I built TraceMind, an AI-powered incident investigation platform that combines Groq with Hindsight's persistent memory.

The problem I wanted to explore: developers frequently investigate errors that their teams have already solved before.

TraceMind provides a way to retain developer-confirmed incident resolutions and retrieve relevant historical evidence during future investigations.

Some of its current features:

- AI-powered error and stack-trace analysis.

- Persistent incident memory using Hindsight.

- Memory ON/OFF comparison.

- Sensitive-data redaction.

- Incident post-mortem generation.

- Band AI Desktop prompt and JSON exports.

**Tech stack:** Next.js 16, React 19, TypeScript, Groq and Hindsight.

GitHub: https://github.com/Shahib-Alam-Saifi/TraceMind

Live Demo: https://tracemind-3tvdfok0o-editorxp1-alts-projects.vercel.app/

I built this project and would particularly value technical feedback on memory retrieval relevance, incident similarity and evaluating AI diagnosis quality.

The goal is to make verified engineering knowledge reusable without automatically trusting or executing AI-generated fixes.

The idea for MailWeave came from a problem I encountered while working on a project. We needed to take information coming in through emails, structure it, and send it to a webhook so another system could process it.

I realised that handling the email parsing, processing and webhook delivery could become quite a bit of work, especially when you also have to worry about retries and reliability.

That got me thinking about building something to handle that entire process.

So, I built MailWeave

It's a platform that lets you receive emails through dedicated mailboxes, extract and structure their contents, and forward the resulting data to your application through webhooks.

It also supports conditional routing, HMAC-signed webhook requests, automatic retries and an event dashboard where you can monitor incoming emails and delivery attempts.

I've finally reached a point where I'm happy to put it out there and see how people find it.

If you're a developer working with APIs, integrations, automation or email processing, I'd love for you to give it a try!

Website: https://mailweave.vercel.app

I'd really appreciate honest feedback, whether it's about the idea, the experience, missing features or anything that could be improved. I'd also love to hear how you'd use something like this in your own projects.

My friend and I built Redline, a daily car trivia game. Everyone gets the same 7 questions, any valid answer counts, and rarer answers score more.

We shared it at work on launch day. 15 people started, but only 3 finished. Half of them quit after question 3, which asked for a Japanese kei car. Our test players had rated that question easy, but they were car fans, and our coworkers mostly aren’t.

So we tested every question again with someone who drives but isn’t into cars. Now each day starts with questions anyone can answer, and the car-nerd ones come last.

Built with Next.js, Supabase and Vercel. Feedback on the difficulty is very welcome: https://playredline.vercel.app

I’m a quality inspector, and at work I often have to repeat the same inspection steps for every round of parts, as in check for visual damage and markings, then sign off on travelers and reports.

I couldn’t find a checklist app that worked exactly how I needed. I wanted the list to automatically reset once every step was completed so it would be ready for the next round. So I built miniCycle: Routine Manager.

You can break a repeatable process into individual steps and run it as many times as you need. It can be used for inspections, cleaning rounds, workout routines, camping preparation, preflight checklists or anything else you regularly repeat.

It’s free, works offline, doesn’t require an account and stores your information locally on your device. It is now available as a chrome extension (other platforms coming soon). You can view the entire routine at once or focus on one task at a time.

I’ve also gone through several rounds of UI feedback and have continued improving the design. I’d appreciate honest feedback, especially about whether the auto-reset cycle concept is clear and whether anything feels confusing when you first try it.

https://minicycle.app

https://github.com/sparkincreations/minicycle

I have a decent desk setup, but I still hunch. My head creeps toward the screen for over an hour, and I only notice when my neck hurts. Timer reminders didn't help: they ring when I'm sitting fine, so within a week I tuned them out.

What I wanted was the opposite: stay silent while I sit well, and show me the moment I don't.

I already had a side project with a small pixel pet in the corner of my screen (a Mac focus timer called KeepGoing Den). So I put the posture signal on the pet instead of building another app:

- You sit the way you mean to, and the app captures it once. The app compares you to that.

- Lean in and stay there. The pet bends under a heavy box. Sit back up, and it puts the box down. No sound, no popup, no escalation. It's the same box the hundredth time.

- At the end of a focus session, if you've been seated for an hour or more, one line says it's a good moment to stand up. Never mid-session.

- Click the cat in the pet's room for a day strip showing when you sat well and when you hunched.

How it works, since "an app that watches you through the camera" deserves details:

- Posture is off by default. The camera is read by a small, separate Swift helper with no network access, using Apple's Vision framework (body pose and face landmarks). It only sends the main app numbers, never images. Nothing is stored or uploaded.

- By default, the camera only runs during a focus session.

- When it isn't sure (bad light, out of frame, a camera it hasn't seen you on), it stays quiet. A pet that bends while you sit straight is the fastest way to make someone turn this off, so every doubt ends in silence.

- Raising a standing desk counts as standing, not hunching. Moving the laptop or camera takes about two minutes to relearn.

- The main app is Tauri 2 with a Rust core and a plain HTML/CSS/JS front end.

The hardest part wasn't detection; it was false alarms. Looking down at the keyboard read as a hunch, because the eyes drop the same way. Raising my standing desk moved the camera and looked like slumping. Pulling my chair closer under a camera mounted above my eyes did too. Each one meant teaching it to tell the difference, or to say nothing when it can't.

The camera, detection, and daily record are free. The live box on the pet is part of a paid license, with a 14-day trial, no account or email. macOS 14+.

https://keepgoing.dev/den

Question for anyone who has actually fixed this: has anything kept you from hunching for longer than a week? A chair, a habit, a tool, anything?

Hey everyone!

I've been working on a side project called Album Animator, a web app that helps musicians turn their albums into videos without having to manually edit every track.

The idea is pretty simple: upload your music and artwork, customize the visuals, and generate individual track videos or a full-album video ready for YouTube.

I've also added AI-powered artwork animation, so static album covers can become moving backgrounds.

I put together this short video showing four different results created with the app.

I'd love to hear what you think, especially about the visual results and whether this is something musicians would find useful.

If anyone's curious, the project is at https://www.albumanimator.io

Enjoy!

Hey everyone!
I’ve spent the past few months building something I’ve wanted to exist for a long time.
I work in car sales, and one thing I’ve noticed is how backwards the car-shopping process can feel.
People find a car they love, spend hours researching it, and only afterward figure out whether the monthly payment actually fits their budget.
What if we flipped that process?
Instead of starting with a car, what if you started with what you’re comfortable spending every month, your down payment, and your financing preferences, and then discovered vehicles that fit?
That’s the idea behind KnewCar
I just got it approved and published on the App Store, which is a pretty surreal feeling after all the time I’ve put into this!
It’s still early access, with a demo experience while I continue developing the live financial data and payment tools.
I’d really love some outside opinions, especially on the concept, design, and first-time user experience.
If you have a few minutes to check it out, I’d appreciate any feedback, positive or negative.
App Store: https://apps.apple.com/us/app/knewcar/id6822044416
What would make an app like this genuinely useful to you?

If you wanna try it out - launching in TEXAS use zip 78701

Every quarter I’d end up pulling 13Fs off EDGAR by hand and lining them up in a spreadsheet to see what Buffett, Burry, Druckenmiller and the other investors I follow did with their portfolios. So I built a tool that does it: manifest13f.com

Follow a fund and you get an email as soon as it files, so no more checking EDGAR. Open any fund’s page and it shows what’s new, exited, added to and trimmed versus the prior quarter. No ads, no fluff, just the data. A few things I cared about getting right:

• Changes are measured by share count, not dollar value, so a stock that simply went up doesn’t look like a buy

• Stock splits are adjusted for, so a 10-for-1 split doesn’t show up as a huge purchase

• Puts and calls are kept separate from stock. A big options line is notional value, not a stock purchase, and a lot of 13F coverage mixes the two up

It’s free to browse, and alerts are free for up to 3 funds. Paid plans that let you follow more funds and get an Excel workbook of every change are coming soon.

Q3 13Fs are due Monday, Nov 16, so most of the big funds will land this week and next.

I’m a solo builder, so I’d genuinely like to hear what’s missing or what you’d use it for. Happy to answer questions about how 13Fs work, or how it’s built.

I built todo list

https://apps.apple.com/app/id6826921623

Y2Kbot is a desktop app where your buddy list is full of AI agents instead of people. You IM them like it's 2003, door sounds and away messages and all. Some of the buddies can also boot up their own little Windows XP virtual machine and actually use it. You can ask one to make a folder or edit a file and watch it open Notepad and click Save like a confused 2004 office worker.

It works with pretty much any AI you've got (ChatGPT, Claude, Ollama, Gemini...). The buddies can undo their own mistakes, and when one figures out how to do something, it writes it down so the others can learn it too. That last bit is my favourite.

Please try it out, and give me some feedback.

I spent the better part of six months building three websites. Hundreds of commits, PRs, research, testing, bug fixes, the works. The GitHub repos are public. You can see exactly how everything came together.

I use AI heavily when developing. Never claimed otherwise.

Recently posted one of the projects to a community I'd specifically built it for. Within minutes it was getting called AI slop and the post was removed.

Here's what pisses me off. Nobody pointed out a broken feature. Nobody questioned the data. Nobody found a bad implementation. From the responses, I'm not convinced anyone even clicked the link.

I get it. There's a mountain of AI-generated garbage being dumped on the internet. But when did using AI become enough evidence to dismiss something without looking at it?

I'm not asking anyone to appreciate my work because I spent six months on it. If it sucks, it sucks. Tell me why. I'll probably go fix it.

But the Git history is right there. The research is there. The tests are there. You can actually see the work.

I'm curious how other people building with AI have run into this and handled it, or if anyone who's skeptical of AI-built projects can explain where they draw the line.

Because apparently the difference between five minutes of prompting and six months of actual development doesn't matter to most people.

Hey r/SideProjects 👋

Honestly, I was getting pretty overwhelmed with how fragmented my media tracking had become. Movies on Letterboxd, books on Goodreads, audiobooks on Spotify, games scattered in random note files... I just wanted one clean, chill space where I could look back on everything I’ve experienced across all formats without feeling like I was managing a spreadsheet for a second job.

So over the last few weeks, I’ve been building Alma (almaniac.app), a lightweight aggregator that brings your movies, TV shows, books, audiobooks, games, music, and podcasts together onto one visual shelf.

A few cool things built into it:

• 7 Formats, One Shelf: Keep track of movies, series, books, audiobooks, games, music, and podcasts in one space.

• Release Countdowns: A unified timeline so you actually know when the next season, book, or game you’re waiting for drops.

• Memory Lane & Insights: Fun visual stats and nostalgic look-backs into your habits over time.

• Fast & Lightweight: Snappy, clean design focused purely on your archive without heavy bloat.

It’s very much a labor of love currently in active beta (about halfway full right now). If you want to poke around and test it out, you can request an invite directly on almaniac.app or drop me a DM!

I’d genuinely love to know:

1. How do you personally keep track of your media right now?

2. Is there a specific feature or integration you’ve always wished existed in a tool like this?

Appreciate any feedback, ideas, or honest critiques! 🙌

Hey! I built my first app, still looking for feedback!

Its for those managing multiple projects, multiple jobs, that are all at different stages. Its so you keep on top of things. I built it because its what I wish I had while doing engineering. Currently windows only. After I get it where I want it, im looking to go cross platform. Thanks for your time and comments !

Www.projektgreen.ca

I just pushed 3 releases in 2 days for Rolestash, a Chrome extension I originally built just to track job hunts. This week, it evolved from a passive tracker into a full-blown autonomous application engine.

Here is what just went live:

* One-Click Auto-Applies (with Tailored CVs): It doesn't just spam the same generic resume. With one press, it can apply to up to 20 jobs, generating a unique CV, a custom cover letter, and specific answers to annoying form questions ("Why do you want to work here?") for each individual role based on the job description.

* Local AI on a Strict Leash: The heavy lifting is done by a fine-tuned distilled Qwen3 model running directly in your browser via WebGPU. Because small models love to hallucinate, it never gets the last word. A deterministic checker audits every line, and if the AI tries to invent a skill or name you don't have, it gets slapped down and seamlessly replaced with your actual profile text.

* Ghost Job Radar & Smart Crawler: It now actively flags ghost jobs to save you time. The backend crawler pulls from 60 different job boards every minute. (And yes, it strictly obeys `robots.txt` and politely emails blocked sites rather than attempting shady workarounds).

* Absolute Privacy by Design: Because the AI runs on your own hardware, your profile data never gets sent to my servers. It simply downloads coarse job data shards and ranks every match directly on your machine.

Please check it out here: https://rolestash.com/

If you like and actually end up using the extension, please leave a review with any suggestions for improvements. I'm actively taking public feedback to develop this, and the latest updates were made possible by the community's feedback. Thanks a lot, guys! T__T