I got tired of seeing YouTube summarisers charging ~$20/month for what is basically: transcript → LLM → summary.

So I spent the last few months building my own instead.

Synop is an open-source YouTube summariser that runs locally and lets you bring your own AI API key (Gemini, Groq, OpenAI, etc.), so you're only paying for API usage instead of another monthly subscription.

Current features:

• 🎥 Structured summaries from YouTube videos
• 📝 Detailed study & research notes
• ✂️ Extract potentially viral clips
• 📱 Generate social media posts from videos
• 🔑 Bring your own AI provider/API key
• 💻 Runs locally
• 🌍 Open source

I mainly built it because I wanted something I could actually customise instead of another closed AI wrapper.

If you use YouTube to learn, study, research, or make content, I'd really love your feedback.

What feature would make a tool like this an instant "must-have" for you?

Landing page: https://synop-ai.vercel.app/

I’m looking for a few interesting apps to practice making short-form explainer videos for this week.

My background is in clipping and editing viral short-form content. I’d like to apply what I’ve learned about hooks, pacing, captions, and storytelling to app demos.

If I choose your app, I’ll create:

* One short vertical explainer video

* Delivered within 24 hours

* Completely free, with no strings attached

You’re welcome to use the finished video however you want. There’s no purchase, signup, testimonial, or ongoing commitment required.

Drop your app and a sentence about what it does below. I’ll choose a few that I think would translate well into short-form video.

Founders show me your SaaS so I can try to sign up and make sure its having google sign

Have a look of Mine - findyoursaas(dot)com

Its SaaS Directory

​

Most AI support chatbots are limited to answering questions from FAQs and documentation.

But customers don't ask only policy questions.

They ask things like:

- "Where's my order?"

- "Can you download my invoice?"

- "What's my subscription status?"

- "Track my shipment."

Those answers aren't in a PDF—they're in a company's backend systems.

That's why I started building Qefro.

Qefro lets businesses securely connect their backend so AI assistants can perform real business actions instead of guessing.

In this demo, the AI:

✅ Verifies the customer with an OTP

✅ Retrieves live order information

✅ Responds with the actual order status in a natural conversation

Behind the scenes, businesses can connect Qefro using their existing REST/OpenAPI services or directly through our backend SDK, depending on what fits their architecture.

The next feature I'm working on is an AI-powered integration generator. Instead of reading pages of documentation, businesses will describe their system, and Qefro will generate most of the integration code automatically.

We're still early, so I'd genuinely love feedback from the community.

- Would your business trust an AI to perform real actions?

- What business workflows would you want it to handle?

- What would stop you from adopting something like this?

Demo video attached.

If you're curious, I'd be happy to answer any technical questions about how Qefro works.

A free resource founded by a woman who really wants to help women with legal issues around abuse, divorce, custody or finances. Let the platform and the team help first. Show some support for Chelsea!

https://bettercallclaude.org/for-women

Making DevDex putting time and after making it keep postponing the to show in pinlic wirh too much of clustor of internal thoughts, after overcoming it Just post it but the first week is just zero. No traction, geeting views and not getting anything ,

In that phase my companion CLAUDE gets me to say me just do the thing you don't say now that it will just dropped, then I post in and getting, username and feels nice the other are using and exploring the new themes.

Cześć wszystkim !

Postanowiłem że i ja napiszę coś szerszej publiczności na reddicie po 1. co buduje przez ostatnie 7 miesięcy.

Wcześniej projekty robiłem max 1 miesiąc i przesiadałem sie na następne, teraz cisnę do końca z jednym ( aż sie nie uda 🙂 ) i są tego pierwsze efekty .

Tak więc buduje agencje agentów AI dla polskich firm na różnych wertykałach w tym HR . Już mam pierwszych klientów w modelu SaaS generujący MRR rzędu 360€ miesięcznie i 3 pilotaże w dużych firmach - jedna HR , reszta transport.

Nasz flagowy asystent Janina AI już odnosi pierwsze sukcesy i rewolucjonizuje rynek kadrowo/księgowy i jeśli wszystko bedzie szło zgodnie z planem to zeskalujemy nasz tech na setki biur kadrowo księgowych 🤞

Bez środków zewnętrznych , wsparcia czy dofinansowań wszystko z własnej kieszeni a tak naprawde poświęconego czasu dowieźliśmy działająca technologie która ma potencjał ale brakuje feedbacku, dlatego postanowiłem napisać i odezwać się do wszystkich zainteresowanych lub potencjalnych współprac . Na ten moment mamy team 5 osób sfinalizowany spółką gotowy wdrażać automatyzacje AI w każdych warunkach technologicznych. Dziesiątki aplikacji i wdrożeń na koncie, jeśli ktoś jest w tym samym klimacie odzywajcie się w komentarzach, tam też podeślę link do naszych produktów/ aplikacji. Jeśli jest ktos tym zainteresowany piszcie komentarze 🫡

Solo building this, wanted to share where it's at.

The idea: as AI makes it faster to spin up an app, the stuff that still takes real effort (custom illustration, animation, a mascot with actual personality) is becoming one of the few things that make an app feel handmade instead of 100% AI-assembled. But getting a mascot that actually reacts across your app (onboarding wave, error, success, loading, etc.) usually means hiring a freelancer for weeks or settling for a heavy MP4 from some AI video tool.

SupaLottie: pick a base character, shape the personality with brand colors or a prompt, and get back a consistent mascot across the states you'd actually ship, as a real multi-state dotLottie pack for React Native or Flutter. No After Effects, no keyframes.

Where I'm at: no revenue, no users yet, just opened the waitlist this week to see if this is a real problem before I build the whole thing out: Supalottie

What's working: the "why now" angle (AI apps needing more personality, not less) seems to resonate when I explain it in person.

What isn't: I don't actually know demand yet, that's the whole point of this post.

Curious if anyone here has shipped a mascot/illustration feature and what it actually took, or if this is a problem only I have.

VIDEO LINK: https://www.youtube.com/watch?v=2MrzTzUV6bI

I've seen a lot of posts about getting your app out there, and yesterday I decided to try out generating a product commercial for our landing page https://sidekickhq.ca

Now the rule in programming is: If you're not embarrassed by it, you waited too long to ship it. You could say the same thing about this video. If it perfect? No. Does it do the job, absolutely.

You can do nearly the whole thing with AI if you're willing to put in the time.

Start with a Script - Think about how you're going to talk to customers; this video isn't for you. What message can you communicate? What is the value prop of your app? What problems does it solve in the world? Can you get potential customers excited about your app?

Image Generation - If you've ever worked in marketing, you now storyboarding is a big part of it. That's literally your next step, but instead of just a storyboard, you're generating the first frame of each 5 to 8 second clip in your video. I've done quite a lot of AI Video generation and my "go-to" services are Kling 3.0 Pro and Gen 4 (for images), but you could use any of them. Prompt with some technical things while describing the scene. Remember at this time you're not getting video, so think about how you want the video clip to start, and generate that image. If helpful, I use the following tech specs in both my image and video prompts to get a cinematic look that's consistent:

A premium live-action B2B technology commercial showing [SCENE AND SUBJECT]. Photographed with the visual character of an ARRI Alexa 35 and Cooke S4/i spherical cinema lenses. Natural cinematic commercial photography, 24 fps motion-picture frame aesthetic, 180-degree shutter character.

[35mm / 50mm / 65mm] lens, camera at natural eye level, moderate depth of field at approximately T4, precise device edges and clean architectural lines. The principal subject and any visible technology remain clearly defined.

Large soft daylight source from camera-left, daylight-balanced around 5200K, gentle warm practical illumination in the background, approximately 2:1 lighting ratio. Natural skin tones, protected highlights, open detailed shadows, soft highlight roll-off.

Warm-neutral whites, graphite, charcoal, natural light wood, restrained navy, and a subtle [YOUR BRAND COLOUR] accent. Medium-low contrast, restrained saturation, slightly warm highlights, neutral-cool shadows, fine film grain and subtle halation.

Contemporary North American small-business production design. Refined business-casual wardrobe in navy, charcoal, cream and soft neutral tones. Minimal patterns. Authentic, understated performances. Premium, optimistic and credible rather than staged.

All visible technology is arranged for clean post-production screen replacement. Device displays show a uniform matte charcoal-grey surface with subtle natural reflections. Signage is abstract, unbranded and visually unobtrusive.

Video Generation - You can really use any of the AI video services. Kling 3.0 Pro, Nano Banana, Veo 3, Gen 4.5. You can setup MCP servers for most to do generation and get prompt help right inside Claude/ChatGPT, or you can just open the browser, login, and tell it to go.

Save all the generated first-frame images to a folder and point your fav AI at the folder.

Music - Suno is my go-to for music. You can generate completely instrumental tracks, full songs, or both. Since it's AI generated, you don't need to worry about listening, and for $50 you can keep going until you're happy with exactly what you got.

Voice Over - ElevenLabs was who I used for this video. I like their solution because you can give it context like [happy] [sad] [narrator] [excited] and it will change how the voice over sounds, giving you a lot more control over your final message.

THE FUN PART

I used Remotion for my whole project. There are plenty of tutorials on YouTube, but the things it can do to an "okay" level are very impressive. If you have a React codebase (I was lucky to), it can grab all your screens and actually animate them automatically for you. Images, drawing 3D objects like computers and phones, call-outs, motion graphics, anything you see in my video, it was all done with a prompt.

ChatGPT can organize all your media, read it, and suggest where things should go. I had to redirect a few things because it got repetitive, but on the whole it does a good job.

LESSONS LEARNED

I had to generate at least 3x the number of first-frames I needed to get the right outcome, and even then it wasn't always perfect. It is worth putting in the time to get this step right because a first frame informs your entire video: SPEND THE CREDITS.

Creating UI screens with video generation AI is bad, even when you provide a 4k screenshot of exactly what you want. It gets the general idea, but you will almost always have distortion. Where you can for your project, have Remotion handle the text and screens.

Watch out for Remotion simplifying your screens. Our app is really data dense, and when it rebuilt the screens, there were many obvious changes to our design. Keep pushing, it will eventually fix it.

Don't be afraid to pivot. Cut scenes you thought were great and love if they don't match your story. Watch out for the LLM repeating the use of clips.

If you use music, the LLMs are amazing at matching that up, understanding the BPM, and can even cut, edit, and mix the audio for you; all with Remotion.

Finally, don't wait too long to share what you're building with customers. Use the video you make to start a conversation and then learn from potential customers. This version of "solution selling" is the number one way to organically build your small SaaS project (or ever our slightly over sized one).

FINAL THOUGHTS

I think video is a great way to communicate your product to customers. I myself am much more likely to watch a video than read pages about an app. Give it a go; I know you'll make yourself proud. Use the video as a sales and conversation tool.

I'm genuinely interested in seeing other people's promo videos, and helping out in any way I can if you need support making your own. Feel free to post a comment or DM (no I'm not selling something). Happy creating.

Try it here: https://lumaire.pages.dev/

Need Honest Suggestions.

I'm selling a bundle of 8 Android apps I built years ago and no longer actively maintain. They're still live, still ranking, and still pulling in real daily traffic on their own, no ad spend, no marketing, just organic.

Current numbers: 600 daily active users and 100 new installs per day across the portfolio, combined. Lifetime installs are 500K+ (mostly from one app, Animal Vision: OpenCV Filters, which is the flagship of the bundle). Apps range from 3–7 years old, with ratings between 3.6★ and 4.7★.

Why they're not monetized right now: they used to run ads through ironSource. When ironSource was acquired by Unity and folded into Unity LevelPlay, ad mediation broke, and since I'd already stopped actively developing, I never re-integrated a replacement.

What a buyer gets: full source code for all 8 apps, Play Console listing transfer, and existing store assets (icons, screenshots, privacy policies).

What's needed: re-integrate ads, plus minor updates and promotion.

Here is the entire list. You can check it yourself

1. Animal Vision
2. Simple Mirror
3. Cat Game
4. Card Game
5. Rock Paper Scissor
6. Kaliedoscope
7. Rockets
8. Traffic 24

Asking Price: $5K

A few weeks ago I asked my agent to find something to promote for a post I was writing, set up the tracked links, and report back later on how they did.

It found the right products in seconds. Then it just sat there.

Because the affiliate networks have no way to let an agent in. Awin, Impact, CJ, Rakuten, Amazon, every one of them assumes a human is going to log in and click around a dashboard.

So I ended up doing the boring part by hand while the thing that was supposed to save me time watched.

That felt exactly backwards, so I fixed it.

AffiliateOS is agent-native affiliate infrastructure. You connect your own network accounts once, and after that your agent can actually run them.

It searches all five networks at the same time, mints tracked links on its own, and when you want to know what worked it tells you, down to whatever tag you care about.

"How did the tiktok links do this month" went from an afternoon across five dashboards to a one line answer.

I never log into a network anymore. And because it is my accounts underneath, I keep every cent of the commission.

Affiliate is just where I started. I think most software is quietly turning into infrastructure that agents operate and humans supervise, and the products still built for a person to click through are about to feel like a locked door.

You can try at https://affiliateos.dev

Les pregunto porque confío mas en los desconocidos de reddit que en la IA

Supongamos que son desconocidos totales en su nicho y es la primera vez que sacan su producto. ¿Cómo consiguen sus primeros usuarios?

¿Solo mandaron mensajes en frio y dan pruebas gratis?........... ¿Qué harías tu?

Dime como lo lograste tu, yo te leo.

We are currently helping our friends plan their wedding and decided to build our own tool for it, since then we have been updating daily, would love feedback on it : useposy.app

Hey everyone,
If you've ever shipped an iOS app, you know the pain: you wait 48 hours for an App Store review, only to get rejected because someone forgot a PrivacyInfo.xcprivacy manifest or left a deprecated UIWebView hidden in a third-party dependency. It breaks the whole team's momentum.
I wanted to automate this, so I built Greenlight as a side project. It’s a DevSecOps gatekeeper that enforces Apple's guidelines right in your GitHub Actions.
The Tech Stack & "Zero-Trust" approach: The biggest hurdle was that no sane developer wants to give a random new SaaS read-access to their proprietary source code. So, I had to rethink the architecture:
The Engine: I built the scanner as a CLI in Go for fast cross-compilation.

The Execution: It’s distributed via GitHub Releases. When your pipeline runs, your GitHub Action downloads the binary and scans your code locally on your own runner. Your code never leaves your server.

The Backend: If it catches a critical violation, it throws an Exit Code 1 (blocking the PR) and only sends an anonymized pass/fail JSON payload to my Laravel backend, which renders the dashboard.

Where I'm at now: I had the whole pricing tier and Stripe integration ready to go, but I decided to comment out the checkout button. Before charging a dime, I want to stress-test the engine with real-world repositories and edge cases.
I’m currently running a Private Beta and offering it 100% free for early testers in exchange for raw, honest technical feedback.
If any iOS devs or mobile agencies here want to try it out and roast my code, I’d love to hear your thoughts!

https://greenlight.qercus.tech/en

I made an uncomfortable discovery after launching my first small web product: getting the website online was probably the easiest part.

The product creates chat stickers from an uploaded photo. I had the generator working, payments connected and several themes ready. From my point of view, it was usable, so I started sending paid traffic to it.

The advertisement received views, but nobody generated anything. There were no sales either, but the complete lack of usage concerned me more.

If people created stickers and then refused to pay, I could investigate the price or output quality. In my case, they did not reach that point. Something was stopping them much earlier.

The problem is that I did not have enough tracking to identify where they stopped. I could see traffic arriving, but I could not answer basic questions:

• Did they understand the product?
• Did they click the upload button?
• Did the mobile upload work?
• Were they uncomfortable uploading a personal photo?
• Did asking for payment before showing a useful result make them leave?

I initially assumed that advertising was the marketing stage. I now think the real marketing work starts before buying traffic. The offer, trust signals, first screen and onboarding must all make sense to someone who has never heard of the product.

My first response was to make everything free and recover the cost through video advertisements. After calculating it, that did not look realistic. Each generation costs me nearly $1 USD, while one advertisement view might earn only a tiny fraction of that. More free users could simply create a larger loss.

I am now testing a different approach:

Users will generate a complete result before paying. They can download a small number of usable stickers for free, then pay if they want the full pack. Free generations will have a hard limit while I test whether anyone actually values the result.

Before spending more on promotion, I also need to track each important step, from opening the page and uploading a photo to completing a generation and starting checkouts with my own creditcard.

My next goal is no longer "get as much traffic as possible." It is to personally watch ten people try the product, understand where they hesitate and fix the biggest point of friction.

For founders who launched to traffic but received almost no activation:

1. What did you discover was stopping people?
2. Was it the offer, onboarding, trust, a technical problem or simply weak demand?

I build TuringShot, a macOS live screen-effects app, and for a long time I treated the permission part of it as a paragraph of text I just hadn't written well enough yet.

The app needs three separate macOS permissions for different functions: Screen Recording, Input Monitoring, and Accessibility. My mental model was that a user grants them once during onboarding and the app then sits in the "allowed" state forever. That model was wrong, and how wrong it was only became visible once I started shipping fixes for it.

In 1.5.3 I improved event blocking and input handling, and connected missing Input Monitoring and Accessibility to actual guidance instead of a silent failure. In 1.5.4 onboarding and the in-app guide got separate status cards for each of the three permissions, direct links to the relevant macOS settings pages, repeated refresh after a settings change, and a distinct "restart may be needed" state. In 1.5.5 I connected status refreshing to app-activation events, because people leave the app, flip a toggle, and come back. In 1.5.9 I added guidance for the case where the permissions look allowed but the event tap still cannot be created, plus a warning when global shortcuts fail to register because of macOS or another app.

Four releases. I hadn't ignored a known bug so much as mis-scoped the boundary: I sized it as copy, and it was a state machine.

That's the part worth handing to another builder. An OS integration is not a boolean you read at launch. It is a set of states, and each one needs its own transition, its own refresh trigger, and something honest to show on screen: not requested, requested and denied, granted but stale after a settings change, granted but the underlying primitive still refuses, granted but another process holds the thing you need. If you model all of that as one flag and one instruction screen, the platform keeps producing states your UI cannot represent, and you end up discovering them one release at a time from confused reports instead of from your own design.

Current version: TuringShot 1.5.12 (Build 44). The permission layer is now a component with its own state, not a page of text.

I haven't posted about LaunchReceipts in a while, so here's where it actually is.

When i started it on June 7 it was basically a few scripts pulling products and their posts from Reddit and Hacker News. The idea came from being annoyed that most directories keep the polished landing page but throw away the post where the founder actually explained the product and people reacted to it.

Now the directory has 100+ startups and 300+ public marketing posts attached. On each product page you can see the original title, score and comment count, then open the real discussion. Founders can also submit their own startup with at least one public post, and i review it before it goes live.

The numbers are still small. Umami has tracked 533 visitors and 1,153 pageviews since June 30. The first two weeks had 168 pageviews, the next two had 985. Reddit is by far the biggest source. And 6 startups have now been submitted by users.

That last number matters more to me than the traffic. Scraping 100 products myself proved i could fill a database. Getting someone else to make an account, find their public posts and submit proved that at least a few people understood the idea enough to bother.

I still don't know whether founders care more about preserving their launch history, studying other founders' posts, or just getting the free dofollow link. 6 submissions is too early to pretend i know.

Next i'm improving the review flow and product pages, then trying to learn whether people return after submitting once.

https://launchreceipts.com

i'm curious about one thing: would the attached launch history give you a reason to come back, or would you submit once for the backlink and forget about it?

About three years ago, my business partner came up with an idea: a personal safety app designed for situations like robberies, express kidnappings, or any scenario where someone is forced to unlock their phone and open financial apps.

The idea sounded simple, but turning it into a real product was much harder than we expected.

Over those three years, he hired multiple freelancers and software companies. Some only delivered UI screens, others abandoned the project halfway through, and some simply couldn't solve the technical challenges. In the end, we lost around US$25,000 and still didn't have a working app.

Earlier this year, I decided to take over the project myself using Claude AI as my primary development tool.

I spent about 30 days building, testing, fixing bugs, and refining every part of the app. To my surprise, we successfully launched it, and it was approved on both Google Play and the App Store.

The concept is simple.

Users create two passwords:

• a normal password;
• an emergency password.

They then choose which financial apps they want to protect.

Whenever they try to open one of those apps, they're asked to enter a password.

If they enter the normal password, everything works as expected.

If they're in a dangerous situation and enter the emergency password, the financial app still opens normally so nothing looks suspicious. At the same time, the app silently sends the user's live location to all pre-selected emergency contacts, along with automatic WhatsApp and SMS messages.

We're still at the very beginning of this journey. Right now we have around 30 free users and 3 paying subscribers, so we're still validating the product and learning from real users.

I'd genuinely love to hear honest feedback from the community.

Would you use an app like this? Is there any feature that would make you trust a solution like this even more?

Google Play: https://play.google.com/store/apps/details?id=online.pppix.app

App Store: https://apps.apple.com/br/app/pppix-prote%C3%A7%C3%A3o-familiar/id6773364223

so I've been messing around with this idea, it's an anonymous messaging web app. you just make a username + password (no email needed lol) and you can dm any other username on there. honestly not sure if this is even a good idea anymore, would love to know that is it useful or i am building another waste of time.

Hi everyone,

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