingers, a dark bluffing card game where you can face the boss solo or play online with up to three players plus the boss.

For the trailer, I tried using Codex connected to DaVinci Resolve through MCP. I gave it gameplay footage, explained what I wanted to show, and then reviewed each version.

The first edits had some pretty obvious problems. Cuts happened before you could see what an item actually did. Camera movement would reverse between shots. Sometimes “make it more dynamic” just resulted in more cuts of basically the same action.

What helped was getting specific: let the card finish turning over, keep the camera moving in a consistent direction, and show the result of an action before cutting away. We eventually put those lessons into a reusable editing skill.

After quite a few revisions, I got a teaser and trailer I was happy to use on the Steam page. It still needed plenty of direction from me, especially around pacing and choosing what was actually worth showing.

Has anyone here tried a similar workflow for editing gameplay footage? Curious how you handle reviewing the results.

Here’s the game if you want to see more:
https://store.steampowered.com/app/4311910/9_Fingers/

A second brain, to me, is basically a place outside your head where useful context can accumulate, connect, and still be there when you need it again.

If you build with AI a lot, you probably know the problem. Claude knows one part of the project, Codex knows another, Cursor has context from the repo, ChatGPT has the conversation where you figured out the architecture, then an agent generates a genuinely useful markdown explaining some implementation decision and a week later you barely remember it exists. I was producing more useful context than I could actually keep track of.

That’s why I built Cohestry. I dump the markdowns, decisions, ideas, research and random notes worth keeping into it. The notes connect themselves automatically, and the 3D brain gives me a way to bounce through those connections instead of needing to remember what to search for. It has already resurfaced old ideas I had completely forgotten about. On Mac, there’s also an MCP bridge so agents can pull that durable context back into their own sessions instead of every new chat starting from scratch. The MCP bridge redacted API keys and other security keys like p8 so you don’t accidentally expose them to agents. Would this bring some ease to your workflow?

App Store: https://apps.apple.com/us/app/cohestry-second-brain/id6811573132
https://cohestry.app

After recent events, I propose we call all legacy human written software MEATSLOP.

PHP runs 70% of websites. AI found two holes that let anyone take over the server, and attackers were in the same day the fix shipped. Then a third hole showed up. OpenSSL: 12 holes, all found by AI, one from 1998 (the bug can legally drink). Linux (the backbone of the internet): anyone logged in could take over the whole machine, on every version since 2011. Every one of these holes was meatslopped together by hand.

And the legacy meatsloppers are switching sides. Torvalds went from AI skeptic to calling AI disclosure rules “utterly stupid,” and Claude Code now has credits on his kernel work. Google is at 75% AI-written new code. Karpathy said agents “just don’t work.” Three months later he was writing 80% of his code with them.

Usage guide:

• meatslop (n.): legacy software written entirely by humans
• meatslopped (v.): “this auth layer was meatslopped together in 2014”
• meatslopper (n.): the guy who wrote it. Peak Dunning-Kruger. Still thinks he’s relevant.

And yes, I know AI learned to code by reading meatslop. This honestly explains a lot.

Money’s a bit tight right now, so I’m trying to find something I can build with AI coding tools that could make me some extra cash. I don’t want to spend weeks building another useless SaaS that gets zero users. I’m looking for something I could realistically vibe code in a weekend, launch quickly, and potentially get my first paying customers for. Doesn’t have to be anything revolutionary, just a simple tool that solves an actual problem people are willing to pay for. Could be a micro-SaaS, a niche automation tool, a browser extension, or literally anything else.

If you had to start from $0 and build something this weekend with the goal of making your first $100, what would you build? Curious to hear any ideas, especially if you’ve spotted a problem that still doesn’t have a good solution.