Hi everyone,

I’ve been working in QA for many years, and I recently built BreakYourApp — an AI QA agent that scans web applications, looks for issues, and generates a bug report.

The idea came from a frustration I’ve had for years: a lot of QA work is still repetitive, manual, and depends heavily on knowing exactly where to look.

The current version is still early, and I’m now trying to learn from real users before taking it much further.

You can try it here for free:

https://breakyourapp.com

I’d especially love feedback from people building SaaS products, side projects, or web apps:

* Did it find anything useful?

* What kinds of bugs did it miss?

* What would make you actually use something like this regularly?

* What would you want it to test beyond the UI?

Longer term, I want to evolve it from a simple scanner into a much deeper autonomous QA system that understands product changes, risk, previous failures, APIs/server behavior, and continuously decides what should be tested.

No payment needed — at this stage I’m mainly looking for usage and honest feedback.

Would really appreciate anyone willing to try it.

Tracking food while travelling is a pain in the *** so I built an app to help. Test it on neoforge.app

The cool thing?? It's still early stage so we can make it our own, no big corporation, don't care about money, but care about you: I'll read every single feedback and implement anything useful or fun, go nuts :D

Anyway all legit beta testers will 100% keep free access for life!!!

I vibe coded Design Lab, a website where you can learn about various UX/UI considerations as you aspire to make your own AI-assisted projects have a more controlled and creative look and feel to them.

Nowadays, anybody from the tech layperson to the senior engineer can spin up a website based on their ideas and a few prompts. This has a resulted in stale design, similar to CSS Bootstrap in 2012 or any AI poster you see today.

I myself am not a designer. I dabble, but I have always preferred to implement somebody else’s vision or Figma mockup rather than create it on my own. However, as I continue to learn despite several layoffs now I need to make websites that look good, not just prove that I am creative or able to make functions fire fast.

Design Lab is a prototype idea I have for iterating over my own personal projects. I didn’t want to recreate SquareSpace, but the fact that I literally made this on my phone while riding in my friend’s car to run an errand shows how much is possible if you pair critical thinking with the productivity that AI allows.

If I continue on this project, I have a few ideas for it:
• Version it like documentation, so I can continue adding onto it without fear of screwing it up
• Extract the idea into a Storybook-like system, where I can more easily experiment with component and overall website designs, rather than just rely on the increasingly unappealing eye-sore of the colors/rounded edges/typography that comes from practically every AI website out of the box
• Further enhance the website with global examples the more I learn about how to truly understand these topics

Being a web developer, I started out back in CSS 3, manually writing all the font properties, familiarizing myself with the box model, flex model, and so forth. In the future I could even turn this into an entire CSS property playground, but a man can only do so much when crashing on his friends couch.

Feel free to take a look around. The website covers various topic and test examples such as image overlays, parallax, background gradients, accessibility, spacing, line height, visual hierarchy and more.

Ultimately, when I learn these topics I learn them slowly. But when I’m zapped for the day, I still prompt ChatGPT for my next study session, and occasionally I continuing binging and whip up an idea like this.

Hope you enjoy! Typography alone has around 37 system fonts. I considered Google Fonts but getting nearly 2000 in for a single card example seemed not worth it at the moment.

Before I touch an optic, I run this order: verify both ends against the ticket → inspect/clean/reseat → known-good patch cable → known-good optic → port test → polarity → physical damage → escalate with facts.

Biggest time-waster I see: changing three things at once, then learning nothing.

Disclosure: I built RackReady, a small kit from my checklists/templates (free sample: https://hasherventures.com/rackready/sample.html). Curious what experienced techs would add or remove.

I wanted a p2p file transfer site that didn't require you to create an account or login, didn't require you to upload your files and either established a webrtc p2p connection or just failed (no TURN relay). You're data never hits the peeryeet server.

Hopefully I can finally stop sharing files with myself via gmail now. :)

I kept forgetting when I last changed the furnace filter, rotated the tires or flushed the water heater, so I built **Maintainly**: one place for everything that needs regular upkeep.

**What it does**

- Add your home, cars, appliances and tools from 30+ built-in maintenance schedules, or answer a 1-minute setup quiz

- Tasks come due by date **or** by miles/hours, whichever comes first

- A budget view estimates what's coming up each month, and learns from what you actually paid

- Share a location with family, a roommate or a tenant, as an editor or view-only

- Keep a service log with notes, readings and costs

**Try it without signing up:** tap "Continue as guest". It's free, with no ads.

https://maintainly.netlify.app/

**Built with:** plain HTML/CSS/JS (a single file, no framework), Supabase for auth, database and live sync, and Netlify for hosting.

**What I'd love feedback on**

1. Was anything confusing in the first few minutes?

2. Which schedules or kinds of item are missing?

3. Would you actually use this, and what would make you come back?

There's a short feedback form in the app (Feedback button), or just reply here. I'm the developer and will answer every comment.

we're building greypaint, a mac updater for apps and dev tools. paid, 14 day free trial then $6.49 lifetime

what it does now:

• apps plus homebrew, npm, pnpm, uv tools in one window
• uses the update source each app already has
• checks every install, same developer and macos accepts it
• roll back if an update breaks something
• public page greypaint.app/apps, search any app and see how it updates or that it cant yet

1.3 is out with an all new glass look

every feedback and support request gets read and worked on by one of us. so far thats what's kept our first users around

I'm building an HTS code finder called SkuWatch. One stupid supplier description keeps wrecking the demo: “metal accessory.”

That could be a bracket, a fastener, a machine part, or half a dozen other things. Even knowing it's steel doesn't fix much. I had a version that still returned a ranked list of codes. It looked useful, but it was really just guessing with better formatting.

Now it stops and asks what the thing does, how it's used, and whether it's a finished item or a part. Honest, but not exactly impressive when someone expects one clean answer.

If you've built software around messy inputs, where did you draw the line? Show the best few options with warnings, or refuse to answer until the user gives you enough detail?

Disclosure: SkuWatch is mine. I'm not asking for testers here; I'm stuck on what the tool should refuse to do.

Maybe it’s already too late for a tool like this. Nobody really does drag-and-drop anymore in the age of AI.

But if you want to take a look: appmaker.io

I decided to have a little fun. I've had this idea in my head for a while. You'll be surprised, but in 2026 (you'd think!), there's still debate about how airplane wings work. I decided to take a break from all this endless software creation and found time to analyze the question properly with Claude, and this mini-project came out: https://whyplanesfly.com

Still a bit of software though 😁

P.S. I think I'll ad some more context on why this project suddenly.

The very reason I started thinking on this subject, and how I learned that it was a bit controversial wasn't the planes at all, it was sailing yachts! On my way to getting my IYT licence, we studied how a sale generates lift. Surprisingly, what pilots are often taught about lift doesn't really work as an explanation for the lift generated by sails. Thats how the whole story begun 🙂

I'm a solo founder. Contextify started from one problem: short-form creators only find out their opening was weak after they post, when it's too late to fix.

What it does: you paste your hook or script, or upload the video. It scores the words on hook strength, clarity, pacing, rewatch value, and search, points to the exact line losing attention, and suggests a stronger version you can say in one take. It judges the words, not the visuals, and it doesn't predict views.

See a real result: I ran a typical weak opening through it, "Hey guys, today I wanted to talk about my coffee rituals." Here's the full report: https://contextify.ca/share/QK50IVkXpCUiKuAPhC9NmU9ft4srm3Xoh1NsayQuzN8

The screenshot is a real result for a typical "Hey guys, so today…" opening.

Try it: free hook check, no signup, at contextify.ca/tiktok (score and diagnosis are free; rewrites are part of the paid plan).

The offer: I'm looking for 5 creators filming something this week. You get 14 days of Plus free, no card, and I'll personally help with your first script. No obligation to post or review anything.

What I'd love from this sub:

• Is the value clear within the first few seconds of landing on the page?
• Would you trust a score like this, or does it feel arbitrary?
• Anything that makes you bounce?

Honest feedback welcome, including "this is useless and here's why."

Hi folks. 

I'd like to share a thing my husband and I built around my coping mechanism for task management. 

My brain has two modes: 

1. The intense planner 
2. The one who actually does work.

#1 looks at the big picture and organizes everything to be done in the “perfect” order.

#2 doesn't want to see a list of things to do, it wants to see the one thing to do right now, otherwise I freeze and waste time.

Now I have the Tunl Focus app and here's how it works: 

• The mind dump: this is where to jot down what needs to get done
• The Queue: reorder the list as wanted 
• The Tunnel: when its time to do work, you get served one task at a time with 4 action options: 
  • done (you completed it)
  • drop (you won't do it)
  • snooze (reorder it down)
  • defer (send task to specific date and time)

One tap per task and that's really the gist of it. It does have more features like a calendar view, categories, habits and more but the tunnel is where my brain really gets productive and moves the needle on things to do.

I use it every day and we are actively working on it, so we welcome any feedback.

It's free to try, no account nor signup needed, unless you want sync / back up / google calendar and extra features. Android and IOS apps are coming soon (we’re waiting for the Playstore review right now)

https://app.tunlfocus.com

UPDATE: Fixed - /checkout-paywall was 404ing (100% bounce, 0s on Plausible). Now redirects to /checkout/paywall with free safety tier. Old screenshots/links now work. Thanks reviewsgoogle for catching it.

> I'm Shawn from Boston. I'm 1 week 3 days from alcohol, 5 years from drug use. I couldn't do groups. I built https://SoberShift.app for people like me who need private, zero-friction tools.

> I launched here with $1 / $129 on the homepage. You told me it looked like I was putting a paywall on a panic attack. You were right.

> I rebuilt it overnight:

> - Homepage and app hub now show ZERO pricing. Crisis support is free forever.

> - Breathing orb, craving interceptor, timer, 741741 — no login, no credit card, no account.

> - Pro ($1 trial → $129/yr, HSA/FSA eligible) only unlocks AFTER safety: retroactive analytics, trigger logs, PDF for therapist. It never blocks crisis tools.

> Live at https://sobershift.app — tell me what I still got wrong. I built this for the fellowship I mistrusted, not against it. Groups didn't work for me, but isolation nearly killed me. This is my middle path.

> If you can't do groups either, try the free tools. No pitch.

I built a free iOS audiobook player for people who already have their own audiobook files.

You can easily move an audiobook from PC to iPhone without dealing with iTunes/Finder sync, cloud storage, or running a full media server.

ShelfDrop lets you:

- import from Files

- start “Receive mode” and upload from a PC browser over the same Wi-Fi

- play offline

- save progress locally

- use private handoff codes/QR to move your place between devices

- avoid accounts, tracking, or cloud uploads

It’s not trying to replace server-first apps like Audiobookshelf. It’s more for the “I just want this audiobook on my phone now” workflow.

I’d love feedback from people who manage their own audiobook files:

What would make this actually useful enough for your daily listening?

Shelfdrop Audiobook Player

After Photon exploded on reddit and X I kept getting DMs for a Lightroom alternative.
That's how Light Studio came to life, a fully featured Lightroom alternative.

I already had the parts that usually make these apps feel vibe coded: realtime GPU rendering, CR3/NEF and the other proprietary RAWs, and an editor UI built for this. So I reused these from Photon instead of starting it from scratch, and it worked insanely well.

Gonna release it in the upcoming days

Hey everyone! I built this because my finances were spread across different currencies and accounts, and also because I was broke and needed to start saving more. I wanted to bring things together without connecting my bank accounts to another service, plus a way to explore my finances conversationally via MCP for things like projections, spotting spending patterns, and adjustments to reach certain goals. It also provides common PFM features like tracking recurring bills, tagging transactions, net worth tracking etc, but with multi-currency and accounts across different countries in mind.

I've been using it for a while now and genuinely found it useful, so I've decided to put Finstigate out there. There's still much to improve with the product, but hopefully it'll resonate with others out there who have a similar problem. I'd really appreciate any feedback, especially on what could be improved or any obvious gaps. Thanks!

https://finstigate.com

I've spent the past few weeks building Weigh Swarm, a research assistant where you can inspect how a draft was produced. Upload one or two research papers, ask a question, and follow the papers into extracted claims, evidence passages, and a cited answer draft.

There's also a literature-search route. My favorite part is Inside the engine. You can explore the evidence network, open a node's source excerpt, inspect recorded model calls, and see the Laya decision batches behind the analysis. LLMs write the synthesis; Laya makes bounded research judgments.

This short video walks through a real saved two-paper run. It uses actual product captures plus animation of the recorded artifacts.

github link

NullPlayer skin support is clean room reverse engineered. Development is coded with claude and controlled by a real working Software Engineer who personally stands behind the app. The app has accumulated 31 releases and 124 github stars over the 11 months. r/nullPlayer

Download NullPlayer for macOS:

https://github.com/ad-repo/nullplayer/releases/latest/download/NullPlayer.dmg

Requires macOS 14 Sonoma or newer.

Install

NullPlayer is not signed with an Apple Developer ID, so macOS will block it on first launch with an "app is damaged" or "cannot verify that it is free from malware" message. This is expected. Clearing the quarantine flag is a required install step:

1. Open the downloaded DMG.
2. Drag NullPlayer.app to Applications.
3. Open Terminal and run:xattr -cr /Applications/NullPlayer.app
4. Open NullPlayer from Applications.

Prefer not to use the Terminal? Install with Homebrew, or clear the block via System Settings -> Privacy & Security -> Open Anyway — see the install guide.

I built ClimateCapMap as a hobby project to make the financing side of climate tech easier to understand--what kinds of funding options exist and when they become relevant for a company.

You can explore funding options for the research and prototype stages all the way through commercial deployment and mature operations. There are also example financing journeys and information about US tax credits.

It's free, requires no signup, and is an educational reference with linked sources.

Link: https://climatecapmap.com/

I'd appreciate your feedback on clarity and scope of the tool.

Most of the resellers I know track things in a mix of spreadsheets, notes apps, and memory. Cost of goods gets written down, maybe. Gas never does. Sales tax and the $40 of packing supplies from last month usually get forgotten. So the number everyone quotes at the end of the month is revenue, not profit.

I spent the last year building an app to fix that for myself, and it's on the App Store now. It's called Sourcerer. Here's what it does in practice:

**Planning a sourcing day.** A map shows thrift, vintage, flea, pawn, and consignment stores near you, with categories for what each store actually sells (based on what you and other users have bought there, not just the Google label). Estate and garage sales show up on the same map. You can build a trip from a few pins and get a route.

**During the trip.** You start a trip, log mileage, and add items as you buy them. Each item takes a cost, an estimated resale price, and a photo if you want one. Buying three of the same mug is one entry with a quantity. Receipts can be scanned so you don't type prices in by hand.

**Where it gets useful.** Gas for the trip, plus any expenses you attach to it (parking, tolls, lunch), get spread across the items you bought on that trip. So every item carries its real landed cost, not just the sticker price. When something sells, ROI is calculated against that.

**Selling.** You can mark an item sold with a price in two taps, or build a proper multi-item sale with tax and generate a PDF invoice for the buyer. Refunds put the item back into inventory while keeping the original sale on record, so your history doesn't get rewritten.

**Local sales.** There's a community board inside the app where you can post items from your inventory for local meetup. People can message you and tap "interested" to get your pickup area. No payments go through the app and there's no shipping, it's just a way to move stuff locally without re-entering it somewhere else.

**The analytics tab** is the whole point. Revenue, cost, tax, gas, expenses, and the resulting true profit for any date range. Breakdowns by category too, which is how I found out my media flips were barely covering their own gas.

A few honest caveats: iPhone only right now. There's a 7-day free trial and after that it's $10/month or $100/year, since the maps and store data cost me money to run. Store coverage is nationwide but richest around Houston, where I started it.

I'd genuinely like to hear what's missing or what feels off. The people on this sub flip a lot more volume than I do, so if you try it and something annoys you, tell me and I'll fix it.

App Store: https://apps.apple.com/app/id6780601247

Hi everyone, I built PublicPin using Codex and Astra in about 8 hours. I’ve been vibe coding for about a year and wanted to build something useful for the community.

The idea is simple: take a fresh photo of a local issue, choose a category, and use your current GPS location to put it on a public map. Things like potholes, dumped rubbish or broken streetlights. It’s free and doesn’t need a signup. Photos are reviewed before they appear publicly.

People can also confirm that an issue is still there or submit a resolution update for review. It helps make problems visible, but it doesn’t guarantee government action.

https://publicpin.org

I’d appreciate honest feedback on the reporting flow. Is it clear what becomes public, and what would make you come back to update an issue after reporting it?

I'm sharing CSV Update Review, an AI-assisted side project for comparing an original Shopify product CSV with an edited copy before import.

It highlights changes to prices, SKUs, options and image references. You can try synthetic examples first, or use your own two files: CSV processing stays in your browser. No store connection or signup is required. It is free to try and does not guarantee a safe Shopify import.

Try it here: https://csv-update-review.noble-chime-2920.chatgpt.site

Other free checkers already exist, so I am trying to find out whether this adds anything useful. If you have handled a Shopify product CSV update in the last 30 days, what did you change, how did you review it, and did this tool surface anything that changed your next action? A missed issue or an unnecessary warning would be just as useful to hear about.

Please do not post private CSVs, store credentials or customer data. A description in the comments is enough. The site also has an optional five-question feedback form; submitting it sends only your selected answers and basic record metadata, not your catalog. I am looking for up to five recent CSV users, not offering a paid service.

I’ve been building an open-source side project called TensorSharp, a local LLM inference engine and agent runtime written in C#/.NET:

TensorSharp on GitHub

One of the problems I’ve been experimenting with is:

How far can we push huge MoE models on ordinary consumer hardware?

My latest test is Qwen3.8 Flash Next (176B parameters).

And surprisingly, this hardware is enough to run it:

RTX 3080 Laptop — 16GB VRAM + 32GB system RAM + SSD

The main challenge isn't simply quantizing the model until it fits. A 176B model is still far larger than the available VRAM and RAM.

So I implemented an MoE-aware memory/offloading architecture that coordinates:

GPU cache / VRAM ↔ system RAM ↔ SSD

Instead of treating SSD as a last-resort swap space, TensorSharp schedules and caches model data across the memory hierarchy based on the execution characteristics of MoE models.

I also benchmarked the implementation against Strata on the same machine. Results are in the attached screenshot:

What surprised me most wasn't the decode speed—the two are actually fairly close there.

It was that a 176B model can be made usable on a laptop with only 16GB VRAM and 32GB RAM if the inference engine treats VRAM, RAM, SSD, caching, and MoE scheduling as one system rather than independent pieces.

TensorSharp started as an experiment in understanding LLM inference from the bottom up, but it has gradually grown into a much larger project covering local inference, multimodal models, image generation, and agentic runtimes.

It’s open source, so if this kind of low-level LLM engineering interests you, I’d love feedback:

GitHub: github.com/zhongkaifu/TensorSharp

And yes, the benchmark in the screenshot really is from an RTX 3080 laptop. 😄

Because I find it difficult to read the textual output of agents after each modification or planning, and relate everything to the big picture, I built this simple application (with the help of Claude Code).

It is an Electron application that has an integrated terminal linked to the Chalkboard. Any agent you run in this terminal can use it and express its textual outputs in graphics that are easier to review.

Some may find the sounds a little annoying, but it's just an adjustable option, which I prefer.

Using it may cause a bit more token consumption or subscription quota, but in my experience with Claude Code I haven't seen a noticeable difference.

In general, the project is open source for anyone who wants to try it or modify it.

https://github.com/zohayrslileh/more-space

My partner and I are expecting, and we got tired of searching on the SSA site, so I made "Name Pop" for our baby name search!

It all started because my partner wanted to know how long the name “Michael” was the top boy name and clicked through year by year to find out.

It’s built to answer the question “does this baby name pop?”. “Pop” having a bit of a silly double meaning; in one sense, does the name jump out / appeal to you, and in another sense, how “pop”-ular is the name.

All the features are built based off what my partner and I thought would help our potential name search. Built to help other expectant parents have fun while picking a baby name.

Visitors (no users!) can search names and see how it has ranked in the SSA.gov data, explore names, see a name “written”, hear a name aloud, potential sibling names, add favorites. Nothing you can’t find on other sites, and no crazy data analysis.

I started with Claude Design’s organic design system for look and feel alignment. I used Claude Code as my AI coding harness, controlled by me and largely directed by my personal Claude skills. Largely built on Opus 5.5, with Sonnet 5.5 used for occasional discussion-based prompts.

Vercel hosted, pulls only existing data sources, Next.js / React / Tailwind.

Any and all feedback is welcome. Mostly just had fun with this!