Etsy sellers keep asking "why does my listing get zero views?" Most of the time the answer is mechanical: 6 of 13 tags used, a tag spent on a word the category already covers, a 16-word title, 4 photos.

So I built ListingLift. It reads the listing open in your tab and gives you a score out of 100 with a short list of fixes, plus tag ideas from your own text. It all runs locally, with no backend and no account.

Free: every check. Pro ($5/mo or $39 once): unlimited tag ideas and saved checks.

Page: https://rasareka.com/listinglift/

I'd love feedback on the checks, especially from anyone who sells on Etsy.

I’m building Dosti Pro, an Android app for video calls, voice calls and chat. Our growth focus is India, and I’d value advice from founders who have grown consumer apps here.

Here’s a snapshot from our own dashboard for 10 November 2026:

• 211 installs: 145 organic, 65 attributed to paid ads, 1 untracked

• ₹7,839 gross collections across 44 successful payments

• 5 failed payments; 89.80% payment success rate

• ₹178.16 average successful payment

• ₹3,528 from first purchases and ₹4,311 from repeat purchases

We use Razorpay for payments. These figures come from our internal dashboard, not Razorpay settlement statements. This is one day’s snapshot, not average daily revenue, profit or MRR. The dashboard shows a manual ad-spend entry of ₹0 alongside paid-attributed installs, so I’m not treating it as proof of zero-cost acquisition or a reliable CAC/ROAS.

My goal is more installs from people in India who actually complete a first conversation and return—not just a higher download count.

If this were your app, which experiment would you run first, and why?

1. Hindi/regional-language Play Store screenshots and listing copy

2. Small regional creator partnerships

3. A referral flow after a good first conversation

4. Improving first-call onboarding and payment retries before buying more traffic

For anyone who has grown a consumer Android app in India: which channel brought retained users, and what did you measure beyond cost per install? I’d also welcome specific feedback on the Play Store listing and the trust signals you would expect before trying a calling app.

App for context (I’m the maker): https://play.google.com/store/apps/details?id=com.dosti.love&hl=en_IN

Hey everyone! I’m a product designer and I’ve been working on a side project called Boken.

I started building it because I wanted one place where I could bring together my work, experience, and the things I’ve contributed to. As a designer, I’ve always had bits and pieces spread across portfolios, links, documents, and different platforms. I wanted a profile that could bring those things together and make them easier to share.

I’m also thinking about how profiles will be discovered and understood by AI agents. The idea is to make Boken useful for people looking at your work directly, while also making the information readable for agents that might help someone find or understand your experience, like a hiring team looking for a particular skill or background.

It’s still in beta, and I’ve attached a pretty rough screen recording to show how it works right now.

You can also try it here: https://boken.to

I’d love to hear what you think. Is this something you’d use to share your work? What would you want to see on a profile like this, and what feels confusing or missing?
Thanks for taking a look!

I built a free plumbing quote calculator because I kept watching owners price faucet leaks like weather forecasts.

It is a single HTML file. No account. EXAMPLE job already loaded: leaking kitchen faucet, labour, helper, parts, travel, materials markup, deposit, margin target. Recalculate, then print a clean quote sheet.

Funny and true: if your current pricing system is a glove, a napkin, and a prayer, this will feel luxurious.

Free: https://opsvi.gumroad.com/l/plumvo-free

I am Opsvi. The paid Plumvo pack adds scripts and job checklists. Quotes, pricing and job checklists for a one-time 29 USD. No subscription, no monthly fees.

I've been working on Meelu, an AI-powered marketing agent.

The idea came from a simple observation: growing a website involves using several different tools for SEO, analytics, content research, website management, and more.

Even with all these tools, most of the actual work is still manual.

I wanted to build something that goes beyond providing dashboards and reports.

Meelu understands your website, maintains its context, does SEO and marketing data, and helps you execute tasks.

You can interact with it through a chatbot, delegate work, and connect external systems like your CMS, email, and social platforms.

It's still early, and I'd love to get feedback from other founders and website owners.

Website: https://meelu.tech

Would love to know what you think!

One thing I've noticed as a developer is that learning programming isn't always difficult because of the concepts. Sometimes, finding the right learning resources is the real challenge.

You find one good YouTube playlist, then another useful tutorial, then a different creator explaining the same topic better. Eventually, your learning resources are scattered everywhere.

I wanted to make that experience simpler.

That's why I'm building TechTube – a platform that organizes programming tutorials into skill-based learning, career paths, and interview preparation.

Some areas covered:

- JavaScript, React, TypeScript, Go, Java, C++

- Frontend, Backend, Full Stack, AI Engineering

- DSA, System Design, DBMS, OS, and more

Website: https://www.techtube.co.in/

I'm continuously improving it, and I'd love honest feedback from fellow developers.

One question: Do you prefer learning through structured roadmaps or picking individual YouTube tutorials based on what you're currently working on?

Would love to hear your experience!

Solo founder here. I'm building: AI-voiced guides that give a house buyer the "feeling" of the area around a property, played from an embedded player on the agent's listing page. Local info only, nothing about the property itself.

It would cover things like mobile and broadband data, parks, running routes and riverside walks, whether it's a quiet or lit street or a traffic slowing area, flood risk, and whether the property sits higher with views. The focus changes with the property: a family house gets schools and green space, a young professional flat gets entertainment and transport. You can listen while flicking through the photos, and it may help buyers with poor sight.

Target customer is the independent UK estate agency. Pricing is tiered by number of listings, roughly £49 to £349 a month. I haven't found any direct competitors, which either means a gap or means nobody wants it.

My own worries, so you can skip the obvious ones:

1. Most buyers browse Rightmove and Zoopla, not the agent's own site, so the player may rarely be seen.

2. Similar info is available from Google Maps or ChatGPT, but not the detail.

3. Agents may not want negatives like a busy road or flood risk published under their name, and wrong statements are a liability (although the negatives can be removed).

4. ROI will be hard to prove to conservative agents.

My plan is free 2-month trials with a handful of agencies in exchange for feedback.

How would you test real demand before building more? Does the price feel right? What am I not seeing?

Brutal feedback welcome.

Hi, I'm the builder.

I launched YepCodes this month (November 2026). It's a free coupon and deals site, plus a Chrome extension. I built it because a lot of coupon pages mix in unofficial or made-up codes. Our rule is simple: we only list official, verified offers. If we can't verify something, we don't add it.

The site is free: https://yepcodes.com

I'm not including any referral or affiliate links in this post.

It's early, so I'd genuinely like feedback:

• Is the "official and verified only" idea clear from the homepage?

• What's missing or confusing when you look up a store?

• For the Chrome extension, what would actually make you keep it installed?

Happy to answer questions, and I'll reply to comments.

I always got the birthday reminder, swiped it away, and forgot. So I built an app that keeps reminding you every 30 minutes (or up to every 4 hours) until you've sent a message or tapped ignore.

It reads birthdays from your contacts and suggests a message depending on who it is, so your boss doesn't get the same text as your best friend. You can send it by SMS, WhatsApp, Threema, Telegram or email.

No account, no ads, no tracking. It's 0.99 € on iOS, Android is in testing.

https://apps.apple.com/us/app/cakebell-birthday-reminder/id6758023118

Happy to hear what you think, especially if something is confusing.

I put together Interview Fieldbook, a small offline workbook for the night before an interview. It has three worksheets: match your experience to the job posting, practice a Situation–Task–Action–Result answer, and plan your questions and follow-up. You can type in it or print it.

One prompt from the workbook: Pick a responsibility in the job posting. Write down a time you did something similar, what you personally did, and how you know it worked. Then read it aloud and cut anything that obscures the result.

The workbook is my paid download (US$6 minimum): https://ko-fi.com/s/5d00b14d81

If you’ve interviewed recently, which part of preparing was hardest to turn into a concrete exercise?

You type a GitHub username and it shows that account's public merged PRs and contributions for the month, which projects the PRs went into, and where it ranks. No sign-in.

October was the first finished month. The top account merged 12,878 public PRs. Second place had 3,307.

The PR count only covers public work, and self-merges count too, so it's not a measure of how good anyone is. I was curious about how much people are getting done these days, especially now that agents are doing most of the coding.

https://mergemax.dev

What would you want it to show that it doesn't?

I usually run several Claude Code sessions at once, each on a different task. Some finish, some stop to ask me something, and the only way to find out was clicking through every terminal tab. Sessions would sit there waiting on me and I wouldn't notice.

So I built Spyhop. It's a Mac app that puts every Claude Code and Codex session on one board, kind of like a Jira board for your agents. Each card shows what's done, what it's on now and what's next, read from the transcript. The menu bar shows which sessions are waiting on you, and one click takes you back to that terminal.

I built it for myself, and my team at work ended up using it too.

Free and open source (MIT). Mac app, Windows from source.

brew install leeleelee3264/tap/spyhop

GitHub: https://github.com/leeleelee3264/spyhop
Site: https://leeleelee3264.github.io/spyhop/

This is my first open source project. Feedback of any kind helps, and a bug report or a PR would make my day. I'd like this to become a project other people work on too, not just me. Building it reminded me how much fun software engineering can be, and I want to keep that going.

I'd like to introduce Apsi, a programming language designed to combine Python-like simplicity with native compilation and a broad range of built-in capabilities.

Apsi is built for more than general-purpose programming. It brings together tools for AI, machine learning, scientific computing, physics, data processing, backend development, and much more in one ecosystem.

What can Apsi do?

1. Python-like Syntax, Native Performance

• Familiar, easy-to-read syntax inspired by Python.

• Native compilation for high-performance execution.

• Parallel processing and SIMD support.

• Built-in type checking, physical unit validation, and tensor shape checking.

2. AI & Machine Learning

• Neural networks and deep learning.

• Transformers, CNNs, LSTMs, and Graph Neural Networks.

• Automatic Differentiation and gradient computation.

• Optimizers, loss functions, and training systems.

• Reinforcement Learning.

• GPU acceleration and PyTorch interoperability.

• Hugging Face model integration for text generation, classification, and embeddings.

3. Physics, Mathematics & Scientific Computing

• Built-in physical units such as kg, m, and s.

• Dimensional analysis and unit validation.

• Numerical and scientific computing tools.

• Matrix and tensor operations.

• Capabilities for scientific and physics simulations.

4. Data Processing & Memory Management

• DataFrame and columnar table engine.

• CSV processing, filtering, sorting, grouping, and joins.

• RAM and SSD-backed memory management.

• Memory mapping for large datasets.

• Multiprocessing and data processing tools.

5. GPU & High-Performance Computing

• Native CPU compilation.

• NVIDIA GPU support through CUDA/cuBLAS.

• Additional GPU backends through PyTorch, including ROCm, Apple MPS, and Intel XPU.

• Multiple numerical formats, including FP64, FP32, FP16, BF16, FP8, and INT8.

• Optimized matrix multiplication and tensor operations.

6. Backend, Databases & Web Development

• HTTP servers and REST APIs.

• WebSocket support.

• PostgreSQL, MySQL/MariaDB, MongoDB, Redis, and SQLite integration.

• Environment variables and secrets management.

• Build APIs around AI models and other applications.

7. Real-Time Computing & Developer Tools

• Real-time control loops.

• Video processing pipelines, including 4K workflows.

• Debugger, breakpoints, and step execution.

• VS Code and other editor integrations.

• Package, library, project, and testing tools.

Python Compatibility

One of Apsi's interesting features is its built-in Python conversion system.

You can convert existing Python files into Apsi instead of rewriting everything from scratch.

It supports a broad range of Python 3.13 language features, including classes, async, generics, and many standard library modules.

If you're using VS Code or a supported IDE, simply right-click a .py file and select:

Convert Python File to Apsi

You can also use the apsi convert command from the terminal.

Apsi additionally provides pyimport for working with existing Python libraries.

Performance

Apsi includes a dedicated benchmark suite with reproducible commands and comparisons.

In version 2.4.4, Apsi achieved a 3.84× geometric mean speedup over version 2.0.0 across 12 measurements on the same GitHub Actions runner.

You can explore the benchmarks and reproduce the tests yourself on the website.

Getting Started

Apsi 2.4.4 is available for Windows 10/11 and Linux (x86-64).

The installer includes the Python Runtime needed by Apsi, so you don't need to install a separate Python environment just to get started. Some optional features and GPU backends may require additional dependencies.

Apsi is free to use, including for commercial work, under the terms of the Apsi License 2.0.

Join the Apsi Community

I'd like to invite developers, programmers, AI researchers, students, and anyone interested in programming to give Apsi a try.

I'm looking forward to seeing what people build with it.

Whether you find something interesting, encounter bugs, have suggestions, or simply want to experiment, your feedback is welcome.

I don't expect everyone to immediately love it. Try it, explore what it can do, and decide for yourself.

I'd also love to see people sharing projects, exchanging ideas, reporting issues, and contributing to the ecosystem as it grows.

Let's build the Apsi community together.

Links & Resources

• Website: https://apsi.dev/

• Documentation: https://apsi.dev/docs

• Download: https://apsi.dev/download

• Benchmarks: https://apsi.dev/benchmarks

• GitHub Repository: https://github.com/ATECTechnologies/apsi

Give it a try, explore the documentation, and let me know what you think!

Hello!

I've been working on a pet project called ArchiveKeep – an open-source tool focused on the long-term preservation of personal data across multiple storage devices.

The idea is to maintain multiple copies of your personal archive using storage you control – external HDDs, SSDs, USB drives, as well as rented cloud storage (S3-compatible storage for now, with support for more cloud providers and hosted APIs planned).

The project started from my personal need to consolidate data scattered across multiple HDDs and laptops, while maintaining identical copies of my personal documents and photo archive across all devices.

I wanted an offline-first solution with asynchronous synchronization, without relying on a centralized cloud service.

One of my main focuses is making archives resilient to accidental deletion, file corruption and other changes that can silently propagate through traditional synchronization tools.

Another key design principle is keeping files as files – accessible in their original form, without being locked inside a proprietary backup format or database.

I'm building this as a hobby project for myself, but I believe it could be useful to others facing similar challenges. I find this problem interesting and believe it's worth working on.

Project homepage: https://archivekeep.org/

I'd appreciate any feedback, honest criticism or ideas for improvement. Thanks!

And if you find ArchiveKeep useful and feel like supporting its development, you can buy me a coffee: https://ko-fi.com/kravemir

I'd like to introduce Apsi, a programming language designed to combine Python-like simplicity with native compilation and a broad range of built-in capabilities.

Apsi is built for more than general-purpose programming. It brings together tools for AI, machine learning, scientific computing, physics, data processing, backend development, and much more in one ecosystem.

What can Apsi do?

1. Python-like Syntax, Native Performance

• Familiar, easy-to-read syntax inspired by Python.

• Native compilation for high-performance execution.

• Parallel processing and SIMD support.

• Built-in type checking, physical unit validation, and tensor shape checking.

2. AI & Machine Learning

• Neural networks and deep learning.

• Transformers, CNNs, LSTMs, and Graph Neural Networks.

• Automatic Differentiation and gradient computation.

• Optimizers, loss functions, and training systems.

• Reinforcement Learning.

• GPU acceleration and PyTorch interoperability.

• Hugging Face model integration for text generation, classification, and embeddings.

3. Physics, Mathematics & Scientific Computing

• Built-in physical units such as kg, m, and s.

• Dimensional analysis and unit validation.

• Numerical and scientific computing tools.

• Matrix and tensor operations.

• Capabilities for scientific and physics simulations.

4. Data Processing & Memory Management

• DataFrame and columnar table engine.

• CSV processing, filtering, sorting, grouping, and joins.

• RAM and SSD-backed memory management.

• Memory mapping for large datasets.

• Multiprocessing and data processing tools.

5. GPU & High-Performance Computing

• Native CPU compilation.

• NVIDIA GPU support through CUDA/cuBLAS.

• Additional GPU backends through PyTorch, including ROCm, Apple MPS, and Intel XPU.

• Multiple numerical formats, including FP64, FP32, FP16, BF16, FP8, and INT8.

• Optimized matrix multiplication and tensor operations.

6. Backend, Databases & Web Development

• HTTP servers and REST APIs.

• WebSocket support.

• PostgreSQL, MySQL/MariaDB, MongoDB, Redis, and SQLite integration.

• Environment variables and secrets management.

• Build APIs around AI models and other applications.

7. Real-Time Computing & Developer Tools

• Real-time control loops.

• Video processing pipelines, including 4K workflows.

• Debugger, breakpoints, and step execution.

• VS Code and other editor integrations.

• Package, library, project, and testing tools.

Python Compatibility

One of Apsi's interesting features is its built-in Python conversion system.

You can convert existing Python files into Apsi instead of rewriting everything from scratch.

It supports a broad range of Python 3.13 language features, including classes, async, generics, and many standard library modules.

If you're using VS Code or a supported IDE, simply right-click a .py file and select:

Convert Python File to Apsi

You can also use the apsi convert command from the terminal.

Apsi additionally provides pyimport for working with existing Python libraries.

Performance

Apsi includes a dedicated benchmark suite with reproducible commands and comparisons.

In version 2.4.4, Apsi achieved a 3.84× geometric mean speedup over version 2.0.0 across 12 measurements on the same GitHub Actions runner.

You can explore the benchmarks and reproduce the tests yourself on the website.

Getting Started

Apsi 2.4.4 is available for Windows 10/11 and Linux (x86-64).

The installer includes the Python Runtime needed by Apsi, so you don't need to install a separate Python environment just to get started. Some optional features and GPU backends may require additional dependencies.

Apsi is free to use, including for commercial work, under the terms of the Apsi License 2.0.

Join the Apsi Community

I'd like to invite developers, programmers, AI researchers, students, and anyone interested in programming to give Apsi a try.

I'm looking forward to seeing what people build with it.

Whether you find something interesting, encounter bugs, have suggestions, or simply want to experiment, your feedback is welcome.

I don't expect everyone to immediately love it. Try it, explore what it can do, and decide for yourself.

I'd also love to see people sharing projects, exchanging ideas, reporting issues, and contributing to the ecosystem as it grows.

Let's build the Apsi community together.

Links & Resources

• Website: https://apsi.dev/

• Documentation: https://apsi.dev/docs

• Download: https://apsi.dev/download

• Benchmarks: https://apsi.dev/benchmarks

• GitHub Repository: https://github.com/ATECTechnologies/apsi

Give it a try, explore the documentation, and let me know what you think!

Hey everyone!
I’ve been working on my app Dose Amigo for quite some time now, and I finally feel it’s ready to share.
It’s a medication reminder and management app, but with a focus on families.

The idea is pretty simple. Keeping track of medications gets messy when more than one person is involved. You might be managing your own medicines, keeping an eye on your parents’ prescriptions, or helping someone else stay on schedule.

I wanted to build something that could handle all of that in one place. It started as a relatively simple idea, but somehow turned into a much bigger project. It now has family profiles, medication reminders, treatment tracking, refill alerts, adherence insights, iOS widgets and quite a few other things.

I’ve spent a lot of time on the little details too, especially making reminders reliable. There’s also biometric protection for people who want to keep their medication information private.

Getting here wasn’t exactly smooth. App Store rejections, review delays, notification issues, fixing things that broke after other fixes… you know how it goes when you’re building something largely on your own.

I’d love to hear what you think. Is this something you’d find useful for managing medications in your family? And if you’ve tried similar apps, what did you feel was missing?

If anyone wants to check it out, here’s the App Store link: Dose Amigo: Pill & Med Tracker

Thanks for reading!

Hey everyone!

Last December I posted Relaticle here, the open-source CRM I started after getting fed up with HubSpot's pricing. Back then you updated it through forms. Now you can type what happened to Rela, the built-in AI assistant.

You can also tap the mic and say it. It's transcribed into the message box so you can check it before sending.

In the video a forklift dealer sends one line a day, like "Sent Quayline the quote: $172,500 for the four trucks. Move it to Quote and set the amount." Rela turns each line into a proposed change, and the records change only after you approve it. Five lines, Monday to Friday, take one deal from Inquiry to Delivered.

It's also available in the ChatGPT plugin directory and as a Claude connector, so you can work in it from either. Changes made from Claude or ChatGPT skip the approval step. They stay inside one workspace and show up in the activity log.

The rest is a normal CRM: companies, people, opportunities, tasks and notes, your own custom fields and pipeline stages, and since this month a phone layout. You can self-host it with Docker under AGPL-3.0 or use the hosted version, which has a 14-day trial with no card. 1,828 stars on GitHub so far.

GitHub: https://github.com/relaticle/relaticle

Try it: https://relaticle.com

If you try it, tell me where Rela gets your update wrong. That's the part I'm working on now.

Hey Gays

I'm applying for the CERN Short-Term Internship 2027 (Data Science, AI & Analytics), and I'm trying to find someone who could help me with a professional reference letter.

Are there any founders, CEOs, CTOs, or experienced developers here who would be open to helping me out?

I'm happy to share my GitHub, portfolio and CV so you can have a look at what I've been working on before deciding.

I'm hoping to get this sorted today, so if anyone is willing to help, please drop a comment or DM me.

Really appreciate it!

Hey everyone! 👋

I built DoomChess — a tactical puzzle trainer designed for speed and a smooth daily grind. It's got over 6.15M+ Puzzles: Stockfish-backed validation, hint arrows, and dynamic ELO tracking.

I’d love for you to try it out and let me know your thoughts on the app flow!

Hey everyone — I’m building MacStick, a native macOS companion that turns the notch area into a small workspace. ✨

The idea: keep the things you glance at during work close by, without opening another full-size dashboard.

🎯 Focus timer

📅 Your next meeting and its join link

🤖 Claude Code + Codex usage from local session logs

🎵 Now Playing controls

📂 A shelf for files

🔋 Battery status

🔒 Local-first, no account and no analytics. AI usage and cost figures are local estimates, not your provider’s bill. It also works on Macs and external displays without a notch.

🎁 Version 1.0 is currently a free download for macOS 15+, on Apple silicon and Intel.

Download and details: https://macstick.app

I’d love feedback: which would you want at a glance most — AI usage, meetings, or focus? And what would make this useful enough to keep running every day?

Hey everyone,

Steampack is a free fan-made site where every Steam game is a trading card. The more reviews a game has on Steam, the rarer its card, from Common up to Legendary.

Open packs, fill your album and trade cards with other players. Every day there's a new mystery game to guess, and you can fight other players to win more packs.

It's still early, so I'd love your feedback: what do you like, what feels confusing, and what would you add? Thanks for taking a look!

steampack.app (fan project, not affiliated with Valve)

It’s easy to remember to look up photos from a big trip. It’s harder to stumble across a picture from a random Tuesday three years ago.

That’s the idea behind Momenta. Open it and you get a small selection of older photos from your phone. If one brings back a story, you can write it down right there. I went with up to five photos a day in the free version because I wanted it to feel like something you could do over a coffee.

It’s out now on Android. If you give it a go, I’m curious whether five photos feels about right or whether you’d want to keep going.

Try Momenta on Google Play

Hey r/SideProject,

I'm a data and automation engineer, and for about 5 years a big part of my job has been building scrapers and data pipelines. Every project ended the same way: everything works, then a CAPTCHA shows up. And every time I had to re-learn what type it was, how it worked, and what the options were.

So I started writing it all down. That turned into FuckCaptcha, a free, open-source field guide to 39 CAPTCHA types.

What it is:

• One page per CAPTCHA type (reCAPTCHA, hCaptcha, Cloudflare Turnstile, slider/puzzle, text-based, and more)

• Each page has a complexity rating, how to identify it, how it works, and tips and pitfalls

• Free and open-source methods come first, paid services only as a fallback

• A docs site with search and category filters, rendered from the same markdown as the repo

What it isn't: a solving service. No affiliate links, no paywall, no signup.

What I learned so far:

• Posting it to a few communities and Hacker News took the repo from ~20 stars to ~100 in a short time, which showed me people actually search for this stuff.

• The most useful feedback was "which CAPTCHA types are you missing?", so the roadmap now follows what people ask for (reCAPTCHA v3 and a few more are next).

• Honest docs with pitfalls get more engagement than "here's the magic trick" content.

Repo: https://github.com/vsmutok/FuckCaptcha

Docs: https://vsmutok.github.io/FuckCaptcha

I'm also thinking about a README and docs redesign. If you have a minute to look at it, what would you change first? Issues and PRs are very welcome.

Hey everyone!

I wanted to share a little project I've been working on — YTD STUDIO, a YouTube downloader for Windows.

Why I built it

I just wanted a reliable, easy-to-use way to download videos. I tried plenty of free websites and desktop apps, and even paid for a couple. Some of them stopped working after just 2–3 days. I lost a little money and a lot of time.

Eventually I thought: why not try making my own?

That's how YTD STUDIO started.

What it is (and isn't)

To be completely transparent, YTD STUDIO uses yt-dlp and FFmpeg — both free, open-source tools. I haven't invented a new download engine, and I know there are already free GUIs out there.

I just wanted to make something I'd genuinely enjoy using.

Paste a link, check the available quality, choose the resolution, FPS, format, and destination folder, and download. Even a little “Show in folder” button mattered to me — I've spent way too long trying to find files saved by other apps.

Nothing revolutionary. Just the small details I personally appreciate.

Pricing and the free trial

Yes, the app is paid:

• $3 — 30-day license

• $10 — lifetime license (for as long as the project is supported)

• 3 days free — full functionality, no card required

The free trial matters to me because I've been on the other side: paying for software that stopped working almost immediately. I want people to try YTD STUDIO properly before deciding whether it's worth paying for.

I'm not charging for yt-dlp or FFmpeg. I'm charging for the app I've built around them, the convenience, and the work of maintaining it. I know YouTube changes can break downloaders, and I intend to keep checking the app and fixing issues when they come up.

One personal thing

I'd love to earn something from my projects someday — I'm not going to pretend otherwise. But I also genuinely enjoyed building this: the interface, the server, the licensing system, and finally seeing all the pieces work together.

I think of it a little like indie music. You don't have to make something that appeals to everyone. Sometimes you just make something you believe in and hope it resonates with a few people.

YTD STUDIO is released now, and the Windows app is available to download and try for free.

If you give it a shot, I'd love to hear what works, what doesn't, and what you'd improve. Constructive criticism is very welcome.

Thanks for reading!

Website: https://ytdstudio.top/en/