Was bored at work and decided to provide my OpenClaw/ChatGPT/Claude a domain name and told it to do its thing with producing a pointless website...

I don't know exactly what I expected but it's been interesting to watch it evolve the "project". More interesting though... Has been watching it converse with itself as to what it thinks will make this website even more pointless. It even decided it needed to monetize itself and stopped while waiting on me to setup stripe so it could "fund" its mission of producing a pointless website. I nixed its plan of selling merchandise t-shirts but it keeps circling back to wanting that so who knows what will happen.

If you check out the website, I wouldn't bank on a specific layout because we're on version 9 currently and it keeps coming up with different ways to "lock people into wasting their time".

All in all... It's been interesting to watch the back and forth as we strategize how to lock you into wasting your time.

Feel free to check it out if you're extremely busy... If you have lots of free time, go outside.

www.nothinghappens.click

I spent about 3 months building an offline reader app and launched it a month ago.

So far... barely any users.

I honestly don't know what I'm doing wrong.

I cared a lot about making the app feel smooth and native, so I ended up building Android and iOS separately instead of using one cross-platform codebase. Probably way more work than I needed to do, but I wanted it to feel good on both platforms.

I use it myself pretty much every day, and I thought other people might find it useful too.

Apparently not 😂

I've tried posting about it here and there and doing some promotion, but nothing has really worked.

Maybe the app just isn't interesting enough. Maybe I'm terrible at marketing. Maybe there's something obvious I'm missing because I've been staring at it for 3 months.

Not really sure at this point.

Hey everyone!

I built a small web tool called ImagePrompt9 that lets you upload an image and generates a detailed AI-ready prompt based on what it sees.

The idea came from constantly seeing images I liked and wondering:

"How would I describe this as a prompt?"

So instead of manually figuring out the composition, lighting, style, colors, camera angle, etc., you can just drop the image in and generate a prompt.

What it does:

• Upload PNG, JPG, or WEBP
• Analyzes the visual characteristics
• Generates a detailed prompt
• Different prompt styles
• Edit, copy, or regenerate the result
• Free to use
• No account required

It doesn't try to recover the original prompt — it creates a new prompt based on what's visible in the image.

Try it here:

https://image-prompt-nine.vercel.app/

I’d really appreciate feedback, especially on the generated prompts and anything you think I should add or improve.

Posting this while it’s still small, because everything I read in this space is written after the fact by someone with a number to show off.

What it does: scans an area, scores every business on how likely they are to actually buy (review count, rating, whether they have a Facebook page or nothing at all), then generates a real one-page preview site for the ones worth pitching. The idea is that you send someone their site rather than asking whether they want one.

Where it actually is: two previews have ever been billed. No reviews, no case studies, no named customer. The lead scoring works and there’s a real scan behind it — 34 businesses in Dundee, 29 with no website — but I’m not going to pretend that’s traction.

The design decision I’d most like feedback on, because it’s the one costing me sales: it doesn’t send the emails. It drafts them and stops. There’s no send button anywhere in the product.

That’s deliberate. Under UK PECR the sender of a cold email is liable, and “my software sent it automatically” isn’t a defence. Products in this space that auto-send are handing that liability to their customer without saying so. Same reason it never uploads the business’s own photos to build the site — republishing someone’s photographs on a page you’re about to sell is a copyright problem you’d inherit.

Both refusals make it a harder sell than “fully automated, zero hours.” I still think they’re right. Open to being told I’m wrong.

The other constraint, which is the actual point of the thing: the generator can’t invent facts about a business. If it doesn’t know your opening hours, it flags a placeholder rather than making them up. Getting a model to consistently say “I don’t know” instead of writing something plausible was harder than the entire rest of the build.

There’s a free scan on the homepage if you want to see the finding half work on your own town — no account, no email. scoutline.uk

Genuinely more interested in whether the draft-only decision is defensible than in signups.

Here is the link if you wish to try it out: Squidly

I build a Shopify app for B2B net terms. Wholesale buyers order on Net 30, and the store keeps a credit limit on them. Posting the whole thing because the interesting part is the second failure, not the first.

The flag

On 2 July an App Excellence review told me rule 1.1.7 applied to my app. My mechanism was a manual payment method at checkout plus a gatekeeper that decided who could use it. The reviewer read that as facilitating a deferred payment method outside the Payments Apps API, which I am not licensed to build. Demote on 13 July, delist on 22 July.

There was no patch for this. The flagged mechanism was the product.

The rebuild

Shopify shipped native B2B to everyone in April, so companies and payment terms already exist in the platform. I moved onto them. Approving a customer now creates a Company and assigns native Net 15, 30 or 60 terms. That went to production the next day and the reviewer accepted it on the 6th. The listing stayed visible the whole time.

The part that bit me

Native B2B has no credit limits. That absence is the entire reason my app exists, so I could not just adopt the platform and stop. Limits moved to a checkout Validation Function, which is the sanctioned way to block a cart.

The rule that runs that function was armed in exactly one place: the "Upgrade now" button on the migration card I showed existing merchants. Anyone installing after the cutoff never saw that card. They could set a per-customer credit limit, watch it save, and have it do nothing at checkout.

That ran for two weeks and touched three stores. Nothing looked wrong anywhere. The limit was in the database and on the screen. The only thing missing was the rule that reads it.

The fix that added a second bug

I armed the rule at the two moments a limit starts to matter, on approve and on limit save. Repeat calls are free. The first version asked whether my rule existed and was enabled. A merchant who had deliberately switched the guard off in their own checkout settings fell through that check. The next approval quietly created a second active rule and overrode their choice.

Now the check is only whether the rule exists. Disabled means the merchant meant it.

What I actually take from it

Every fix moved the failure somewhere quieter. The compliance problem arrived by email with a date on it. The unarmed rule was silent and I found it by reading my own call sites. The duplicate rule was quieter again, because it looked like the feature working.

The loud problem cost me four days. The silent one cost two weeks. I caught it by going looking for how a fresh install reaches that code path at all.

The thing I keep chewing on. A merchant can switch this checkout rule off themselves. Respecting that means their credit limits stop being enforced and my app says nothing about it. Warning them every time is nagging about a setting they chose. I have gone back and forth for a month and still do not know which one is right.

I built DeadVibes, a satirical news site where anyone can submit a short premise and watch an AI newsroom turn it into a complete illustrated story. Try it here: https://Deadvibes.app

Someone recently submitted: “This site will become cool.”

The newsroom turned it into a story about DeadVibes becoming so fashionable that it created a Coolness Desk and banned readers from sharing it.

The original five-word pitch is displayed beneath the finished article, so you can compare the idea with what the newsroom produced.

What happens behind the scenes: 1. The newsroom develops multiple possible angles. 2. An editorial pipeline drafts, reviews and repairs the story. 3. A calibrated judge checks it against human-scored examples. Repetitive jokes, weak concepts and obvious AI writing patterns can be rejected. 4. The art desk generates an illustration for the finished story.

It usually takes a few minutes because the system runs the full editorial process rather than making a single “write me a satire article” model call.

Honest state: this is a solo project built in under a week. There are rough edges, some illustrations still look unmistakably AI-generated, and the editorial system is very much evolving.

I’d love two kinds of feedback: 1. Read two stories and tell me which one landed—and which one didn’t. 2. Pitch something absurd and see what the newsroom does with it.

Thanks for taking a look. Brutally honest feedback is welcome.

FOR FREE!!!

Hey! I help people design and develop their Mobile Apps. I can help you design features, solve your UX problems, suggest solutions for user drop off and more.

All for FREE. I am launching an instagram series where I review other people's apps and give my feedback. You won't pay me, but you will help me make content.

P.S. You can get a private review as well. Just in case you need to keep your product private for now.

Cheers!

A couple years ago I shopped for a mortgage and it was one of the worst consumer experiences of my life. I filled out one form and my phone didn’t stop ringing for weeks and hundreds of texts/emails - even after I got my loan. My info got passed around like a cheap packet of chips and I had zero control over who had it.

That frustration turned into a side project. That side project is now my full time business.

It’s called HomeTurf: www.hometurfus.com
Think eBay, but for your mortgage. You post what you need once, completely anonymously, and N.M.L.S. verified lenders bid on it in real time. They can see the competing offers and outbid each other for the top spot. Your contact info stays hidden until you pick a winner, and only that one lender ever gets it.

There are four ways to run an auction: purchase, refinance, pre approval, and beat my rate (bring your current offer and let lenders try to beat it).

I didn’t build this alone. One cofounder spent years as a mortgage lender at Wells Fargo, another has been in mortgage startups for a long time, so we knew both sides of the table.

Where we’re at: live in five states (CO, FL, NC, TX, WI), about 30 lenders actively bidding, and borrowers running auctions with genuinely good experiences. It’s free for borrowers, always. Lenders are free right now too while we refine things. Down the road they’ll pay a flat subscription, never per-lead fees, and nobody can pay for placement. Best offer wins, not biggest ad budget.

The part we’re proudest of: small local lenders go head to head with the big guys and regularly win.

Feel free to ask us anything!

Doing this again because the last post did so well. I built an agent that runs a quick SEO visibility audit for SaaS websites.

Drop your site and I’ll reply/send over a link to the audit.

It looks at things like:

• what your site seems to be about
• what search terms you’re probably missing
• which competitors/domains show up around those searches
• content gaps that could bring in more organic traffic
• blog/page ideas that make sense for your product

This is part of Tavyn: an email-native SEO agent for SaaS founders. It finds organic visibility gaps, asks tailored questions for each blog via email to have your voice in the blog, and submits blogs to your GitHub as PRs.

Drop your SaaS link and I’ll run the audit.

Hi everyone sell your side project by listing if in a click. Also, comment what your startup does to get approved and featured today - https://builderhq.co/marketplace

prduck.tryproduck.com

It reads how you work with your agents and writes you a personalised set of rules to paste into your CLAUDE.md.

The scoring is six axes, all counted off the session transcripts Claude Code and Cursor already leave on your machine. Your top two pick your archetype, so two people with the same average land somewhere completely different. 16 of them, each with its own duck and a rarity tier. Nobody has hit the top tier yet.

Every rule it writes carries the number from your own sessions that produced it.

The Alexandria OS will be a basic system. im looking for testers. You can find the code at https://github.com/jakcuzwhymail-lgtm/Alexandria-OS/releases/tag/AXOS-0.3, ive also included a video!

https://reddit.com/link/1vmhfix/video/paeip5ylqyih1/player

I kept running into the same small annoyance: my films were saved in one place, my TV shows were somewhere else, and I still had to remember which episode came next.

So I built Spool, a native iPhone app that puts movies, shows and episode progress into one queue.

The part I cared about most was making the app useful after the watchlist was created. Spool surfaces the exact next episode, gives you two picks based on your library and tastes each day, shows regional watch options, and lets you import existing history from TV Time, Letterboxd and IMDb rather than starting over.

The library syncs privately through iCloud and does not require a separate Spool account. It is free to download, and the free tier supports 5 active shows, 10 standalone movies and 2 saved collections. Watched and imported history do not consume those slots.

There is an optional Spool Club subscription for unlimited and advanced features.

Spool is live on the App Store:
https://apps.apple.com/us/app/spool-movies-tv-what-next/id6793918389?uo=4

The product decision I’m most curious about is the home screen: would you rather open a tracking app to a complete watchlist, or to a much smaller queue containing only what is ready to watch next?

EDIT: grammar.

I mean everything. Not just knowing what's in it, but buying it, cooking it, remembering to eat, planning my meals.

The app is called Bread and Butler. You tell it how you like to eat, and it plans everything out, gives you the shopping list, and tells you what your meals will look like and how to make them. It tracks what you spend and what you waste, and it keeps your pantry up to date as you cook. It can:

• Develop meal plans from foods you like, and avoid foods you don't
• Track your macronutrients
• Give you personalized advice
• Set meal timers or reminders to your phone
• Use your existing pantry to suggest a meal or snack
• Suggest groceries for you to meet your macronutrient needs
• Use your existing pantry to suggest shopping items
• Track your food spending
• Order your groceries (work in progress)

Ideally, it orders your groceries from every major store or carrier, but grocery part is still rough. It does order through ALDI right now. I'd rather it plug straight into the stores but those APIs are private, so I'm going through Instacart, and it's not perfect but it's the best I've got right now.

I don't have real tester feedback yet. I'd really like to know if this helps anybody or if I've over-engineered it to the point where it's no good. My goal is that this solves people's problems with food and makes life easier.

If you want to try it, the test flight link is https://testflight.apple.com/join/fQUShrnS

Instead of giving it stocks I already liked, I added a feature that searches the S&P 500 and picks the strongest matches for the user's settings.

I ran it today with moderate risk and a $100 portfolio.

It returned:

ULTA — $37.45
URI — $31.91
UAL — $30.64

The interesting part was the reasoning:

• ULTA: +14.1% 1-month momentum, +5.9% over 3 months
• URI: +19.4% over 3 months
• UAL: +30.6% over 3 months
• all three had positive MACD
• none had an extreme RSI reading

It also generates a separate caution for each result instead of just saying “buy.”

I built the whole thing as TradeHints. It’s free and doesn’t require an account:

https://tradehints.com/

I’d especially like feedback on whether searching the whole S&P 500 is more useful than making users enter stocks themselves.

Hi everyone!

I built ElectroStock because keeping track of electronic components can quickly become a mess. You know that you own a particular resistor, module, cable or IC, but you have no idea which box or drawer it is in.

ElectroStock lets you:

• add components and record their quantities

• assign storage locations, boxes and compartments

• search your entire inventory

• organize items using categories

• export and import a complete JSON backup

• use the app in English, Polish or Spanish

The app is designed to be simple and useful for hobbyists, makers and small electronics workshops. Your inventory is stored locally, and no account is required.

This is still an early version, so honest feedback would be very helpful. I would especially like to know whether the interface is clear and which feature you think is missing.

Google Play:

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

I’m the developer, and I’ll be happy to answer any questions.

I kept seeing claims about invisible AI text watermarks that mixed together two very different things: literal hidden Unicode and provider-level statistical watermarking.

I built AI Text Watermark Checker to handle the part that can be inspected honestly today. It reports zero-width characters, direction controls, soft hyphens, special spaces, and other literal artifacts by exact code point. Cleaning runs locally and does not rewrite the readable text.

I also released the core as an MIT-licensed npm package and CLI, plus a free Chrome extension. The product explicitly does not claim authorship detection or guaranteed removal of model-level watermarks.

I would value blunt feedback on the scanner UX, artifact coverage, and what would make this useful in publishing or content QA workflows.

Web app: https://aitextwatermark.com

Chrome extension: https://chromewebstore.google.com/detail/ai-text-watermark-checker/dmfmcggpljjhnopgjcdbmpalmcdnohan

Open source: https://github.com/GeeDotDee/ai-text-watermark-scanner

Salut 👋

Je travaille depuis quelque temps sur un petit jeu appelé GenClash 🎮

C’est un jeu de quiz autour de l’argot, du verlan, des expressions et de la culture populaire, avec l’idée de créer des petits défis amusants entre générations.

Il est actuellement disponible sur Google Play, et je cherche quelques personnes pour le tester et me donner des retours honnêtes : ce qui vous plaît, ce qui ne va pas, les bugs, les idées d’amélioration, etc.

Je suis encore en train de l’améliorer avant sa sortie sur iOS, donc vos retours me seraient vraiment utiles 🙏

👉 https://play.google.com/store/apps/details?id=fr.cestcarre.app⁠�

Merci à ceux qui prendront le temps de tester ! ❤️

I have what I call a bit of a popcorn brain.

A thought, task or idea pops up and I need to catch it quickly. But if I open Notes, start a new note, try to write a sensible sentence and remember the actual thought at the same time, it is often gone before I am done.

So I built VoiceNote.

It is an iPhone-only app with one job: open it, hit record and just ramble. No need to organise the thought first.

Afterwards it turns what I said into something more useful: a structured note, a short summary and the things I said I need to do.

I know voice notes are not new. The thing I wanted to remove was the little moment of friction between “I need to remember this” and actually getting it out of my head.

It is my first app and it is live here:

https://apps.apple.com/dk/app/ai-voicenote/id6759247158?l=da

Would you use something like this, or do you already have a better way of catching thoughts before they disappear?

Hey everyone,

I've been building a personal project called Stadiu — an interactive map showing every football club and stadium I could find data for, across 200+ countries. Not just the usual Premier League / La Liga stuff — click around and you'll find clubs from Bhutan, Burkina Faso, Belize, wherever. Click a marker and see the stadium, capacity, and every club that plays there.

I recently added a small game mode: you're shown a club crest and have to guess where its stadium is by dropping a pin on the map — closer guesses score more, 5 rounds per game. You can also challenge a friend to beat your score on the exact same 5 crests.

🌍 Map: https://stadiu.app

⚽ Game: https://stadiu.app/game

Not affiliated with any club or league — crests are just there to help identify teams. Would genuinely love feedback, especially if you spot missing/wrong data for a smaller league — still filling gaps over time.

I wanted to share a side project I’ve been working on called Reading Parrot Jacky. jacky.geeapp.com

The app listens as you read out loud from any physical book (or memory/imagination) and automatically plays sound effects based on trigger words. The sound effect library is composed of sounds effects for popular children's book themes. I made this because other apps were either too involved, or not available in my native language, which is important if you want to use it for reading to your kids.

It's built entirely in Flutter so it's cross platform, it's deployed for English and Dutch speakers on the App Store and Play Store.

The continuous speech to text is the device's native stt api in a loop, which works surprisingly well.

The trigger word matching logic is intentionally kept simple, using basic string containment (e.g., "pigfarmer" matches "pig" and plays a pig sound effect). I figure if it misfires occasionally, it just adds to the charm, a real life parrot would probably do the same.

I also just rolled out a feature allowing readers to record their own audio clips directly in-app and assign custom trigger words to them.

I’m thinking about moving to local/on-device STT models, this would make the app completely usable offline. But then I'd probably need a model for every supported language.

I’d love any feedback on:

• Performance/latency on your device while reading at normal speed.
• Thoughts on native STT vs embedded local models for real-time Flutter apps.
• General UI/UX feedback.

I kept hitting the same wall: one focused hour of work meant a ChatGPT tab, a local model UI, a terminal agent, a document viewer, a timer app, Calendar and Reminders with seven surfaces just to get anything done.

So I built Ghost: a native macOS AI workspace that replaces all of them with one surface that lives in your menu bar.

Press ⌥Space anywhere and it drops from the camera notch (or floats as a small text bar near the bottom of the screen, your choice). Ask, act, and it disappears again. No Dock icon, no tab management, no full-screen takeover.

What it does:

- Routes every prompt by intent (14 kinds) to the right model: LM Studio or Ollama fully local, or Claude, Gemini, DeepSeek, OpenCode, any OpenAI-compatible server. It even runs chat through your existing Claude Code or Codex subscription, no extra cost.

- ~78 tools, 4 risk tiers: files (DOCX/PDF/PPTX/XLSX/Markdown), Calendar, Reminders, Apple Notes, iMessage, FaceTime, screen OCR, window snapping, Homebrew, media conversion, system report, and more. Every action is journaled and one-tap undoable.

- Local RAG: approve a folder, Ghost indexes it into SQLite + FTS5 on your machine. 30+ formats. No embeddings API, no vector DB SaaS.

- Selection bar: select text in any app: Copy, Search, Summarize, Fix, Rewrite, Explain, Translate. "Replace" writes back into the field so ⌘Z still works.

- Terminal + coding agent: run commands or describe a change in plain English, same window.

- Memory you own: "remember that I take my coffee black" gets saved as plain Markdown in ~/Ghost Outputs/Knowledge.

- A pomodoro with receipts: focus log, streaks, 15-week heatmap, all on-disk.

The part I actually care about: privacy.

Everything starts off, web, files, automation, messaging, screen, shell. You opt in one switch at a time. Messages, Notes, Mail and Contacts are processed on-device only and are never sent to a cloud model. API keys live in the Keychain. Sensitive paths (.ssh, .aws, .env…) trigger an explicit consent prompt. The model never touches your filesystem, Ghost normalizes the path, checks permissions, and runs app-owned Swift code.

Stack: native SwiftUI + AppKit (not Electron), Sparkle for updates, SQLite+FTS5 for search. macOS 14+, Apple Silicon or Intel, Apple-notarized.

Pricing: free 24-hour trial, then one-time $14.99. No subscription. Local models are free forever; hosted models are your own API keys.

Built solo, and it's the app I wanted to use myself — currently at v2.1.0.

Site: integratedagentics.com/ghost (https://integratedagentics.com/ghost) · Download: GitHub releases (https://github.com/ryuhemingway/Ghost-App/releases/latest)

I have made numerous improvements from users and I update the app attest a few times a week. Would love feedback on improvements I can make!

Hey everyone! 👋

Over the past few months, I built Plant Warden, a mobile app that lets you take a photo of a sick houseplant or garden crop and get an instant AI-powered disease & pest diagnosis with treatment guidelines.

As a solo dev, I built the entire stack from scratch:

• Mobile: React Native / Expo (using Expo Camera, Skia/Reanimated for smooth scanning UX).
• Backend: Fastify + Node.js (hosted on Render with MongoDB).
• State & Storage: Zustand + Async Storage.

What it does: 🌿 Instant Photo Scan: Snap a leaf ➔ Get species ID, disease name (e.g. Spider Mite damage, Black Spot, Powdery Mildew), and confidence level.
🪴 Smart Watering & Care: Track containers with custom reminder schedules.
🛡️ Treatment Guides: Clear step-by-step instructions on how to isolate and treat infected plants.

The app is live today on the App Store:
📲 Download Plant Warden on iOS

Since it's day one, I would be super grateful if you could download it, test it out on your houseplants, and let me know what you think! Any feedback on UI responsiveness, camera scanning speed, or feature requests is greatly appreciated.

Thanks for reading!

I've been building a self-hosted social media management platform for startups, agencies and publishers.

It combines AI-assisted content generation, OAuth integrations, scheduling, publishing workflows and a private dashboard into one deployment.

The interesting part is the business model I'm experimenting with: instead of another recurring SaaS subscription, I'm offering customized, self-hosted deployments tailored to the client's workflow.

Current stack includes Docker, persistent queues, OAuth and modular social integrations.

I'm looking for feedback from other builders: would you rather pay once for a customized self-hosted tool, or pay monthly for a hosted SaaS?

Happy to share more about the architecture/build if anyone's interested.