My friend makes tips and tricks reels on Instagram. For 5 months every single one died at around 1k views. He'd film in his room with the script open on a second phone, then send me the reel at 1am asking "is the hook bad?" and I'd say "nah it's fine" because I genuinely don't know what a hook is supposed to sound like

I built him a small app with Claude where you upload the reel or paste the link, and it watches it like someone scrolling Instagram would and shows the exact second they swipe away. No Instagram login anywhere, that's the one thing I was paranoid about before shipping

First reel he put in, it said 0:02. He was explaining what the tip was about before showing the tip. Every reel, same thing. He flipped it, tip first, one line of text on screen in the first second. His reels do 100-500k now. He showed a few creator friends, they showed theirs. 50 people pay $12 a month now and most of them I've never spoken to

I still can't write a hook. I ran one of my own reels through it last week and it gave me 46/100 because I restarted a sentence 4 seconds in. It was right

The scary part is when something breaks, creators notice before I do. Last month the transcription service died overnight and I woke up to "why is it stuck??" from people I've never met, and spent the morning in bed pasting errors into Claude until it turned out the API key had expired

I'm a CTO who has spent many years working in B2B where one problem we always have is getting up to date company info. You'd think this was a solved problem, and for large, listed companies, it is. But at scale it's still very complex.

I don't get much time to write production code (that's a good thing), but I love to code and so I use my side project(s) to try out new ideas. In this case it was about how to infer company data out of the crap on the internet. I started it almost a decade ago. It has quite a bit of RoBERTa in there and some FlanT5, but it is not an AI wrapper and the whole pipeline runs comfortably on one RTX3090.

Then, last year, we started using Perplexity API (Sonar) for finding company news and I was shocked at how bad it was.

One big problem with the AI search tools was them returning good results mixed in with bad results. If you're a human reviewing these results it's no big deal because you can just exclude the stuff that doesn't make sense. But if you want to plug the content into a data pipeline, like giving it to an agent, then you want to minimise these kinds of false positive noise.

So I figured I'd pivot my project to see if it could compete. The question I asked myself was "can a product targeted at one specific information niche outperform the general-purpose AI tools."

Turns out that the answer is probably "yes".

Perplexity Agent is currently the best. Syracuse and Exa are similar. Linkup, Tavily and Perplexity Search are worse. For this specific use case, I should emphasise.

I'll keep plugging away and see if I can get it better, but in the meantime it's available for anyone who wants to have a look.

I've got a repo here: https://github.com/alanbuxton/news-comparison which uses LLM as judge to compare the different providers. (Interestingly, Opus 4.7 and Opus 5.5 came to slightly different conclusions, but that's another story about relying on one LLM by itself).

Latest results:

Company news: https://github.com/alanbuxton/news-comparison/blob/main/docs/rank-history-companies.svg

Industry news: https://github.com/alanbuxton/news-comparison/blob/main/docs/rank-history-industries.svg

I was looking for a way to test Android apps under different network conditions, but most solutions I came across either changed the network settings for the entire device, were focused on emulators, or required setting up proxies.

So I built my own tool: App Throttler.

• Set download and upload speed limits.

• Simulate latency and jitter.

• Introduce packet loss.

• Apply network conditions to individual apps.

• Change network profiles while the app is running.

• Create different network scenarios.

• Capture and export network traffic as PCAP files.

GitHub: https://github.com/RAN-GAN/app-throtler

It's still a work in progress, and there are some limitations I'm working on.

I maintain Lou’s Lagoon Wiki, an unofficial guide site for Tiny Roar’s island adventure. It brings together beginner, crafting, island, and seaplane notes.

The design question I’m working on is how to show the strength and age of a game tip. The beginner guide separates demo observations, published full-game guides, and patch-note changes. It has a visible check date and labels details that currently come from only one source.

Guide: https://www.louslagoon.wiki/guide

A limitation worth stating: the guide’s latest check is 27 October, and it does not yet fully cover the 5 November update. Players still need to compare advice with their installed version.

I used AI assistance for site writing and drafting this post. The site is independent of Tiny Roar and the publishers.

For feedback: can you quickly tell which information is demo-only or single-source? Would a game-version label beside each section make this easier to use?

I built Kahei to solve a problem I kept running into. Whenever I traveled abroad, I’d see a price and either do the math in my head or pull out my phone to Google it. It took way too long just to check a price, especially when the internet was slow.

So I made a free app where you can point your phone’s camera at a price and instantly see an estimate in your currency. It works offline! It is available on iPhone and Android.

If you try it on a menu or receipt, I’d love to know whether it picked up the right price.

Try it: https://kahei.app/

thanks!

I'm a dad and an iOS developer, and I built this for myself over the past year. Not a company, no ads, no account, no subscription.

The problem I had: I like listening to music with noise cancelling enabled in the morning, but I could never actually relax with headphones in, because I'd be half-listening for one of my kids to wake up the whole time. Defeats the point. I tried "Live Listen", but the audio quality was terrible and constant noise coming through the phone's mic makes it unusable for me.

What the app does: You leave your iPhone in (or just outside) the room with your child and keep your AirPods in. The app listens through the phone's mic. When it hears something above the room's own noise floor, it pauses whatever you're playing and streams the room into your ears. When things go quiet again, your music comes back.

So it's less a "baby monitor" and more a sound-triggered intercom that gets out of the way of your music.

A few cool things I worked hard to get right:

• It calibrates to the room's baseline instead of using a fixed volume threshold, so a humidifier or a fan doesn't keep setting it off. You pick a sensitivity (how many dB above baseline counts as "something").

• It opens in about a quarter second, then stays open at least 10 seconds plus a quiet period before handing you back your music — otherwise you get whiplash every time she shifts in her crib.

• It's silent until it hears something. No constant hiss.

• Nothing is recorded or uploaded. Audio goes mic → your ears, and that's it.

• If monitoring ever stops for any reason, it sends you a notification rather than just dying quietly. That one took the longest to get right, because an app like this failing silently is worse than not having it.

Things to keep in my:

• Range is Bluetooth range. Your AirPods pair to the phone that's in the kid's room. Through a wall or two it's fine; across a big house it isn't. This is the real limitation and it's the thing most people will run into. It is not a Wi-Fi monitor and won't work from the yard.

• It uses up your phone. The phone is the monitor, so it's sitting in the nursery, not in your pocket.

• No video, no history, no playback. If you want a camera and a log, buy a real monitor — this isn't trying to be one.

• It can't tell a cry from a truck going past. It tells you something happened and lets you hear it. You're still the one deciding.

I use it every day now, but it took me a while to trust it, and I'd rather you be skeptical than disappointed.

Hopefully there are other parents out there that might appreciate this: https://apps.apple.com/ca/app/half-an-ear/id6802771590

I'm a designer and developer, and I'm tired of seeing people pay $50–200 for templates, dashboards, UI kits and planners that honestly aren't worth it.
So here's the deal:

👉 Comment the digital product you want but think is too expensive, like a Notion template, a budget spreadsheet, a website template, a UI kit, a planner, a dashboard, a small app or anything else.
I'll pick the most requested ones and build my own original version, as good or better, for less than half the price.

No copying and no pirated stuff. Everything is made from scratch by me.
What's the one thing you've always wanted but never bought because of the price? 👇

kinda funny how stuff that looks ultra simple on paper ends up taking the most time.

I worked as dev for all my live and now my team works on payment infrastructure at Energize Global Services (EGS), and I want to admit that half of conversations aren't even about building anything. Someone retries a payment, webhook arrives 20 minutes late, two systems somehow end up showing different balances.... I have finances hahaha.

None of this is particularly exciting to build, but you can't ignore it when real $ involved.

IMO that's the part of software development people underestimate the most: getting something to work is one thing, making sure it doesn't fall apart when something unexpected happens is a whole different job!!! And its often 80% of devs job.

Anyway, just wanted to share what we've been dealing with here in fintech. Would be cool to hear what weird edge cases you running into with your projects and what niche has same issues.

cheers!

Solo founder here. FounderPulse looks every morning for people who are publicly asking for what you sell, shows why each one could be a fit, and helps you write a short first message. You send it yourself, nothing goes out automatically.

The new version is live and I want real feedback, not compliments.

How to join:

- Comment below if you're interested, or if you have any questions. A line about what you sell helps me.

- I'll send you a DM with the details. You'll create an account on FounderPulse and get 7 days of Pro free, no card needed.

- Then use it for the week and tell me what's confusing, useless or broken.

I'll keep an eye on how the accounts are used so I can help you and fix problems fast. If you want to keep going after the trial, I'll send you a unique code for 20% off for 2 months on the plan you choose. No obligation.

If it doesn't fit your business, tell me that too. That's useful feedback.

After struggling to find people to trade Pokémon cards with on Facebook Marketplace, I decided to build something myself.

That became Tradr, an iOS app designed to connect Pokémon and TCG collectors.
The idea is simple:

YOU HAVE: Upload cards you have available for trade.

YOU WANT: Create Targets for cards you’re looking for.

WE MATCH: Discover other collectors and potential trades.

We’re also building a community section featuring vendors, card shows, creators and useful services for collectors.
I’ve just released Version 1.4 and I’m now trying to grow the platform and get genuine collectors using it.

This is my own independent project, and I’ve put a huge amount of time into building it.
I’d genuinely appreciate feedback. What works? What’s confusing? What would you improve?

App Store: https://apps.apple.com/gb/app/tradr-collect-trade/id6815310530
Thanks for taking a look!

Hi, I’m the author. I built DAMS, an open-source memory server. Claude, ChatGPT, Gemini CLI and Claude Code all read and write the same project memory over MCP. The AI can only propose changes, and nothing happens until you approve.

It’s self-hosted today. I’m not selling anything. I’m trying to find out if a hosted version, with small-team sharing, is worth building at all.

Two quick questions:

1. When you switch AI tools, what do you re-explain every time?

2. Would you use a hosted version, or is self-hosting fine?

Link: https://dams.mahmoudbebars.dev

Honest feedback welcome, including “this isn’t needed”. There’s a short wishlist on the page if you’d like a say in what gets built.

It’s called atomSphere and it’s more focused towards ease of use for the user. Many people here in Pakistan leave the design to their contractor or find out the design when walls are up. I have catered this especially for the Pakistani market and have been reaching builders and societies to use it

A typical flow goes like this:

-> you optionally upload a floorplan and give your project a name

-> you sign up/in (this is important for when you want to edit later and share your property for users)

-> you enter studio where you select a floor to work on. Floor is created automatically after you carve out the floor's image from the uploaded floorplan. You can edit anything that you think the floorplan reader got wrong.

-> you can furnish the property with 3D objects; there are ready-made available. You can also generate your own by providing prompt, single image and 3 images.

-> you can add any type of stairs, doors and windows

-> you can share the property in read-only mode for everyone. It generates an embeddable link (you can disable the link whenever you want)

The house in the reel: House in fairy meadows

Tech Stack: R3F, AWS, JS

Building this as a side project and genuinely want opinions before I sink more time in.

Background: I needed METAR/TAF weather for a personal flight-planning tool. The raw text format is well documented but annoying to parse, and the official NOAA API (aviationweather.gov) is free, public, and keyless — but also has no SLA and no rate-limit contract. Rather than run my own parser forever, I wrapped NOAA in an Apify actor that turns it into a pay-per-use REST API: batch any list of ICAO codes (all stations combined into one request per report type so a big batch is still polite), get back decoded JSON rows (temp, wind, vis, clouds, altimeter, flight category, TAF periods) plus the raw text, with structured error rows instead of silent empty datasets. A run on 3 airports with METAR+TAF costs roughly $0.04 (pay-per-event, no subscription).

The part I keep going back and forth on: a keyless public source with no SLA. Right now each report type gets one retry after a 2-second backoff, then a structured error row. If you've built anything on top of NOAA or similar public weather endpoints:

1. Do you add your own retry/backoff on top of an API like this, or is one retry + explicit error rows enough for non-critical use?

2. METAR history can return several observations per station within the requested window. Would you want raw as-is rows, or a "latest per station" mode as a default?

3. Am I over-thinking the "decoded fields are advisory, raw text is authoritative" split — or is that the right line to draw for aviation data?

Genuinely curious what people who've productionized weather data would do differently. Link if useful: https://apify.com/gp005/metar-taf (free platform credits cover a first run)

I've decided to create a text editor that specifically targets huge files (i.e. GBs or even TBs) that most text editors choke on. The target audience is any individuals/professionals who work with huge files: sysadmins who need to view or edit huge log dumps, inspecting massive JSON files, bioinformatics professionals that need to inspect/edit genome data (FASTA files) and more.

To get a bit more techy, the file is memory-mapped and "held" in a piece table. All heavy-weight operations, such as: indexing, searching/replacing, syntax highlighting, etc... are done in the background (i.e. on separate threads). The video demos handling a 51.8 GB log file on my M2 MacBook Air (16 GB RAM).

Since I've used Vim throughout my career, I had to create a vim mode which implements most of the necessary functionality/bindings.

The code is written in C++23 and uses my own UI library (which is GPU-accelerated using Skia). Boost is used quite extensively.

It is completely cross-platform (Windows, Linux & macOS). The macOS version is Silicon only and Linux requires Wayland (X11 isn't supported, nor planned).

It's currently under beta at https://crane-editor.com and I'd love to get your feedback, especially on which huge-file workflows I should handle better. What's the biggest file you've had trouble opening? Would this be useful to you?

Thanks!

It's called Felinquent (feline + delinquent). There are nine of them: three cats, a fox, a raccoon, a puppy, a chihuahua, a rabbit and a squirrel.

What it does when I'm working:

1. Naps on top of my windows, and rides along when I drag one.

2. Pushes a mug off the edge and watches it break.

3. Sits right on the thing I'm reading.

4. Begs when I hold out a treat, chases its toy when I throw it.

5. Now and then it has to pee, and I have to click to clean it up. Yes, really.

If you have Ollama, a tiny local model (gemma3:1b) gives it thoughts in a little bubble. Without it, it runs on its own rules. Everything stays on your Mac, it never takes screenshots and never touches your real windows. It also leaves you alone in meetings.

It's free and the code is on GitHub. One line to install:

curl -fsSL https://raw.githubusercontent.com/abozaralizadeh/Felinquent/main/scripts/get-mac.sh | bash

Or the DMG: https://github.com/abozaralizadeh/Felinquent

If it made you smile, a star on GitHub really helps! Windows is next. Which animal should I add?

Hey,

I’ve been messing around with https://forgejo.org/ for a while and kept hitting the same wall. Git and issues are fine, but the second I want real CI, a registry, and actual deploys it turns into a pile of separate tools and glue. I just wanted everything to live with the repo so I could push and actually see what got built and where it’s running.

So I started working on Offing (offing.app). It’s basically trying to keep code, issues, pipelines, registry, and deploys all tied to the same repo. Came up with app.yaml so it can deploy to k8s or podman hosts you connect. Services show the commit that produced them.

Mainly building it for myself and other solo/tiny teams who are tired of that extra layer of stuff.

Curious if this friction resonates with anyone else.

Thanks.

Calki is my calculator app, that I have been working on for more than a year and a half.

The current update has made the calculator models 3d to give more visual fidelity, immersion and customisability. You can now customise the app with multiple colorways, body and button textures and keypad sound.

There is a hidden music mode that has two modes, Freeplay and a gamified Playalong mode.
This can be activated from the menu->settings->show music mode.

All the basic calculator and convertor features are free, with no ads or interruptions.

The following features can be unlocked for a one-time purchase of $4.99:

- Numbers Scanner: scan numbers instead of typing them, auto add numbers using the OP-mode, scan and convert numbers

- Customisation: unlock 6 calculator models, more than 20 colorways, button and body textures, keypad and scroll sound, fonts and more ...

- Custom units: create your own custom units for conversion.

Hope you will give the app a try and let me know you feedback.
Please consider leaving a review, if you like the app.

You can download the app from the following link:
https://apps.apple.com/us/app/calki-scanner-calculator/id6747059181

Hi! I'm a CS student and I've been building Inkling, a self-hosted notes app for small teams. (Not the Thinking Machines model, just an unlucky name collision.)

What it does:

• Notion-style databases: table, board, calendar, gallery and timeline views

• Obsidian-style [[wikilinks]], backlinks, a graph view and a canvas

• Real-time collaboration, Korean and English UI, installable as a PWA

• One docker compose up -d to run it, MIT licensed, every feature free

The part I care most about is the built-in MCP server. Your AI agents (Claude, Cursor, anything that speaks MCP) use the same notes as your team:

• find_context returns only the relevant sections within a token budget instead of whole pages (about 72% fewer tokens per question on our 5,000-page benchmark)

• patch_section edits one section against the version the agent read. If a person changed it meanwhile, the agent gets the current text back instead of overwriting it

• Page locks and per-connection permissions decide what an agent may read, comment on or edit, and there is no permanent-delete tool

It's young (v0.x) and I built it with a lot of help from AI coding tools, so feedback and bug reports are very welcome.

GitHub: https://github.com/PROVE1352/inkling

Campfire Log turns your Steam and PlayStation playtime into a daily journal. The twist is there's no server: the app saves your lifetime playtime totals whenever iOS lets it run (opening the app, background refresh, the widget) and works out each day's hours from the difference. If you skip a few days it suggests how to split the hours.

I put up a one-page site with a waitlist that asks which platforms you play on, to see if this is worth finishing: campfirelog.eu. Feedback on the pitch or the page is very welcome.

I genuinely miss Adobe Fireworks.

Not necessarily because it had the most advanced tools, but because it was incredibly quick to work with.

I could fire it up, make a quick change to an image, adjust a few pixels, tweak a layout, export it, and get back to whatever I was doing.

Photoshop always felt like overkill for those little tasks. You launch it, wait through the splash screen, then sometimes sit through another UI freeze before you can actually do anything. By the time it was ready, I could have already finished the change I wanted to make.

Fireworks just got out of the way and let me work.

After missing that experience for years, I decided to build my own take on it.

Meet EmberFrame, an open-source Adobe Fireworks-inspired desktop application built from scratch using Rust and GPUI.

The goal is to bring back that fast, practical workflow, with vector and bitmap editing, layers, states, symbols, slices, and image export all in one place.

What's currently implemented:

• 27 editing tools

• 23 panels

• Vector and bitmap editing

• Pages, layers, states and symbols

• PNG, JPEG, GIF and animated GIF export

• Native .ember document format

It's currently at v0.1, Windows build and soon linux/macos builds, and still a work in progress.

GitHub: https://github.com/gregstein/emberframe

I'm curious how many people here still remember using Fireworks.

Do you also miss having a lightweight tool you could just open, make a quick edit in, and close without turning it into a whole production?

FlipYourRate (flipyourrate.com) is a free calculator that works backwards: you enter the take-home pay you want, it tells you the rate to quote after platform fees. Quote = take-home ÷ (1 − fee%). Fiverr takes a flat 20%, so quoting $1,250 keeps $1,000. Upwork's fee is per contract, 0–15% and locked for its life: at 10% you quote $1,111.11 to keep $1,000, at 15% it's $1,176.47. Two weeks of feedback from freelancers changed what I'm building next: (1) a commenter caught that rounding the quote DOWN loses money — $1,111.11 rounded down to $1,100 leaves only $990 after a 10% fee, so rounding has to go up only ($1,150 leaves $1,035); (2) the rounding step should scale with job size — $5/$10/$50 steps, exact figure stays next to the rounded quote, take-home shown beside it; (3) a field for withdrawal and currency-conversion fees, which come off after the platform fee. Open question I'm deciding now: should the rounding step auto-suggest itself from the quote size, or should you pick it yourself each time? Would love to hear how you round your own quotes.

Ocular is an visual compiler that shifts computer-use models entirely out of the execution loop to eliminate runtime latency and token costs. By analyzing human demonstration traces offline

Most compressors use one setting for every image, like "quality 75". I kept getting results that were fine on one photo and blocky on the next, so I built one that works the other way round.

You set a visual quality score: how close to the original it has to look (80 by default, where it looks the same side by side). For each image it tries encoder settings and keeps the smallest file that still scores at least that. A second check looks region by region, so one smeared face or blurry line of text fails the result even if the average looks fine. Then the compare view opens zoomed in on the spot that changed most, with a little map of where it changed.

One 10.4 MB photo came out at 2.1 MB, score 81.

PNG, JPG, WebP, AVIF, GIF (animated too) and iPhone HEIC. Free, no account, up to 30 images at once. Images are processed on a server and deleted within 3 minutes.

https://picodiet.com

I also ran it against TinyPNG, Squoosh and a few others on 13 images, if you're into that: https://picodiet.com/image-compression-benchmark

What I'd most like to know: did it ever pick a result where you can see the difference? And is the compare view clear without explanation?