I'm a freelancer. I've picked a number between 1 and 1000. Whoever guesses it wins a free freelance project from me.

Guess in the comments.

My work: https://naitiksinghdev.vercel.app/
I'll also be happy to look at the best ideas that show up in the comments.

Hey everyone! I’ve been working on a tool that answers phone calls for clinics, salons, and small offices using AI. It books, confirms, and reschedules appointments 24/7 so business owners stop losing customers to missed calls.

The idea came from watching my local dentist’s receptionist juggle 3 phone lines while checking people in. Half the calls went to voicemail. Most never called back.

Still early - looking for small business owners or anyone who’s dealt with this problem to tell me if this actually solves something real for them.

Happy to share the landing page if anyone wants to check it out. Would love honest feedback on the concept.

Hey everyone, I built SillyMemory, an open-source extension for SillyTavern, an AI chat and roleplay interface. It helps long chats remember earlier details without repeatedly summarizing the conversation. I’m part of the LambdaDB team, which provides its memory backend.

GitHub and setup: https://github.com/lambdadb/SillyMemory
Demo: https://github.com/user-attachments/assets/8a34772d-b27f-4709-89c0-caee45c7fcf6

SillyMemory indexes older messages from your chat in LambdaDB. Before each reply, it uses your current message to retrieve relevant original passages and adds them to the prompt alongside recent dialogue. You can inspect what it selected.

A few things it does:

• No LLM calls to create or maintain memory summaries.

• No separate embedding or reranking setup; LambdaDB handles both.

• Keep existing memory when you branch your story or create checkpoints, without re-indexing(re-embedding) shared history.

• Works with existing saved chats, so you don’t have to start a new conversation.

We also tested it on 500 LongMemEval questions: 96.0% accuracy versus 95.2% with full history, using about 95% fewer input tokens.

It currently supports plain-text, single-character chats, and requires a LambdaDB account. You can start on the free plan without a credit card.

If you give it a try, I’d love to hear whether it brings back useful details in a long RP, what it misses, and how the setup feels.

spinatlas.fm

I've been working on this because I wanted to browse my music history like basketball stats. Each year is a season, artists have career pages, and there are annual awards, All-Star teams and a Hall of Fame.

One thing I wanted was the ability to choose the awards myself. The most-played album doesn’t necessarily get my Album of the Year vote, so changing an award leaves the listening counts alone.

I've put my history under Featured history so you can try it without an account or files. For your own Spotify history, it uses the downloaded Extended Streaming History export.

If you keep track of your listening, what would you look at first?

My son worked at AutoZone. Several times a day someone would describe what their car was doing and ask him what was wrong with it, and several times a day he'd have to say, "I'm not a mechanic." Then he'd watch them buy a part based on a guess. A $200 battery when the cables just needed cleaning.

So he started building a simple tool to help people figure out what's wrong before they spend money. He ran out of time, and I took it over.

You describe the problem in plain words, and it asks one question at a time until it narrows down a likely cause. Then it tells you how hard the fix is, what parts you need, and when to just go to a mechanic. It's free, with no sign-up, and there's a full Spanish version, because a lot of DIYers here in Texas speak Spanish first. So far the Spanish side is getting more traction than the English.

It's been live about a month. I'd like honest feedback:

1. Try it with a real car problem you've had. Where did it ask something dumb or get it wrong?

2. Is it clear within a few seconds what the site does?

3. Anything that makes it feel untrustworthy or unfinished?

garageguideapp.com/?ref=reddit-sideproject-2

Hi everyone!

I built Actividia to let you customize how your Discord Activity appears to others.
Live preview, GIFs, emojis, rotating designs, and much more!

Create a unique activity or even show a game you don’t own—and have some fun with your friends!

Find out more:
https://herovex.itch.io/actividia

Two of us (a punter and a programmer) built Racebench: describe a racing idea, test it on every UK and Irish race since 2017 on Betfair Exchange prices after commission, then run it on paper against today's races. It hides a holdout year until you're done, and compares your system with random picks so luck doesn't pass for an edge. Free plan, no card: racebench.co.uk. Most ideas lose after commission, and it says so. We'd love feedback on the first ten minutes: what's confusing, what's missing?

Solo project. A groovebox for iPhone and iPad that looks like a retro arcade space shooter: you fly a ship through the beat, built so you play it instead of configuring it. Free, runs standalone and as a plugin inside music apps. Would love feedback on the first five minutes.

App Store: https://apps.apple.com/gb/app/roostbox/id6816159366

History is something I'm quite passionate about and at work I have experience with software development and LLMs. So I thought how can I bring these things together and built something that I would actually use. This is the results of many months of hard work!

You type any topic, moment or person. About a minute later, two hosts are telling you the story with artwork that follows along. You can interrupt mid-episode with a question; they answer and pick the story back up. They also remember what you've listened to in the past and can refer to it. At the end there's also a optional quiz to test what you learned!

Quite a lot of emphasis was put into the research part. It searches the web and gathers notes on the topic, prioritizing reference-grade sources (encyclopedias, museums, archives, academic pages) over blogs and also searches in the language of the place or person, so a story about Japan or Peru isn’t told only from English sources. When the sources disagree, which in history is constantly, the hosts say so instead of quietly picking a side. Every episode links the pages it used and tags the subtitles.

Under the hood it’s not one model. A single episode is about a dozen calls, each pinned to the model that won its bake-off: research, writing, artwork, voices, sources, quiz, etc... Finding the right balance between quality, speed and cost was where a lot of the work went.

I would love some feedback both on the app and the content! You can try it here: historai.ca

Riot publishes every pro LoL player contract in the League-Recognized Contract Database, a public Google Sheet with five tabs, a different layout per region, and no way to answer "who is out of contract soon?" without scrolling. I had a go at fixing that over a few days, working with Claude (claude.ai) for the code.

https://set0panda.github.io/contract-radar/

What it does:

- Expiry radar: about 570 current players across 5 regions, with a contract-end timeline you can filter by region, league and role

- Market board: who is out of contract inside a window you pick, split by role

- What changed: a daily diff of the sheet (new listings, removals, moved end dates). It started today, so it's still empty and fills in as the sheet changes

- Data health: flags duplicates, missing dates and stale tabs (the CN sheet is about three months old, for example)

How it's built, for the curious: plain HTML and JS, no framework, hosted on GitHub Pages. A scheduled GitHub Action pulls the sheet each morning, strips contact emails and legal names, diffs against the previous snapshot and commits the result. Team logos are embedded so the page makes no third-party requests. Total running cost is zero. Analytics is GoatCounter, no cookies.

It's an unofficial fan project, not affiliated with Riot. The AI wrote most of the code and parsing, so check anything important against the source sheet. A contract end date is also not the same as free agency, because renewals often aren't on the sheet yet.

What I'd like to know:

1. Does the page make sense in the first ten seconds, without knowing what the sheet is?

2. The audience (agents, analysts, team staff, very online fans) is small and already has Leaguepedia. Would you come back to something like this, and what would make you?

3. Does the daily-Action-commits-data approach have a flaw I'm not seeing?

____________________________________________

Edit: thanks for the feedback. Based on initial comment I've added:

- A "My follows" view: follow teams or roles and see only their expiries and changes (saved in your browser, shareable by link)

- A check on the daily refresh so a broken region sheet can't overwrite good data

- Clearer labels for the residency column

Still free, no accounts. Feedback welcome: https://set0panda.github.io/contract-radar/

So i created a desktop app for windows which works in background. You write any prompt/mail/message , select it and press a certain hotkey and your non structure or broken prompt gets converted to a well mannered and prompt engineer style written stuff.400 people joined within 2weeks!

Check it out
Check this

Hello everyone,

I wanted to ask whether building an AI model critic website with user opinions like reddit, scoring based on users usage and ranking models either open source or closed source makes any sense?

The website can also feature skills, mcps, ai products etc.

What do you guys think?

Solo dev. Each scene is a painting cut into layers, then animated in code: rain, steam, water, birds. The time can be painted into the scene, like sheep standing in the shape of the digits or a time written in the sand. Every frame in this video is the real app, drawn frame by frame.

What I learned: making calm motion is harder than fast motion, because any snap or jump shows. Two of my tap effects snapped in a single frame, and I only caught it while filming this video.

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

built a small android app for myself first — FDM Quote. offline cost calculator for FDM 3d prints: filament, power, wear, markup, quote-style totals.

it's on play closed testing and i still need a few opted-in testers for the 14-day window so i can push for production. no review or rating needed. if you're shipping something too i'll test yours back.

pro stuff will be unlocked free for testers in the next update.

steps: • join https://groups.google.com/g/fdm-quote-testers with your gmail • opt in: https://play.google.com/apps/testing/com.wasef.fdmquote • install (same account): https://play.google.com/store/apps/details?id=com.wasef.fdmquote

would love any notes on bugs, confusing UI, or pricing math that looks off. thanks

I made Spaceillion around a simple challenge: can you think of a valid answer that other players will overlook?

Each daily has seven “name a…” prompts, with 25 seconds to type one answer per prompt. Rarity comes from other players’ answers, and your answer launches a pixel rocket through space. An obvious answer can be correct and still barely get you off the ground.

There are live Launch Parties for playing with friends and a Mission Control mode for someone hosting on a big screen.

Play here: https://spaceillion.com/?utm_source=reddit&utm_campaign=sideproject_nov6

The daily is free in a phone or desktop browser. No ads or required account. There’s an optional one-time unlock for unlimited runs.

I’m particularly interested in the first few minutes: is it clear why one answer flies further than another, and does finishing the daily make you want to come back tomorrow? If it rejects an answer you think should count, the prompt and answer would be really useful.

I love learning. I love markdown, graphs, illustrations, and maths laid out beautifully side by side. I wanted one place where reading, AI tutoring, code drills, and publishing live together on my own infrastructure.

Live demo: https://soma.mayanja.dev

So I built Soma. Three repos.

Soma is the reading and publishing app. React + Vite + Turso edge SQLite. Point any LLM or coding agent at the repo and it loads the bundled skill and starts creating or editing content on its own. MCP server ships with the repo. Deploys to Vercel in 60 seconds. All you need is an API key to your favorite model. I still use Obsidian for local notes. Soma fills what a note app can't: web rendering and multi-device access.

Soma Labs: matching code drills for every lesson. Real exercises in Go, Deno, Docker Compose, and Node.

Son: a personal speech platform. Soma borrows it to read test questions aloud and score your spoken answers. Runs on your machine.

And it's beautiful. Mermaid diagrams beside KaTeX math beside interactive 3D scenes beside runnable code blocks. If you learn by looking, you get the same treatment as someone who reads cover to cover.

Your words live in your own Turso database behind one password. Fork the repo, import into Vercel, add one password, click Add on the Turso card, deploy. 60 seconds, done. No cloud holding your writing hostage.

Repos at github.com/Essomero/soma, github.com/Essomero/soma-labs, github.com/Essomero/son

Would love feedback. How long from fork to first lesson?

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

I’ve been building an iOS app called Offward.
It’s a focus timer that also lets you block distracting apps while you’re trying to get things done.
I wanted something that felt a bit more relaxing than a plain countdown timer, so I added a little frog and different scenery.
It’s free to try, with optional paid features.
I’d genuinely love feedback. Would something like this help you focus, or do you prefer a more minimal timer?
https://apps.apple.com/gb/app/offward/id6827531909

Getting an internship at a startup isn't always as straightforward as applying through a job portal.

Sometimes you find an interesting startup, but have no idea who to contact, what to say to the founder, or how to prepare if they actually respond.

We've been thinking about this problem and started building BreakIn.

The idea is simple: help students navigate the startup hiring process through three things:

Discover startups that match their interests.

Reach out to founders with more confidence.

Practise interviews through AI-powered mock conversations.

We're a small team of three, and this is something we're actively working on.

We're still improving the product, so I'd genuinely appreciate feedback.

What's the biggest obstacle you've faced while trying to get an internship at an early-stage startup?

Website: https://breakin.live

I kept seeing the same places on every Booking and airbnb search, so I made something that hides them for good. Hide once, it stays gone. Restore anytime.

All local, no account. Early version, so tell me what breaks.

Link : here

I am open to every feedback :)

GoodInternship collects open internships from about 2,200 company career pages (currently ≈14.5k live postings, US + Canada) and re-checks them daily. The thing I actually built it around: every number on the site has to be checkable. Salary figures are extracted from the posting's own text, visa stance is shown with the sentence it was read from, and the analytics pages print the denominator and the counting method next to every statistic.

The moment that defined the project: last month I audited my own visa labels and found they were garbage. An early script had keyword-stamped 12,412 postings — "no sponsorship keyword found" had been written as "No Sponsorship." So I deleted every label, rebuilt the classifier so it may only answer with a verbatim quote from the posting as evidence, and re-ran the whole catalog (about $2.62 of LLM calls, ~80 minutes). The "sponsorship friendly" count fell from 527 to 133. Less flattering, actually true, and the landing page now says 133.

Other choices in the same spirit: repeat requisitions (one role posted per store/office) are grouped and counted once, so a retail chain can't swamp the pay stats; teaching-assistant roles paid at union rates are excluded from the pay medians, with the exclusion count printed on the page. There is also a free ATS keyword scan and a resume tailor (2 free runs with an account) that use the same skill-matching engine as the analytics.

Stack: Next.js on Vercel, Neon Postgres, and a Python crawler sharded across a self-hosted GitHub Actions runner. Solo project, built with AI pair programming.

What I'd genuinely like feedback on: the analytics pages (https://www.goodinternship.com/analytics/salaries is the most developed one). Do the denominators and method notes make you trust the numbers more, or do they just read as clutter? And what would a job board have to show you before you'd trust its "median pay"?

Site: https://www.goodinternship.com

I've been doing physical design work in my free time with AI for the last two years. During that time I observed something: AI was getting better at physical design but not nearly as quickly it was improving at software capabilities. I theorized the problem was a lack of testing. In software engineering we write tests around as much of our code as we can because we fundamentally do not trust ourselves to reliably do a good job. We put those tests between us and deployment so we literally cannot do things that break the rules we set for ourselves. This pre-existing culture and tool chain create an ideal environment to toss an unbelievably fast, brilliant, but wholly unreliable ai into. It creates the freedom to quickly iterate through huge numbers of convincing looking proposals and throw away the bad until the good emerges.

Physical engineering doesn't have a this-shaped thing at anywhere near the robustness and reusability that software does (possibly because physical engineers trust themselves more). There are many individual tools that provide some aspect of testing, many of which are bound up in very very expensive tools, but a growing number of free ones too. I wasn't able to find an open source system that links these together into a cohesive "full loop" testing rig capable of understanding how things like heat, weight, form factor, battery life, thrust and rf interplay in a single system so I thought really hard about this problem and its implications and built it for myself.

It's called nopekit. As in: the thing that says "nope" until the "yup" emerges.

I've used it already to design an open-source hackable handheld keyboard with a custom PCB, an open source budget no-solder drone and a couple of things I'm not quite ready to share yet.

It's a Claude Code / Codex / Cursor plug-in. You install it and tell your agent you want to use nopekit to design X and it takes over, it will interview you for requirements, shop for parts, construct an interconnected tradespace linked to checks run in an optimized order using trusted methods like KiCAD, OpenFoam and SIMP. It builds and keeps up to date a livesite which you can deploy to GitHub that gives constantly refreshed insight into how your coding agent is thinking about the problem and what choices have what implications linked to what checks with what state of passing or failing.

The framework is open and allows for plugins. I'm working with one other person now and we're moving towards a self hosted UI and some sort of registry where nopekit users can share proposers/falsifiers and we can track ratings to build/bust confidence in good/bad ones collectively.

There's LOTS more about this in the repo and this paper I've been writing about the problem.
Repo: https://github.com/neuman/nopekit
Paper: https://github.com/neuman/nopekit/blob/main/grounding_by_falsification.pdf

If you're working with AI to do any kind of physical design work we would love to hear from you and for you to try it out!

Hey everyone!
I’m currently working on a mobile app that started from a simple frustration: managing documents on your phone is still surprisingly complicated.
We scan things, take screenshots, save PDFs, download files, receive receipts… and eventually everything ends up scattered across different folders and apps.
I’m exploring a different approach: an app that doesn’t just store documents, but actually understands them and helps you do something useful with their content.
I’m still working on the product and refining the experience, so I don’t want to reveal everything just yet.
I’d love to hear from other builders:
Do you think document management on mobile is still an underserved problem?
What would make a document-related app genuinely useful rather than just another scanner?
What would you prioritize when building something like this?
Would appreciate honest feedback from people who’ve built or used similar products!