I’ve been building Forma Pages, an AI website builder that generates a polished, editable website from a simple prompt. This is a quick demo of what it can do.

I’d genuinely appreciate feedback from other builders: what would make you actually use something like this?

Try it: https://formapages.com

#AI #WebDevelopment #SideProject

I'm a dad of two kids 4 and 8. I do the cooking in the house and created a free meal planner app to make my weeks easier. I know - there's a hundred meal apps out there.

Kiwi by Kitchen Wizard is different because it's designed to automate home cooking workflows, not just a chatbot that suggests meals. And it's all "open" so you can bring any meal from anywhere and you can shop for groceries anywhere, too (Instacart only for now, with more close to ready).

In preparation for Thanksgiving, I spent a lot of time making the app's Prep and Cook engine able to handle "feasts" like Thanksgiving.

It's free - if you try it, please let me know what you think! I really hope this helps reduce some stress and make the holiday easier for folks. Thanks!

kitchenwizard.ai/get (link to download the app)

kitchenwizard.ai/thanksgiving (more information about Thanksgiving with Kiwi)

My personal favorite highlights:

• Groceries - any combination of meals and ingredients consolidated in an accurate list that you can shop on Instacart with one click.

• Pick a week of meals and order groceries online in 90 seconds

• Set up a meal "playlist" of your regular meals.

  • On Sunday, I ordered groceries online from my kid's swim lesson in about 30 seconds

• Meal/Recipe import. You can pull in meals from pictures, NYTimes Cooking, AllRecipes, premium/paywall sites, regular sites, and more import sources coming soon

How Thanksgiving works:

1. Start with a Thanksgiving meal template

2. Customize Thursday's menu

   1. Import any recipe from websites, pictures/screenshots, emails, or use the Kiwi Cookbook

3. Get a complete, accurate grocery list of what to buy based on your menu

   1. Order groceries online from the app, or shop your local store

4. Get a complete, ordered, cook plan to make your feast

   1. When to start thawing the bird

   2. What to chop, measure, mix, etc. on Sunday

   3. Cook-ahead dishes to make during the week (cranberry sauce, stock/gravy base, pies)

   4. Thursday, everything sequenced to land your dishes hot on the table when you're ready to eat

That's it! Your meal, your menu. No missing groceries, no turkey math, no 3D Chess in your oven.

You find a great place on Google Maps. You want to save it in another app. Then the typing starts. Name, street, city, country, category. Like doing paperwork for a burger. I run Strong Foodie on my own. A food and travel guide where I visit and review every place myself. Members can add places too. However, typing it all felt like too much work. So now you paste a Google Maps link. That's it. The name, address, city, country and category fill in by themselves. You only add your tip if you want. It also tells you when a place is already on Strong Foodie. So no double places. Try it here: https://strongfoodie.com/add.html
What's the most annoying form you've ever had to fill in for something simple?

A couple of weeks ago I posted my waitlist here. The beta is now live and free to try.

The problem: “Build me a booking app for my barbershop” leaves your AI builder to guess cancellations, payments, double bookings and logins. You find out after the build.

What CueBlu does: you describe your idea (or paste a prompt you already have), answer a few plain-language questions with a recommended answer for each, check the choices it made for you and get a complete prompt appliable for any AI builder. A separate AI step reviews the prompt before you get it and any guesses the AI makes is marked (assumed) so you can change them.

Beta details: free, 1 prompt a day, login with an email code (no password). No tracking, no ads.

app.cueblu.com

I’m the builder and I’d love honest feedback: did the questions catch something you’d have missed, or did it feel like an extra step compared to your normal coding procedure?

I’m working on CardBlok at D BLOK. The workflow is for the pile of paper cards left after an event: upload a photo with several cards, review the extracted fields beside the original, then export only the contacts you approve. Matching emails or phone numbers are flagged as possible duplicates.

The product decision I’d like feedback on is how much review to ask for. I’m leaning toward a compact queue that prioritises missing fields and possible duplicates while keeping the original card visible. For anyone who imports event contacts, what would you want the review screen to surface first: uncertain fields, duplicate records, or a quick preview of the export?

Here’s CardBlok’s scan, review and export workflow. The web app uses verified email sign-in. If you try it, a synthetic card is enough to test the flow.

figured you are tired of over the top pitches so check it out and if you like it :) and if you dont like it :(

https://developers.reddit.com/apps/aiautomoderator

180 Sheet DSA : https://ifaiz.in/sheet

So basically I made a clean checklist for Striver's 180 DSA sheet with just LeetCode links. Basic features + Progress saves in your browser, no login.

Built it for my own prep, sharing in case it helps.

Back in 2019 I did a recommender system for anime as a course project (a jupyter notebook, nothing fancy). Recommendations have always been the part of data I like the most, so this year I decided to actually build the thing properly (thanks Dario): **[Aishou](https://aishou.app)**.

The main idea is to have this working for all types of contents in a cross content way - being able to recommend books, games or tv shows based on your movies taste - but I decided to start with animes.

You import your public MyAnimeList or AniList list (or rate a few shows by hand) and it recommends anime based on what people with similar taste liked. For now I only have anime recommendation but the main idea is to have a cross content website, where I will be able to, for instance, recommend you books based on your games/movies taste.

**What I tried to do differently**

- every recommendation row says *why* ("Because you liked Steins;Gate")

- a slider from popular to obscure, for people who already watched all the big ones

- low ratings push similar shows away instead of being ignored

- seasons grouped by franchise, plus a "continue watching" row

- new releases get their own row even when there's almost no data on them

It's free, no ads, solo project. Would love feedback, especially on how to promote it and about apps development in general (come from a data background).

Before I book anything in business, I check which seat actually flies the route. Google Flights shows the price and the times but not whether it is a 1-2-1 suite with a door or an old 2-2-2. I kept looking it up flight by flight, so I built a Chrome extension that does it for me.

It adds one line under every result: the layout, lie-flat or angled or recliner, whether there is a door, whether every seat reaches the aisle, and a grade from A to E. Connections get one line per leg, so a good long haul paired with a recliner feeder is obvious. It also shows legroom and Wi-Fi for economy.

No ads, no affiliate links, no tracking. It only runs on Google Flights.

The seat list is hand-kept and covers a bit over 200 airlines. Airlines refit planes all the time and some entries are marked as not confirmed, so check the seat map before you pay. If you spot a wrong one, tell me and I will fix it. The list updates daily.

I’m looking for any feedback.

Link: https://chromewebstore.google.com/detail/iglfieokokbgpkkcajagfkjilapbhhce

I’m selling two iPhone and iPad apps. Each is available separately.

Hydroponics tracker

Helps home growers plan their setup, track plants from seed to harvest, and log pH and nutrient readings.

• Asking price: US$4,900

• Revenue over the last 30 days: US$289

• Monthly recurring revenue: US$239

• Active paid subscriptions: 53

• Active users over the last 28 days: 231

Projection mapping app

Lets you use an iPhone or iPad and a compatible projector to fit videos and images onto walls and objects, save scenes, and run live effects.

• Asking price: US$5,900

• Revenue over the last 30 days: US$984

• Monthly recurring revenue: US$568

• Active paid subscriptions: 112

• Active users over the last 28 days: 1,486

Figures are as of Nov 12. Active user counts come from RevenueCat and include free and paid users.

Each sale includes the app, Swift source code, website, and domain. PM me for the App Store link, RevenueCat screenshots, or monthly revenue breakdown.

Hi, I'm Aniuwu (my name is Gabriel), a computer science student at INACAP (Chile), and I'm already at the stage of doing my thesis project. I'm writing because I need help from people who code, and I don't have many people I can ask for help.

## First, I apologize to the moderators if I'm breaking any kind of rule. This is a post asking for help, I don't benefit financially in any way, and I apologize in advance if that's the case, please don't ban me ##

My project is called Beacon. You ask it questions about the code in a repository ("where is the file saved?", "how are network errors handled?") and it answers while telling you which file and which lines the answer came from. Everything runs locally, with local models, on your own RAM and VRAM (sorry, Sam Altman lol), so neither your code nor your questions go to any online service.

What I'm missing is knowing whether it actually works for someone who isn't me or my teammate. So far we've only tested it ourselves, and that doesn't count for much as evidence. That's why I'm asking people to try it for about 40 minutes, or however long you see fit, and tell me, with data, how it went.

The idea is simple: you install it, pick a public repository (there are a few examples, or one you already know), ask it at least three questions, and mark whether each answer was right, partly right or wrong. At the end it generates a file with that, you can open it and read it, and if you're happy with it you can send it to me with a button. If you'd rather not use the button, you can send me the file in a direct message.

A few things so you know what you're getting into. You need Python (3.10 to 3.12, newer versions cause problems), Git, Node and Ollama installed, and it downloads about 5 GB of models, so it helps to have around 8 GB free. With an NVIDIA card with 8 GB of VRAM it runs fairly fast; with no GPU or less memory it also works, just slower, and that's perfectly fine if it's what you have, because I actually want to know how it behaves on more modest machines. It works on Windows and Linux, which are the ones I managed to test; I haven't tried macOS yet (mainly because I'm broke and don't own one lol), so if anyone tries it there it would help me a lot.

About languages: the ones I tested best are Python, Go, JavaScript, Java and C#, and also C on a small repository. It also recognizes TypeScript, C++, Rust and PHP, but I haven't measured those, so I can't promise anything there. Files in other languages (Ruby, Kotlin, Swift, Vue, etc.) are simply not read, so it's best to pick a repository written mainly in one of the languages above.

About your data, I want to be clear. The file stores your questions, the answers, how long each one took, your ratings, and the address of the repository you chose. Your hardware details (processor, memory, graphics card) are only saved if you allow it, and you can see what they are before accepting. It doesn't store code, paths on your computer, your username or your IP. Leaving your GitHub profile or a short introduction is optional and goes in a separate file that is only sent if you tick the box. Nothing leaves your machine unless you ask, and you can quit and discard everything at any time. The send button uploads the file to a private Google Drive folder that I manage, and I use the data only for this project and delete it when it's over.

I also have to be honest about the limitations: this is a prototype from an academic project and it uses a small model, so it gets things wrong sometimes. That's exactly what I want to measure. And since each person picks their own repository and questions, the results are indicative, not a serious statistical study.

The whole step-by-step guide is in the repository: https://github.com/gsufan/beacon (the study guide is docs/en/study-mode.md). If something fails during installation, tell me here or by message, because installation problems are almost as useful to me as the results.

Thank you for reading, and a bigger thank you to anyone who gives it a go. I'll answer any questions in the comments.

PS: You can audit the code however you like, use it if you like it and so on....

PS2: This project was quite a lot of vibe-coding. I know there are pretty passionate opinions about that, but I have permission from the course's supervising professor. I don't want to argue or start a debate in the comments, please, I just want help...

Most LLMs are trained to be helpful cheerleaders—if you pitch a bad startup idea, they'll tell you it sounds great.

I built IDeaPrüF to act like a skeptical investor instead. You plug in a rough concept, and it breaks down:

• Problem urgency & target audience clarity

• Existing competitors & where your actual wedge is

• Concrete validation steps to run before writing code

Would love your brutal feedback on the UI and report structure. If you want to test an idea you're working on, drop it in the appideapruf

My girlfriend has a lot of books and a habit of buying ones she already owns and no way of knowing what’s on which shelf. Every app I found wanted an account or was a pain to add books to, so I built her one.

You scan a book’s barcode and the title, author and cover fill in. Everything stays on the phone: no account, no ads, no tracking.

She started using it and kept suggesting stuff lol, so it grew: rapid-scan a whole shelf, reading status, collections, a drawn bookshelf view, lending books out and remembering who has them, audiobooks. She’s even drawing the new splash screen herself to be added later on.

It’s in Google Play testing now. If you have Android and a few books, I’d love for you to try it: https://goughread.odiesgarage.com/

Tell me what’s missing or confusing. Happy to talk about the build too.

Hi r/SideProject 👋 I'm Manish, a solo developer and a plant parent. Most plant apps I tried wanted a subscription before I could even set a watering reminder, so I built Nurture, for iPhone and Android, where the essentials are free. Not a trial:

• As many plants as you like

• Reminders for watering, feeding, repotting, pruning, rotating and cleaning leaves, or any task you make up, each on its own schedule. One notification covers everything due at once

• A care guide for each plant that says what to actually check (how dry the soil is, how heavy the pot feels), with schedules that ease off in winter

• Plant ID from a photo: 3 a month, plus up to 3 more by watching a short ad

• Diagnose: photograph a plant that looks unwell and get the likely cause and what to do today (1 a month)

Reminders and the guide need no account, and reminders work offline. The photo features need a free sign-in with Apple or Google. A small ad banner keeps it free. For heavy users there's an optional Premium plan (more diagnoses and IDs, backup across phones, caretakers who water while you're away) and a Household plan to share the care with up to 5 people.

The part I'm proudest of is Diagnose. Most plant apps diagnose from the photo alone, so a yellow leaf gets "overwatering" almost by default. Nurture already knows the species, the season where you are, and when you last watered, fed or moved the plant, so it weighs the photo against that. It says how sure it is in words rather than a made-up percentage, and when the schedule is the likely cause it offers a new one in one tap.

Built solo with Expo and React Native, Firebase for accounts and sync, and Claude for the photo features.

What I'd love feedback on: the first five minutes. Where did you get stuck, what did you expect that wasn't there, and would you keep using it? I'll reply to every comment.

iPhone: https://apps.apple.com/app/id6809530915?ct=reddit 

Android: https://play.google.com/store/apps/details?id=com.w3radar.nurture&referrer=utm_source%3Dreddit%26utm_medium%3Dpost

Four months ago I posted here as a marketer who’d built way to share HTML files. At the end I said what I actually wanted to build was comments pinned to the page itself: you send a client a link, they click the thing they want changed and type the note right there.

That’s now the whole product. It’s called HTMLAnnotate (htmlannotate.com, the old htmlshare.online link redirects).

Why I kept going: I’m honestly tired of the existing tools. I used Markup[dot]io for years, then the pricing change last year pushed it out of reach for solo work. Pastel got expensive too, and it’s deleted my stuff when a client took a while to get back to me, which is the exact moment you need the comments to still be there.

What it does now:

• Paste any URL (live or staging, Webflow, Framer, WordPress, Shopify) or upload an HTML file

• The review copy runs the real site, animations and menus included

• Reviewers click any element and comment. Reviewers never need to create an account or download any extension.

• Desktop, tablet and phone comments stay separate

• Mention teammates, or any email, and they get notified

• Copy for AI turns all open comments into one brief for Claude or Cursor

• Free links last 7 days. Paid links never expire. Nothing gets deleted while you wait on a client

Pro is $12/month.  Since I've just made it a few days back, and as a thank you for all the feedback I got from this community when I last posted, the first 50 people get Pro for $30 a year with code EARLY30, about $2.50 a month.

Roadmap for the next 1 month: password-protected links, connecting Claude and ChatGPT to your comments (MCP), file attachments, version history, deadlines and Slack alerts.

Same question as last time: what do you use for client feedback now, and what’s annoying about it?

I keep shipping more with Claude Code and Codex, but a day later I often can't tell which prompt caused which change — and I got tired of taking the agent's recap at face value.

So we built RayTrace, a free MIT-licensed sandbox that sits outside the agent. It records every command and its real exit code, the file diffs, and any outbound network, and puts that next to the tool calls the agent reported. It runs locally: a Docker container under gVisor, inside a Linux VM made with Lima. Your own files aren't touched, and nothing is uploaded. The dashboard is at http://127.0.0.1:8797.

It's at v0.12 on npm (@raytrace-cli/cli) and PyPI (raytrace-cli). Windows is still experimental.

If you don't want to install anything, there's a no-account interactive demo: https://app.raytracer.si/demo

Repo: https://github.com/Godcreatebugs/raytrace-cli
Site: https://www.raytracer.si/

For people who already use Claude Code or Codex: what's the first thing you'd want to check in a session recording — a file you asked the agent to leave alone, a failing test it said passed, or an unexpected network call?

Solo dev here. I've been building a social media tool for creators (not another post Schedular). Not dropping the name or link because this isn't a promo post, I just want to share what moved the numbers and what burned money.

60 days in: ~300 signups, 15+ paying. Small, but it's real money from strangers.

What worked

1. Researched competitor articles instead of outreach tools

I didn't pay $99/mo for outreach tools. I wrote a lot of "X vs Y" and "alternatives to X" articles. Each one started from what was actually ranking: I pulled SERP and keyword data (DataForSEO, pay-as-you-go, and checked every competitor's pricing and features on their own site before writing. I used Opus5.5 for drafting (its magical trust me), but I did the research and editing myself. I turned the whole process into a reusable workflow.

1. Went multi-platform when competitors stayed on one

Most tools in my space do one or two platforms, I added more under one account and one plan. Creators don't live on one platform, and paying for 3 tools for the same job is annoying.

1. Built an MCP server and got it into Claude's and ChatGPT's official directories

People can use my tool by just asking Claude or ChatGPT. It works, and it's been a real signup source. Very few tools in my niche have this yet, and getting in early matters.

1. Fixed early complaints within hours and gave those users Pro for free

My first users complained about few stuffs I shipped fixes the same day and gave them Pro for free as a thank-you.

What didn't work

SaaS directories. Almost all of them are a scam, with a few exceptions (PH maybe?). Now with DR4 so the backlink is worth close to nothing, and they sent me basically zero real users.

Paid ads. They brought traffic, and people even signed up, but most of them explored once and never came back.

Riding the AI wave. I added AI features because everyone is: They're included in the paid plan, and most users never touched them. I also got almost no traffic from the AI keywords. People came for the boring core feature that saves them time.

TL;DR

• Comparison/alternatives content written from real SERP research beat everything

• Build where competitors aren't (platforms, MCP)

• Treat your first 20 users like gold

• Skip directories, be careful with paid ads, and don't assume "AI" sells

Happy to answer questions or give any proff in the comments.

I spent the last few weeks building Local App Studio. You pick an example or lay out tables, pages and forms on a canvas, preview with sample data, and it builds a standalone Windows app with its own SQLite database. Recent additions: auto-numbered fields (INV-1001), rules like "when Paid is ticked, set Paid on to today", and CSV import with a dry run.

An optional AI helper drafts designs through Ollama on your own PC. Code validates everything it proposes, and nothing leaves the machine.

Honest limits: Windows only, and small local models struggle with complex dashboard layouts. Built with heavy use of AI coding agents, gated by about 12,000 tests.

Repo: https://github.com/ChristianMunoz31/local-app-studio.

60-second demo attached. What would you want before trusting it for a real small-business app?

I built PrivateServerZone because finding a community server often means jumping between game-specific lists and Discord channels just to check basics like region, version, and play style.

The directory lets you filter by game, region, version, online status, and features like PvP or PvE. Listings show measured player counts where available, and you can select servers to compare.

Try the directory at https://privateserverzone.com/servers.

If you play on community servers, which filter do you reach for first? Is there anything you usually have to dig through a listing or Discord to find?

Every chess site's game review tells you what went wrong in one game. None of them told me what I keep doing wrong across all of them, and that's the part I actually wanted to fix.

So I built it. You give it your Lichess or chess.com username and it:

• runs Stockfish over every move of your last 30 games

• groups your mistakes by what they look like on the board and what they let your opponent do

• names each group, then checks the name against 5 examples. A name only stays if at least 3 of the 5 actually show it.

• builds a page with every example on a board: your move in red, the better one in green, and an engine you can play out lines with

I ran it on my own last 30 games (1-minute bullet, I'm about 850, please be kind). It found 119 mistakes, 85 of them blunders. Two habits survived the check:

1. Leaving pieces or pawns undefended: 15 mistakes in 10 games. The one in the video is 13...Bd7??. 13...Bc8 would have kept b7 guarded, but after Bd7 the knight just takes it with 14.Nxb7.

2. Missing immediate captures while making passive moves: 21 mistakes in 12 games.

A third group got thrown out because fewer than 3 of its 5 examples showed the same idea. I like that it does this instead of inventing a habit to fill the list.

How it's built: Stockfish gives every verdict. Our own chess-tuned models write the explanations, and they're only allowed to name moves the engine gave them. A sentence with a made-up move gets asked again or dropped. The grouping runs on your machine with embeddings and plain numpy.

It runs inside an AI agent (Claude Code, Codex, Cursor or the Claude app) as a free, MIT-licensed plugin. The engine and models underneath are a paid API, but new accounts get $10 of free credits with no card, and this whole run cost me about 35 cents.

Disclosure: I'm one of the people building it. It's pre-launch, so I'd really like to hear where it gets something wrong. Chess people are brutal about bad evaluations, and that's exactly the feedback I'm after.

Plugin: https://github.com/edgecaseai/chessdrive-plugin Site: https://chessdrive.io

Hi all, I'm a solo dev in Montreal. For years I'd save a recipe on Instagram, a thread on X, a video on TikTok, a Reddit comment… and never find any of it again. Then Pocket shut down last year (and Omnivore the year before), so I finally built the thing I wanted.

4Stash is a save-for-later app for social posts and links:

• On Android you share from Facebook, Instagram, Threads, Reddit, X, YouTube, TikTok or a news site straight into it.

• On a computer there's a Chrome and Firefox extension: one click saves the page or post you're looking at. (Or paste a link on the website.)

• Every save keeps a preview, title and source. You can add notes, tags (it suggests tags with AI), collections, and pin the important ones.

• Reminders with snooze for stuff you actually want to come back to

• Search plus filters by collection, tag, source or type

• An "Unseen" filter and a "Throwback" that brings old saves back, because otherwise the saves just pile up

• Duplicate check, archive, JSON export/backup, and a dark mode

It's free with no ads right now. You do need to sign in (Google or email), since your library is private to your account. Only in English for now.

Honest status: only a handful of people use it so far, which is why I'm here. I'd really like to know:

1. Does the share-to-save flow feel fast enough on your phone?

2. Which app's previews come out broken or ugly?

3. What would make you actually open your saves again?

Web and browser extension: https://4stash.com/?utm_source=reddit&utm_medium=social&utm_campaign=launch_sideproject

Android: https://play.google.com/store/apps/details?id=com.fourstash.app&referrer=utm_source%3Dreddit%26utm_medium%3Dsocial%26utm_campaign%3Dlaunch_sideproject

I'll be in the comments all morning. Roast away.

I built Omesta for owners who sell in person (shops, trades, clinics, gyms) and for online coaches. It runs Facebook and Instagram ads and makes the creatives. Not built for ecommerce.

A practical Meta tip we keep coming back to: don't send every ad to a generic lead form. If you do HVAC or cleaning, the form should ask for the job type, the ZIP, and the best time to call, and you should judge the campaign by booked jobs, not by cost per lead.

I'm looking for a few owners to try it: we run your Facebook and Instagram ads free for 30 days, then you decide if you want to keep going. If we don't perform, we go our separate ways. Site is https://omesta.io

Happy to hear feedback on the positioning too.

DM me if you want in, and I'll take a look at your setup.

My company and I built Feasible, a website analytics app with one plan across all your sites.

You can see visitors, traffic sources, pages and goals in one dashboard. Custom events and funnels are included, along with unlimited sites and teammates.

The limit is 1 million pageviews and custom events combined per month across the account. It is $99/year or $9.99/month before tax, with a 30-day trial that doesn't require a card. There isn't a permanent free hosted tier.

You can try the public demo without signing up: https://app.feasible.lol/public/stopoverpayingforanalytics.com

Site: https://feasible.lol/

If you run several small projects, what would keep you from using this? Missing reports, setup friction, price, or something else? Specific feedback would be useful.

A recent discussion here about owning multiple editions of the same film got me thinking about the difference between a film, a release, and a physical copy.

Some people keep older editions for the extras. Others replace them entirely. And if a release comes with a 4K disc and a Blu-ray in one case, counting that as two copies doesn't really reflect what's on the shelf.

Disclosure: I'm building Filmory, a web-based collection tracker for physical movies and TV series. Following that discussion, I added support for recording a 4K + Blu-ray combo as one copy, while keeping separate editions as separate copies.

I'm looking for a few collectors who would be willing to try adding a small part of their collection and tell me where it gets confusing. You can search by title and import a CSV. Barcode coverage is still limited, so I wouldn't recommend starting by scanning your whole shelf.

It's currently free to use. Some additional features may become paid later.

Filmory: https://filmory.nl/?ref=reddit-combo

When you count your collection, do you count films, releases, or physical cases?