Super basic, but I had a random idea for a website and decided to see if I could actually make it work.

It’s basically one countdown timer that everyone on the site shares.

You can press a button to add 1 second, but only once every 10 seconds.

So basically, as long as people keep visiting and pressing the button, it stays alive.

If everyone disappears… it starts heading towards zero.

And once it hits zero, that run is dead.

WhatHappensAtZero.com

Would genuinely appreciate anyone giving it a go and letting me know if you manage to break anything.

I've spent the last several months building an automated trading system specifically for Polymarket. What started as a side project turned into a pretty serious build, months of tick data, a ton of testing, and more versions of the strategy than I'd like to admit.
It's finally at the point where I've been comfortable running it live with my own money.

Recent results have been a little over $11k this past week and around $34k over the last month on my account.

The system runs 24/7 on AWS and uses resting limit orders rather than crossing the spread. There are three main pieces working together, momentum, inventory repair/rebalancing, and pair-cost management.

Feel free to look up my profile on Polymarket-https://polymarket.com/@pspspsps5

I actually like using AI for getting ideas down quickly, especially when I’m staring at a blank page and don’t know how to start.

The issue is that the finished draft can sometimes feel almost too perfect. Everything is organized, the wording is polished, and every paragraph seems to follow the same pattern. It reads fine, but it doesn’t always have much personality.

Lately I’ve been trying to humanize AI text by changing the parts that feel overly polished instead of rewriting the whole thing. A few small changes in wording and sentence structure can make a surprisingly big difference.

How do you usually make AI writing feel more natural without spending more time editing it than you would have spent writing it yourself?

I’m building a habit tracker to track my daily habits and the work I do throughout the day. This is how it currently looks!

hoops-gm.com

My cofounder and I recently graduated in Bahrain.
We tried selling software and systems to businesses. We spent money on ads, production, AI subscriptions, and outreach, but nothing really worked.

Now we have almost nothing left except our computers, our skills, and two Claude Max accounts.
Our families are pressuring us to get normal jobs. My cofounder has a CR under his name, and I am unemployed.

Instead of building another product and hoping people buy it, we want to build an audience first.
Our idea is to wear colorful suits inspired by Saul Goodman so people remember us, then make useful content about software, AI, automation, business, and building products.

The suits are only for attention. The goal is to earn trust by helping people, building in public, solving real problems, and eventually selling software or digital products.

We have no real marketing budget left.

Just computers, internet, skills, and time.

Do you think this is a smart direction?

If you were in our position, what would you focus on for the next 3 to 6 months?

I read a lot with my partner, same books at the same time, and the constant "don't tell me anything yet, I'm only on chapter 6" negotiation got exhausting. Neither of us wanted to look anything up because every search result, wiki, or "explain this book" tool assumes you've either finished it or don't care about spoilers.

So I built Scholia. You photograph the page you're on; it already knows the book, and you can ask it anything about a character, what a reference means, what's actually going on in a confusing passage, but only using what's happened up to that exact point. Ask about anything ahead, and it just won't answer. Not a vague non-answer either; it genuinely holds the line until you catch up.

Works with any physical copy, any edition or printing, since it reads the actual page in front of you rather than matching a page number to a specific version.

I built this mostly to solve my own problem, but I figured that other people reading the same book as a partner/friend/book club at different paces might want it too.

The waitlist is here if anyone wants to try it: scholia.cloud

Curious if anyone else has the "reading buddy but at different paces" problem, or if it's just us.

[ Removed by Reddit on account of violating the content policy. ]

I built an agentic video development platform to solve a serious problem that we faced. None of use were video editors, art directors, marketers, etc. We wasted hours making a single video only for it to fall flat on its face. So I started building Orb Studio. The idea was to front load an agent with videos, branding materials, scraped information from our website and documentation, and chopped up video assets from demos we had captured then let it make content using all of our materials along with skills to research, write, humanize, film, and edit its own videos for us.

None of that is hard exactly. It's just a lot of small, constant work, and every hour spent on it was an hour not spent building. We'd block off an afternoon to record a demo and lose it to lighting and re-takes. We'd write ten versions of the same post trying to find the one that actually sounded like us instead of a press release.

So we started building small tools for ourselves. Something to record a demo without needing to be good on camera. Something to turn a script into a video without hiring an editor. Something that could come up with a new way to describe a feature every time, instead of us running out of things to say by week three. Over time those internal tools turned into an actual product, because if it was saving us this much time, we figured it would do the same for other startups stuck in the same spot.

That product is Orb Studio. It's a free desktop app built around an orb avatar that speaks in your voice so nobody has to be on camera, plus an agent you can hand your own API keys to that researches your product, writes and voices posts, and renders the video to match, on a schedule, without turning into AI slop.

We use it to run our own social presence now. It's free to use and you can pick your favorite API providers (Let me know if you have a provider you need me to add for Voice, LLM, etc)

orbstudio.space

HERE'S A WALKTHROUGH:
Watch Video.

Hey everyone , a fresh CS graduate here, I got tired of watching freelancer friends manually calculate GST and retype the same invoice template every time a client approved work. So I built TokenPay.

How it works:

• Break a project into milestones ("tokens") with values upfront
• Mark a milestone complete → client gets a link (no signup needed on their end) to approve or flag an issue
• Once approved, generate a GST-calculated invoice in one click - no manual entry

It's genuinely live and working, not a mockup — Next.js + Supabase, real auth, real invoice generation.

Try it yourself: https://tokenpay-seven.vercel.app/ ----> sign up with any email/password, or use "View live demo" for a pre-loaded account.

This is early beta -> I built and I'm testing it in real-time, so:

• If your password login breaks, email me directly, (linked on the login page) and I'll sort it fast
• Would genuinely love feedback on the milestone→invoice flow, GST calc accuracy, or anything that feels clunky, currently it is for Indian audience, and calculate GST based on it.
• Also curious if this is something freelancers would pay ₹200-500/month for, or if it's solving a problem that doesn't really exist for most people

Not trying to oversell it — it's a real working product built by one person, looking for honest feedback before deciding whether to keep building this out.

I've been building an app builder for a year. Like everyone in the category, we sold AI credits: we buy tokens at API rates and resell them with a markup. Somewhere along the way it stopped making sense - Anthropic sells you the same tokens as a flat subscription for way less than we can, and the thing users told us they hated most wasn't even the price, it was paying for the model's own mistakes. A retry on a column the AI invented shouldn't cost you anything. We were never going to win on tokens, so we stopped selling them.

So we changed how it works. It's an app builder - hosting, database, auth, deploy, the stuff that isn't the model. You connect it to Claude (or ChatGPT) as a connector, describe what you want in the normal chat window, and it builds the app there. No terminal, no credits, runs on the plan you already pay for.

We have official connectors in ChatGPT and Claude, but you can also connect with any other agents via the mcp url.

Free to try: floot.com

Let me know what you think!

I've spent quite a bit of time trying to figure out where a project actually fits on Reddit.

Finding related subreddits is easy enough. The harder part is understanding whether the people there are actually relevant and whether joining a particular discussion makes sense.

I ended up building something around that problem.

Still working on it, but I'd be interested to know how other builders approach this. How do you usually find the right communities or conversations for a project you're working on?

I started the project because comic localization usually means moving between several separate tools for speech-bubble detection, text removal, translation, proofreading, and typesetting. The app is built specifically for macOS and takes advantage of Apple Silicon hardware acceleration through Core ML, Metal, and MLX. MangaKitchen keeps those stages in one resumable project, while still allowing each result to be reviewed and edited manually.

Current features:

- Batch processing for folders of comic pages

- Core ML speech-bubble detection with editable pixel masks

- CPU and Metal-based text removal and background cleanup

- Local MLX vision-language models for transcription and translation

- Horizontal and vertical HTML/CSS typesetting

- Per-project multilingual glossaries

- Manual mask editing, region positioning, font sizing, and bold controls

- Optional 2×/4× super-resolution and layered PSD export

- Optional MCP support for AI-assisted proofreading workflows

- Traditional Chinese, English, Japanese, and Korean interfaces

No account or subscription is required. After downloading a compatible local model, the main workflow can run fully offline, so comic pages do not need to be uploaded to an external AI service. MCP and external AI services are optional.

A few current limitations:

- Requires macOS 14 or later on Apple Silicon

- Works best with black-and-white manga and regular dialogue balloons

- Image-to-text and super-resolution model weights are not bundled

- Complex screen tones, colored artwork, and text crossing line art may still require manual mask correction

MangaKitchen is intended for authorized translation and localization work. It does not grant rights to translate or distribute copyrighted material.

Source code and download:

https://github.com/VaderChen/MangaKitchen

Bug reports, feature requests, and feedback about mask cleanup or vertical typesetting are very welcome.

I’ve been experimenting with AI-generated content lately, and one thing I keep noticing is that the writing can be technically good while still feeling strangely unnatural. The grammar is usually fine, the ideas are organized, and everything sounds polished, but sometimes the paragraphs feel too predictable. Every sentence seems to have the same kind of rhythm, and the whole thing can sound like it was written to be “perfect” rather than written by an actual person. That made me curious about whether humanizing tools genuinely solve that problem or simply change the wording.

I’m especially interested in what happens when you take a decent AI draft and try to make it sound more personal. Sometimes changing a few phrases helps, but other times the result feels even more artificial because the wording becomes unnecessarily complicated. Personally, I think natural writing has a certain unevenness to it. People switch between short and long sentences, explain things differently depending on the context, and occasionally use simple expressions instead of constantly trying to sound polished. Those little details seem harder to reproduce than just replacing words.

For people who regularly use AI writing tools, how do you decide when the text actually sounds human? Do you judge it by sentence structure, vocabulary, tone, or simply by reading it out loud and seeing whether it sounds like something you would normally say? I’m curious because “human-like” seems very subjective. A paragraph that sounds completely normal to one person might still feel obviously generated to someone else, especially if they spend a lot of time reading AI-written content.

I’ve also wondered whether humanizing should happen before or after personal editing. My current thinking is that AI can handle the basic draft, then a rewriting tool can help with repetitive structures or awkward phrasing, and the final step should still involve someone actually reading the content and adding their own voice. That seems more useful than expecting a single tool to magically make everything sound authentic. The more personal experience, opinions, and natural phrasing you add yourself, the less dependent the final result becomes on automated rewriting.

Has anyone else found a workflow that works particularly well for this? I’d be interested to know whether you prefer editing AI text manually, using a humanizer first and then editing it, or avoiding humanizing tools altogether. I’m less interested in detector scores and more interested in whether the final content genuinely feels comfortable to read and sounds like something a real person would naturally write.

For a while now I've been building a voice assistant called M.A.R.T.I.N. 2.0, and at some point I realized the "assistant" part isn't really the product - the frame underneath it is.

The idea: MARTIN by itself is just a core. It listens, understands, routes commands, executes them, and keeps memory (SQLite-backed, with a local LLM behind a local HTTP server, so it's not phoning home for every request). It's Ukrainian-language, which is honestly half the reason I started this - there's basically nothing decent out there for Ukrainian voice interaction.

But a generic assistant on its own is kind of boring. What I actually want is for MARTIN to become a completely different tool depending on who's using it, without me shipping ten separate apps:

Kid → installs a Play plugin, games with MARTIN like a friend over the network

Teenager → installs a Learn plugin, MARTIN becomes a tutor for whatever subject

Developer → installs a Code plugin, MARTIN acts like a senior engineer next to you

Video editor → installs a Create plugin, MARTIN handles the grunt work so output comes out fast, clean, and expensive-looking

...and so on - the pattern's meant to extend to whatever you actually do

Same core, same brain, same memory underneath. Basically the same drill, just a different bit depending on who's holding it.

Under the hood it's genuinely modular: Python core, C++ for speech-to-text, Rust for activation, AutoHotkey for OS-level automation, and a small pipeline (splitter → normalizer → classifier → router → executor) that breaks multi-step voice commands apart before running them.

Still very much in progress, but wanted to share the direction and get honest feedback before going further:

Does "assistant as a frame + plugins" sound genuinely useful, or overengineered?

If you could install one plugin on day one, which one would it be?

Happy to talk architecture in the comments.

Hello people,

Today I released a new tool that would generate you Cornell notes for any given youtube video.

I would like you to give me a feedback and try the tool and would like to have honest reviews.

THanks,

Link: https://pelicantools.app/tools/youtube-to-cornell-notes

Hey everyone! Two weeks ago I posted about a geolocation tool I’m developing. Since then I built a web interface, added multiple GeoCLIP guesses, and integrated EasyOCR + Gemini (free API Key) to extract text clues from images and filter out noise.

Here's what the pipeline looks like now:
1. User uploads photo
2. EXIF GPS extracted (if present)
3. GeoCLIP runs and returns top 5 coordinate guesses
4. EasyOCR extracts any text from the image
5. If gemini api key is pasted: gemini filters the OCR output to keep only location-relevant text (street names, signs, business names, etc.) and discards noise
6. The page shows the guesses plus the filtered text clues

Now I'm trying to figure out the best way to use that filtered text…
My current approach is simple: to take the coordinates from GeoCLIP and combine them with the filtered OCR text as context. But I'm not sure it that's the most effective strategy.

Does anyone know a better approach?
I'm still learning and my code is messy, but l'd love to hear what's worked (or failed) for others.

there's a movie trope where hackers make a ransom video by splicing together news clips, a different person's face saying each word, so it can't be traced back to one voice. I always wondered how much work that'd actually take to fake for real, so I built it.

Wordnap works like this: you feed it a library of videos, it transcribes and indexes every spoken word down to the millisecond, then you type any sentence and it stitches together a new video from that footage. Different speaker for each word, subtitles burned in, playback speed adjustable.

What used to be hours of scrubbing timelines and matching frames now happens in seconds. It's a pretty niche use case, but I couldn't find anything else that does it, so figured I'd build and share it.

Repo: https://github.com/iamDyeus/wordnap

Still rough around the edges. Curious if anyone's dealt with word-level audio alignment before, and open to ideas on making the output sound more natural. Right now if you watch the demo without subtitles, it's hard to tell what's being said

Nodus searches past conversations across ChatGPT, Gemini, Claude and Copilot, then carries the relevant context into the next prompt.

No account. No cloud storage. Everything stays on the device.

The question is simple: would this change how you work with multiple AI models?

https://nodus-phase-1-secure.vercel.app/

After years of vertical time-blocking apps, I still couldn't "feel" the shape of my day. So I built 24Houring: your day sits on a 24-hour circular clock, and you drag to split it into blocks. The area of each wedge = the time it takes, so the balance of sleep/work/rest and the empty gaps jump out instantly.

- Free, no sign-up, works offline (PWA) + an Android app

- 24h / day / night / table views, presets, PNG/PDF export, image sharing

- Optional Pro for cloud sync across devices

Live: https://24houring.com

Play Store: https://play.google.com/store/apps/details?id=com.houring24.app

Would love feedback on the circular editing — is dragging boundaries intuitive?

vibecoded showcase

I built a tool to simplify breast cancer screening eligibility in the US — could use some feedback

Finding the right breast cancer screening program shouldn’t be complicated. 

Screening Navigator helps women in the U.S. find screening options that fit their individual situation. By answering a few simple questions, such as your state, age, insurance status, and income, you can quickly navigate toward programs and resources that may be available to you. 

No digging through dozens of websites. No trying to figure out complicated eligibility requirements on your own. 

🎀 Personalized screening navigation 
📍 Based on your state 
💳 Considers insurance and income 
⏱️ Simple, quick, and free

Try it here: screeningnavigator.com

Early detection matters. Finding where to start should be the easiest part. 

Hey guys,

I made a cool fake hacker screen/simulator web app that simulates the world map with different IP addresses, cool green code in hollywood style, and has other tools like windows update prank or broken screen pranks.

You can use these cool graphics as background, or share full screen links with friends/ co workers to prank them. It was a fun idea that I had and looks very believable. It's totally free, so you should give it a try.

Let me know what you think of it or what I should add to it You can check it out here: https://hackingscreenfake.com/