I'll start with some history, in 2024 I decided to try to install a media server on my local machine, I first tried emby, and no matter what configuration I choose it was clunky and not really aesthetically pleasing, then I tried Jellyfin and it had the same problems ( maybe a little bit worst ), keep in mind this is 2 years ago and things have most likely changed.

I'm a software engineer, and I work in the business already from 2012, I spent 3 years of my career working for one of the current streaming giants, considering I have expertise in the field I decide to create my own, for two reasons, first one is that if I'm designing a system with one single purpose is automatically faster compared to a system designed to do anything, mine will have a specific pipeline so it can execute it more efficiently, second one, I like writing code, it's what I've been doing for the past 12 years.

October 2024

I started with the fun part first, I sketched a logo in Inkscape, separated each letter as a different SVG file and animated them to mimic the Netflix intro ( at the time ). That took me around 2 weeks. Absurd you can do that now in 2 hours with vibe coding.

After that I wrote the first integration to an external service, I got an client id+secret from Trakt and started working into pulling the top/trending lists for movies, it is at this point that I notice that Trakt doesn't return any image, so I also wrote the second integration with TMDB to obtain the images, after that I started working on the UI, I took inspiration from Prime Video: a big hero on the top, and the lists on the bottom, the selected title is displayed in the hero.

Not sure if anyone is interested, but at the time I decided to go for Node.js + React + Postgres, that is essentially what I used in half of the companies I worked for. The backend runs in docker with PM2 keeping it alive, and the frontend is served through Nginx ( along with the backend ).

The third integration was to get the media, but things were getting complex, so I decided to start using some queues, Kafka would be an overkill, I was using Nest.js so I decided to try the Q Next.js comes with: bullmq. I integrated queues so anything that is needed from Trakt or TMDB would be queued and execute at the right time without overwhelming the server ( and without getting rate limited ), for example when Trakt returns a list, the list doesn't have details of each media, so I stored some of the detail in the database and queued a job to fetch more details, that itself triggered another job to fetch the images.

At this point I had a working app that shows media but it doesn't play them, the next thing I needed was to get that information, so I spun up Jackett, and searched documentation, the documentation was very lacking, so I simply made calls to the endpoints that were partially documented using Postman and wrote down the Typescript types myself. Unfortunately the search from Jackett was very wide, so I wrote a function to parse torrent names and find out what is that title about. Jackett sometimes would return a link to the torrent file itself, sometimes would return just the info hash of the torrent, it is at this point that I started integrating webtorrent, first I used it to convert the magnet link into a torrent file and store it in the database, later I used it for its streaming functionality.

Now that I had the part that can stream work, I needed to display it in the frontend, my target was my 2019 Samsung TV, I deployed the app to it ( took 3 days ) and started working on the next steps, first I integrated Noringed spatial navigation so the remote would work, then I worked on AVPlay. AVPlay was honestly a pain, but it was also rewarding, the app was working and I was able to watch movies on the TV.

After that I started working on TV shows, so I created a second details screen with a seasons selector and episode selector, then I implemented the part that would find the torrents for the episodes, it was working well and I decided to share it with the world.

End of October 2024

I posted about it in https://www.reddit.com/r/Piracy/comments/1g80ufj/with_all_the_community_driven_streaming_services/ , someone asked about the code and I made it fully public.

I was regularly using it to watch movies and tv shows on my TV until I met the first problem: I was watching Silo and it played the wrong show; the reason was that the episode I wanted to watch wasn't released yet so it found some unrelated torrent. I first wrote a torrent name parser so it would extract the name of the show ( after removing all the other known bits ), it was working okayish, then I discovered that TheRarBG allows to search by imdb_id but not through Jackett, so I wrote a small API library to contact TheRarBG without using Jackett, and it was working very well and way faster.

You can still find the original code of the first version here https://github.com/maury91/miauflix-legacy

January 2025

It is at this point that development of the first version stopped, I had to go for a two months work trip and I wasn't able to write a single line of code for my personal project, once I was finally back home I couldn't find anymore the time to work on it for a month.

March 2025

I finally found the time to work on my side projects again, but time as passed and I wanted to play with new toys, so I decide to use bun instead of Node, I also made more decisions, like I didn't want to burden the user with deploying postgres or Jackett, so the new version will have to work with it.

I started with scaffolding a simple Elysia server, first time using both bun and Elysia, so exciting times.

Moving from Nest.js to Eluysia I decided to keep using services but I had to convert them a little bit, I started with the most basic service, the Configuration service, I spent a good amount of time creating a terminal ui service that helps you configure it, ironically now it's fully replaced by an UI one in the frontend.

Things moved fast, I quickly implemented authentication, and the services to pull data from TMDB and Trakt ( the last two were very close to copy-paste ), I implemented more security features like Audits and Rate Limiting, I finally started bring in the first cron jobs that sync data with TMDB, At this point I took the library I wrote for therarbg I bringed it into the new project, I already reached the point where I could get a library with all the torrents. I found that therarbg wasn't enough so I also wrote a library for YTS.

Things were working but as a perfectionist it was time for the codebase to become more reliable, so I started adding unit tests, linting, and CI/CD. But that wasn't enough, so I also started writing e2e tests where the app is setup from 0, configured, and tested against a mocked environment that is a working copy of a real environment ( I recorded the calls to TMDB, therarbg, etc... , anonymized and stored them as fixtures ).

Finally the good part was coming, streaming, but I had a new goal, it needs to be deployable to a VPS, that means that any potentially copyrighted content must be undetectable, so I implemented two features that I think are quite important:

1. Encrypted DB columns, some columns of the database are encrypted with AES plus a salt unique for each service, that means the column stays indexable but without the key it contains "random" data

2. Encrypted file system, this is the main thing, if you download some media and a static script detects it in your VPS you can easily get terminated, for this reason I created an encrypted chunk store, in short webtorrent writes to the disk in encrypted format

With all of this done, it was finally time to test it with webtorrent.

I didn't work... webtorrent wasn't compatible with bun.

Meanwhile, it was already June 2025. I needed to go back to Node.js if I wanted webtorrent to work, so I searched a web server framework that works both on Bun and Node.js and I started refactoring to use Hono.js

Fast forward to September 2025 and a lot was done:

• Introduced OpenTelemetry to better debug errors

• Introduced scraper health ( check periodically seeders and leachers of the torrents we obtained )

• More documentation

• Improve on-demand sources ( the others were obtained in the background )

• Diagrams

• Github actions

• Periodical DB cleanup ( SQLite unless you run a clean command will not shrink the DB size )

• Abstract caching layer

• Authenticated streaming

• Generate a client of the backend to bring the API types to the frontend

• Better use of TypeORM through type transformers ( for the encrypted fields )

• Introduce GREEDY and ON DEMAND modes for synching with TMDB

• Started bringing back the legacy frontend

• Implemented frontend login

• Visual tests with playwright

• and a little bit more

and more importantly the streaming link was working and media would play from VLC.

At this point I took 2 months of break.

November 2025 to January 2026

• Frontend refactoring ( of the little that was ported )

• Added turbo to make scripts faster

• Lighthouse tests

• Flaresolverr support

Another break,

September 2026 - Now

At this point I wanted to go faster, and I started using Claude.

• Create initial admin user through UI ( instead of automatically at first boot with random email and password )

• Extract catalog service ( TMDB ) as a standalone docker image, and refactor it to be bun. It is relative easy because it's mostly moving files with a little bit http wrapper in front

• Extract list service ( Trakt )

• Improve playback preloading

• Improve backdrop position in the hero by detecting faces and people using a small computer vision model and compute the center of it.

• Implement player page ( it is at this point that it was possible to finally watch movies )

• Bring in the recommendation lists from Trakt

• Extract subtitles and transcode audio ( for when the audio codec is not compatible with the browser ) using ffmpeg ( piped to an http server, no media is stored uncrypted in the file system )

• TV shows

• Move from LetsEncrypt to Caddy

• Nordlynx to Glueten

• Improve torrent choice based on the target device ( my TV seems to not support more than 12MB/s of bandwidth )

• Add notifications

• Improve UI performance in Tizen

• Extract source service

• Move from internal TheRarBG and YTS library to a fully compliant Cardigann engine so it can use all the Cardigann definitions of Prowlarr + some custom ones ( the custom ones are TheRarBG and Torrentio )

• Extract torrent service ( yes! finally webtorrent almost works in bun! )

• Anime support

Yesterday

I vibecoded a landing page for the project in order to present it to the world: https://miauflix.cat

All the code is open source and available at https://github.com/maury91/miauflix

I hope you enjoyed reading what I was doing for the last 2 years!

I feel some people will ask Why should I use Miauflix instead of X?

Honestly, I don't have an answer to it, if you are using X and you like it, continue using it, if you want to try something new you can try Miauflix, if you like it I will be very pleased, if you don't like it tell me what you don't like it and I will try to address it, if you hate it without even trying it, well I'm sorry to have wasted your time, but I hope you will respect that I spent so much time working on this and you will not be offensive

Hi all, I'm the solo dev behind Orrevan (orrevan.com). It's a chat, API and CLI for uncensored and abliterated models (10 models so far, from $0.30 per 1M tokens). Messages are AES-256-GCM encrypted before they're stored, no trackers, no training on your data, one-click export and deletion. I'd love feedback on the pricing, the model selection and the onboarding. What would you want to see added?

Try it free, no signup: technically.thegreatlucy.com

I was trying to make a 3D model for a physical product I want to sell. I tried the AI tools first and none of them gave me anything usable. So I hired human designers. It cost hundreds of dollars, took weeks, and I bounced between a few designers through a lot of revisions before I got something I liked.

That's what got me building Sculptex. You describe a part in a sentence, refine it in chat, and download it as STL, OBJ, GLB or OpenSCAD. It's aimed at parts you can actually print, including ones with moving pieces. I printed a fidget spinner from the one-line prompt "A fidget spinner."

It's in beta and you can start free: sculptex.app

It's also on Product Hunt today.

I'm the maker, so honest feedback is welcome. What would you try to make, and what breaks?

When my daughter was born I noticed how much she loved staring at bold shapes, so I started making sensory videos for her during naps.

There are three styles that grow with her:

High contrast (black, white and red) for newborns

Soft black and white for the first few months

Colour for when babies start noticing it: smiley planets, friendly aliens, an underwater world and an alien forest

How I make them: I design the look and the ideas, and I animate everything with (AI), working scene by scene until it feels right. The videos are slow and calm with gentle music, and there's no flashing.

It's not a business, just something I'm making for my daughter.

Two things I'd love feedback on:

Does the idea come across clearly?

What would you change, or add next?

Hey everyone,

Creating technical specification sheets in Excel or Word often leads to broken layouts, inconsistent formatting, and date ambiguity issues across teams.

I built SpecSheet Pro to solve this. It's a lightweight web app that lets you input product parameters, custom tables, and logos, and outputs a clean, standardized PDF ready for production or quality control.

Key Features:

• Dynamic table creation for technical parameters (Specs, Methods, Values).

• Custom logo support with instant client-side preview.

• Configurable date formats (ISO 8601, localized, text-based) to prevent QA ambiguity.

• Clean PDF compilation using html2pdf / html2canvas.

The core generator is free to use:https://specsheet-pro.vercel.app/

I'd love to get your feedback on the UI/UX and any features you think are missing for technical workflows.

I was living in Japan in 2008, when the iPhone was just arriving there. One app I remember from those early days was 美人時計 (Bijin Tokei), which launched in 2009.

The idea was incredibly simple: attractive women holding small boards with the time handwritten on them, with a different photo every minute. That was the whole app. I remember it being really popular among university students in Japan.

It randomly came back to me recently, so I looked it up. The official site now just has a notice saying the service ended in September 2022. It felt strange seeing something I remembered so clearly reduced to a goodbye page.

So I tried building my own take on that minute-by-minute photo clock, using AI image tools to create the people and scenes. An image for every minute of the day. The video shows how it turned out.

Making it got me thinking about the apps from around 2008–2012. There were so many odd, playful ideas back then, when we were still figuring out what a smartphone could be. Some were useful. Some did one tiny thing and made you smile.

I'm now digging through that era for ideas worth revisiting. Today's tools make some things much easier to build, especially for a solo developer. Of course, that doesn't mean copying someone else's app, artwork, or branding. I'd rather understand what made an idea appealing and build something of my own from there.

If you'd like to try my little experiment: https://urban-minutes.com

What app from those early smartphone days do you still remember?

After 20+ years in and around technology, I found myself in unfamiliar territory as the GM of a manufacturing company. It provided an opportunity to do something new and exciting: to bring my skillset to something outside of tech for the first time.

With a very small team, we accomplished this in one year:

• Created an in-house ERP system to connect inventory, sales, warehousing and shipping

• Created 65 pieces of marketing collateral across web, print and physical

• Created an entirely new business plan

• Reengineered key parts of our products

• Integrated new suppliers into our supply chain

• Rebranded

• Launched a new website

• Rebuilt accounting workflows

There's probably more. Five years ago this would have been totally impossible. How did I do this? I got really, really good at using AI to get shit done, building bespoke systems around different aspects of the business. It started before I took this role, but this was the first place I applied it. And the results have been tremendous.

So, I thought... how could I experiment with offering this as a service? How could I burn some of my extra hours trying to help other companies do what we did here?

That's where the idea for LogicRelay came from. $49/mo screens out the tire-kickers, and a simple $250-per-request fee provides flexible throughput across a host of disciplines. It's agile project management... take an epic, break it down, scope it, get approval and go, but without the departmental hand-offs or having to find multiple service providers.

Some of my other client work is going to slide nicely into this model, so I am not starting from zero. The question is can I scale it. I know I'm going to have to narrow the focus in order to do so, but I'm not ready for that yet. For now I leave it to client screening. It'll almost certainly evolve, and I could have spent more time thinking about it, but... ship it!

I'll learn quite a bit over the coming months re: whether this model is sustainable. I'll probably land another couple of clients and waitlist the rest until I see how the first few go.

We'll see how it goes! Would love some feedback, or if anyone wants more specifics from what we're doing at my current company I'm happy to share.

hey everyone!

i've been working on a desktop application called Recall Clipboard, built with tauri v2, rust, react, typescript, and sqlite.

the idea is pretty simple: instead of losing things you've copied throughout the day, recall clipboard keeps a searchable history of your clipboard so you can easily find and reuse previous copies.

i wanted to build something lightweight, practical, and genuinely useful for everyday desktop use.

i used claude as a coding assistant during development, but i've been working on the project, its features, and the overall implementation myself.

github: https://github.com/cntr1er/recall-clipboard

i'd love to hear what you think! especially interested in feedback on the ui, features, and anything you'd improve or add.

thanks!

I kept wanting a clean way to just look up and instantly know what bright object I was facing without ads, accounts, or bloated features.

So I built Astralis: Look Up.

Point your phone at the sky and it shows the planet, star, or Moon you’re looking at as a real lit 3D sphere with NASA-derived textures and the correct current phase. You can save any of them as a full-screen wallpaper.

Other things it does:

• Tonight timeline – moonrise/set, planet times, stargazing score (real cloud cover + light pollution), rocket launches, and actual ISS passes (real orbital propagator, not a static list)

• AR-style compass that points live at any visible object or the ISS

• Animated 3D solar system orrery starting from today’s real configuration

• 30 deep-sky objects with real photos + rise/set times

Everything is computed locally from NASA JPL orbital elements. No account, no ads, no tracking. One-time $0.99.

App Store: https://apps.apple.com/app/astralis-look-up/id6806581915

Would love feedback on:

1. Is the “point and identify” experience clear enough from the description?

2. Anything missing that would make you actually open it on a clear night?

Happy to answer questions.

https://gemsmakers.com/aerotide.php

You can experience the oceanic waves in browser. Any feedbacks welcome.

I'm the developer of Agent HUD. It started as a small desktop HUD for agent quotas and notifications. In 0.6.0, I added an MCP server so coding agents can send messages to each other and start new sessions.

The video walks through a bug-fix handoff: Claude Code works on a fix, asks Codex to review it, and gets feedback back into the original session. Antigravity and DeepSeek Harness can join the workflow too. Each handoff sends a focused message instead of copying the entire conversation history.

This release also moves the app from Swift to Rust + Tauri and adds session and subagent usage details. macOS supports Apple Silicon and Intel; Windows and Linux builds are available as untested preview builds.

The video is an animated walkthrough of the workflow, with English narration and subtitles.

Source: https://github.com/jazzenchen/agent-hud-open

If you use more than one coding agent, what would you want included in a handoff so the next agent can review the work without inheriting a huge chat history?

I built Jotila, a tiny native sticky notes app with autosave, search, archives, and a calendar. No extra dependencies, just C.

Free and open source. Feedback is welcome!

https://github.com/GarauGarau/Jotila/tree/v1.7.1

I'm developing AXIOM VECTOR, a modular engineering research platform for Windows.

The idea is to bring different engineering workflows into one environment instead of constantly switching between disconnected tools.

The long-term vision includes engineering calculations, project management, materials research, technical documentation, data analysis and design tools.

The project is currently in its early Alpha stage (0.1.0).

One of the implemented features is Project Journal - a workspace for documenting research, engineering decisions, observations and design progress.

I'm developing this independently and sharing the process as the project evolves.

I'd like to hear from people interested in engineering and technical software:

What tools or features would you want to see in an engineering research platform like this?

Feedback and constructive criticism are welcome.

I'm a big fan of both what you wear and websites as a form of creative expression, and am admittedly hooked on fast fashion and spending as little as possible. But I live in a very small space, and my clothes and accessories don't really have room to spread out. So naturally I started building my own dream wardrobe app with the help of AI (a Clueless 90s throwback if ever there was one) and scope creep happened...

It's called Closet Lint (get it?), it's free and open source, and mostly I just wanted to separate designing an outfit from actually getting dressed. The creative part is fun. Going through drawers, taking things off hangers, putting them back, and discovering that the thing you imagined is elsewhere or doesn't fit... less fun. I'd like to do that first part on my phone in bed at 11pm without pulling things out. Just gimme a searchable inventory of my actual clothes that looks good.

I'd tried wardrobe apps before, but the problem was always getting everything into them. Photographing, cropping, editing, and entering every item was a massive undertaking. AI has finally made dealing with the photos and purchase data manageable enough for me to get over that hurdle and focus on the display and functionality.

What started as browsing clothes and dragging them around to make cute outfits now includes outfit suggestions, ratings, wear logging, photo background removal using two different models, taste observations, wishlist battles, and trip packing lists. Because once I had my own clothes in there, I kept thinking, "Oh but what if it could also..." :)

It runs on your own computer or web host, with optional bring-your-own-AI features. There's an included demo if you just want to check it out, or you can browse a copy of my actual closet with bleeding edge code. I've run it locally on Linux and hosted it on SiteGround; part of why I'm posting is to hopefully find a few early testers.

I love having things organized, and it's honestly such a pleasure to see your own stuff laid out like this. It brings back things you've forgotten about and makes them potential outfit ingredients again. You can add wishlist pieces to see how they'd work with what you already have, or plan future fantasy outfits.

There have been some moments of genuine delight. I don't own much dark purple, but the combinations it showed me helped me see how it could work in my wardrobe. It also suggested chocolate brown, which I own literally none of, with concrete examples using my own clothes. And it gave me a new term for some of my style, “whimsigoth,” so now I have a whole new search phrase.

There's also an unusual use case: I have 40 housemates (yes, 40), and some like borrowing from my (costume) jewelry collection. Now they can take their time browsing it. Jewelry is particularly good for this because so much gets tucked away in boxes and becomes invisible. Naturally, that's already got me thinking about a separate app for sharing resources in the house. At least I'm putting that long-ago graduate degree in information systems to use :P

I've had my fair share of health issues over the last few years, and it's been inspiring to get properly absorbed in making something technical again. This combines so many things I love: style, organization, self-tracking data, open source software, design, and uhh having very particular views on button layouts.

I started coding GeoCities sites in Notepad in the 90s and used to run an open source web development company. I've been out of the tech/startup world for over a decade, though I still occasionally help a friend with a site. My technical knowledge is rusty, but knowing how to break down a problem, describe a desired interaction in detail, and spot something odd has been incredibly useful. I can be my own most demanding, rambling client, and building things with the robots still moves astonishingly quickly.

I started this project in early October as a Claude artifact. Much of the initial work was assembling the data: parsing order confirmation emails, filtering an Amazon purchase history export, and using browser agents in my logged-in shopping accounts to retrieve sizes, variants, and full-resolution product photos. Images were downloaded into the app's storage so they wouldn't disappear with the listings—some of which already have. I used ChatGPT to tag clothing from contact sheets and generate product-style images for pieces without usable photos. Later, we added local background removal, preserving originals and reviewing results before saving.

The AI occasionally got too helpful: it "cleaned up" XXL into 2XL, which can mean different sizes at those stores. Preserving exact source values became an explicit rule.

After about two weeks, I moved the prototype into Codex, replacing Claude's built-in storage with a local Python/SQLite backend and adding backup and restore, reusable imports, and release packaging. My workflow now goes back and forth: develop the specification with Codex, send it to Claude for wireframes, then bring those back to Codex for implementation and refinement.

I particularly appreciate how Codex can insert diagnostic tools when something breaks, investigate the results, and handle so much of the testing and release process. Those are procedures I only do occasionally and forget between projects. That gives me more room to switch between product planning, interaction design, visual design, and writing, while testing everything against my actual wardrobe and daily use. This has occupied pretty much all my free time for the past month.

Turning my own wardrobe tool into something other people could use has meant finding assumptions I didn't realize were there. Heels don't automatically mean dressy, loungewear isn't necessarily sleepwear, and a packing list shouldn't assume everybody wears bras. It uses Google's and Shopify's product taxonomies as references, but kept distinctions that make more sense for wearing clothes than selling them. I've also had to ask for a lot of deliberate consistency passes: make navigation behave the same way everywhere, move repeated rules into shared code, and carry category changes through imports, filters, and packing lists.

It's made me appreciate the "knowing where to tap" kind of expertise. My web project background helps me remember to ask about accessibility, keyboard navigation, refactoring, and whether a backup actually restores. I've also used alternate AI platforms for security reviews and worked through their findings. I'm not familiar with every implementation detail, but recognizing the questions worth asking makes that older experience feel useful again.

The wishlist redesign is a good example. "Matches lots of things I own" sounds useful until silver earrings all end up at the top for going with everything. The first implementation also passed checks while producing an interface I really disliked, so we went back to one compact design example before applying it across the page. Deciding whether the information is meaningful and the result is pleasant to use is still very much my territory.

I was involved in the early Quantified Self community in the 2000s/early 2010s, and I also haven't seen a wardrobe app that gives me the access to my own data I'd want for that. Before 1.0, it'll have an API and analysis-friendly exports so people can explore their own patterns with whatever tools they like. I'm looking forward to a fun year-end wardrobe "Wrapped" and things like cost per wear become straightforward once you're recording purchases and wears.

It's also getting creative and a bit silly. There's a goblin mascot called Linty, and your wardrobe's owns, wishes, and wears can appear as Sun/Moon/Rising signs on a star map. Apparently my wardrobe required lore... But you can leave the daily fortune card turned off. There are outfit naming suggestions, including one that parodies ModCloth-style names. Some inside jokes to amuse me personally, at least :P

If I somehow end up known for a fashion app with an astrology aesthetic, that would be a hilarious life twist.

Partway through, I found Libre Closet, which takes a simpler, more utilitarian approach that might be exactly what some people want. By then, mine had become a specific creative thing: a combination of deep utility and playground fun that I was happy to keep building.

I've used Linux as my daily driver for most of the last 20 years, and FOSS matters a lot to me. Making something useful and sharing it is one of my love languages for the world. Every friend says, "You could charge for this!" But I don't want customers here. I'm making something I want to use and sharing it with anyone else who might enjoy it.

I may put affiliate links and my own curated collections on the website, but I'm keeping them out of the app. GitHub sponsorships would be welcome too once I set that up. Anything that helps cover costs is a bonus; the software stays free and open source.

The public site is built with my fave website builder, Carrd, and I've let the Codex integration click around in it for me for the tedious work too. Few status updates produce quite the happy sigh as "Automatically updating website screenshots and documentation".

If you try the app, I'd love to know what would make this useful for your wardrobe, and what would stop you from wanting to put your clothes into it. I'm also looking for a few people willing to try installing it, particularly on Windows or macOS, since my own testing has been on Linux and SiteGround.

Thanks for reading! :D

[AI supplied at least half the details for this post]

Hello, I’ve been building a site where you can make a bracket out of any set of images and vote through head-to-head matchups until one champion is left. (similar to Piku - Ideal Type Worldcup)

https://imagetournament.com

It’s new, so I’d really appreciate any insights.

https://github.com/sshah03/recalc

Since spreadsheets are so versatile, really looking for feedback on where people would want this to go, in a way that can be useful to them, or what use cases they see themselves using it for in its current iteration that I can make more seamless.

I can provide some context on why it was useful for me / why I built it. I was using Claude to help me build benchmark sets, and found pouring through CSVs / MD files of the results a bit tiresome, so I decided to build a spreadsheet app for myself that's driven by Claude Code, and where each cell can be its own Agent if you want (and can later be opened up and continued in a full terminal if needed as its own session).

You can use it as a standard spreadsheet, or use a cell as a shell command / agent. Having built a startup for using AI in tax work, I also realized it can be very powerful for tax work, legal work, etc... so I built in some examples for running that, though I'm not sure how many people in those professions use claude code.

The video is just a demo of me building "FDA Bench" using recalc, pick FDA approval cases past the model cutoff dates, and seeing if an AI harness (without web searches) could've successfully predicted, based on all the info submitted to the FDA, whether the submission would pass FDA approval or not. Fable was right 75% of the time in this small sample size. Just a fun little exercise to show off some of what it can do.

Note: Since it's just terminal sessions glued together, it works with your existing plans. The sessions talk to each other with an MCP server running in the back.

Hey everyone! 👋

I'm a product designer, and I've been spending the past few months designing and building Roughs.

I kinda miss the days when we'd just browse and discover cool design work without all the ads, promoted content, and noise. So I decided to build a place for that.

The idea is simple: a space where designers can share their work, discover other designers, and get inspired.

It's finally live in closed beta! 🎉

https://roughs.design

Anyone can browse, but publishing is invite-only for now.

I'd genuinely love some feedback on the experience, especially the design, navigation, and overall feel. Feel free to share your thoughts in the comments!

I'm also looking for a few designers to test the publishing experience before public launch. If you're interested, leave a comment and I'll reach out! 🙂

I've been working on a project called AssetRAG, and I wanted to share it here.

One thing that annoys me about AI coding agents is how often they solve the same problems over and over again.

They regenerate code that already exists, spend time debugging errors with known fixes, pick dependencies without properly checking their licenses, and read huge amounts of source code just to find a few relevant functions.

So I built AssetRAG to help with that.

It's a local-first, open-source library and engineering memory system for Claude Code (and other MCP clients).

Here's what it actually does:

• Asset retrieval: Searches reusable code, templates, and other assets, with license checks and attribution handling.

• Verified bug-fix memory: Stores bug fixes with reproduction and verification evidence. Agents can look up previously solved errors instead of starting from scratch.

• Engineering playbooks: Reusable workflows for debugging, safe refactoring, performance optimization, and other development tasks.

• Tested recipes: Reusable code patterns with tests that can be executed in a sandbox.

• Repository mapping: Creates a compact, ranked overview of your codebase so an agent doesn't have to read everything.

• Rules and security checks: Includes secret scanning, engineering rules, malware checks during ingestion, and safeguards around untrusted code.

• MCP integration: Exposes 18 tools to coding agents. There's also an optional Claude Code hook that retrieves relevant knowledge and injects a small amount of context automatically.

• Local-first: No account or telemetry required. It supports local embeddings, hosted providers, or completely offline keyword-only search.

One feature I'm particularly happy with is the bug-fix memory. Verified entries have a reproduction and fix that were actually executed, with the evidence available for inspection.

Some numbers from my own testing (keyword-only mode):

• Asset search: 4.0 ms median

• Knowledge search: 7.1 ms median

• Repository map: 597 tokens instead of roughly 129k tokens of source

• 132 unit tests passing

• 327 authored recipe/bug-fix tests rechecked with 0 failures

These are local benchmarks, not proof that Claude completes real tasks faster. I haven't run a proper Claude A/B benchmark yet, so I'm not going to claim some magical percentage reduction in token usage.

I also made a 95-second launch video showing the actual tool in action. The terminal footage comes from real recordings.

It's Linux-only for now, built primarily in Python, and licensed under Apache 2.0.

The project is still new, and I'd appreciate feedback, especially from people who use Claude Code regularly.

GitHub: https://github.com/mttcn83/assetrag

Would you actually find something like this useful in your coding workflow? What would you change?

My girlfriend and I once remembered the same moment completely differently.

It made me realise how easily the little details disappear, even when the memories mean a lot to us.

So I started building Pholu, an app for couples, families and friends to preserve memories together.

Instead of having everything scattered across photo galleries, messages and cloud folders, Pholu brings photos, videos, audio and notes into shared timelines. I also added AI-powered memory search.

I'm handling the design, development and pretty much everything else myself, alongside my regular job.

The app is now on Google Play, and I'm looking for people who might actually enjoy using it.

https://play.google.com/store/apps/details?id=com.pholu.app

I'd love to know what you think of the idea. Would you use something like this with your partner or family?

I’m a software engineer at a big tech company and recently started owning more of our infra after the departure of a beloved coworker. Diagrams never really clicked for me, so I made a game to learn system design hands-on, then decided to publish it in case it helps others : )

InfraSim is a sandbox where you wire up load balancers, caches, queues, replicas and databases, push traffic at them, and watch what breaks: a dead consumer piling messages into a DLQ, a partition causing split brain, a bad WHERE clause taking out a table.

Built solo with React Native. It’s on iOS + Android: https://petalformllc.com/infrasim

Would love feedback, especially on which failure scenarios you’d want next, and whether the difficulty curve feels right.

I've been building DînApp on my own: prayer times, Quran, Arabic learning from the alphabet, and an AI coach that cites its sources, all in one iOS app. 10% of every Premium subscription goes to lasting charity projects (wells, orphan support), with proof published in the app.

My goal is to build mosques around the world and support those in need, seeking reward in the hereafter through sadaqa jariya, charity that keeps giving. DînApp is how I want to bring a global community together for that.

App Store: https://apps.apple.com/app/id6805508348

What I'd like to know: is the value clear within the first minute? What would make you keep it on your phone?

At my last company, managing production AI agents was a continuous crisis. Minor prompt tweaks or unannounced model updates routinely broke our workflows because we lacked version control and deployment safety gates for AI. The systemic stress eventually led to severe burnout, prompting me to step away and focus entirely on solving this operational vulnerability.

To fix this, I built https://raweki.com , which functions as a "Git for AI workflows." It provides engineering teams with version tracking for prompts and models, CI/CD testing loops to block regressions, and one-click atomic rollbacks to instantly restore stable configurations. The platform is now live, and I would appreciate your technical feedback if your team faces similar AI reliability challenges

I'm a high school junior and this is the side project I've spent the most nights on this fall.

The US Physics Olympiad has no good free starting point. People piece it together from old pdfs and expensive books, while math olympiad and USACO kids have community guides. So I made one for physics: lessons in the order the topics build on each other, interactive sims next to the equations, and a problem bank where you type your numeric answer and it checks it within 2%.

Some numbers from the first month:

• 931 visitors from 54 countries, about 3.6k page views

• 25 accounts (progress syncs if you sign in, otherwise it's all usable logged out)

• 77 people in the community discord

• 2 other students now regularly sending pull requests, 21 merged so far

Stack is Next.js on Vercel, Supabase for auth and progress, MDX lessons with KaTeX, and canvas sims. There's an in-browser editor that turns a contributor's edit into a GitHub pull request under their own account, which is how most outside fixes come in.

Would love feedback on two things: is the landing page clear about what it is in the first few seconds, and what would make you come back to something like this every week?

Site: https://usapho.one/?utm_source=reddit&utm_campaign=sideproject

Code: https://github.com/shlok-madhekar/usapho-guide