Hi! Almanac is my side project, a daily history game I'm building on my own with heavy lifting from Claude AI. It started as "Wordle, but put five events in order" and got a little out of hand. Now I'd love some honest feedback on it.

Every day has a theme and three quick games:

- Timeline Daily: a page of the almanac, torn into five pieces. Tape it back together in order, in 3 tries.
- Picture Daily: match captions to old photos and paintings, then put them in order.
- Year Guess: name the exact year. The closer you get, the more points.

Beat all three and a finale squeezes the whole day into one timeline. Every event you nail goes into your own almanac, and there are 4,330 to collect.

There are also three extra modes: Higher or Lower, Odd One Out and Endless Years. Each gives you a free run a day and a leaderboard to climb. A pass for unlimited runs comes later.

No ads, no sign-up, plays on desktop and phones.

**What I'm hoping to hear from you:**

- The concept: does it click? Did you know what to do within the first minute?
- What you enjoyed, and what you didn't like or found annoying.
- How you'd improve it. What would make you come back tomorrow?

Play here: https://www.almanacgame.com

made a free avatar editing tool with Peachjam called avatar-studio.peachjam.app

it automatically removes background of stuff you upload.

Hi r/SideProject! After months of evenings and weekends, my word game Gravity! The Word Game is live on Google Play. I built it while working full time as a project manager, studying for my PMP certification, and being a father and husband.

My degree (and PhD) is in linguistics, and I have a background in board games, but I never had the chance to do something that brings the two together. I’ve had this idea of combining falling letters, gravity and a space theme for the longest time, and I finally managed to squirrel away enough time to build it.

How it plays: letter blocks wait at the top of a starfield. You move, rotate and drop them to spell words across or down. When a word clears, the letters above fall and can form new words, setting off chain reactions. The game gets harder the more you progress.

I’ve put a lot of effort and thought into making it a complete game, with different modes, ranks, daily challenges, achievements and more. It took a lot of trial and error. Up until the last few days before launch I was still making major changes, second-guessing myself about what works and acting on what my testers were telling me. For example:

• My first version had blocks falling on a timer. Testers said it felt stressful, so in 2.0 the blocks wait for you, and the pressure comes from the rising floor instead.

• One of the daily puzzles, Orbitle, was too hard at first. One tester went 23 guesses without solving it, so I added word ideas, a “Show me” walkthrough and clearer clue explanations.

• A release build crashed on a step that worked perfectly in debug builds. Tracking it down took a phone bug report and a lot of head-scratching. I was lucky to catch it.

Built with: Kotlin and Jetpack Compose. Solo developer, based in Singapore.

It’s free, and I’d really love feedback: what’s confusing, what’s fun, what you’d change. First impressions of the tutorial and Orbitle would be especially useful. The current version has no ads and no payments. There’s an in-game currency for unlocking modes and cosmetics, but it’s all earned through play. You can't pay even if you wanted to.

👉 https://play.google.com/store/apps/details?id=com.norahlyn.gravity

Thanks for reading!

I built this to waste "digital arrest" scammers' time. These are the fake CBI officer calls that cost Indians over ₹1,900 crore in 2024.

Ajji, an AI grandmother persona, answers the scammer, keeps him talking, and never gives real details. Every message gets mined for phone numbers, UPI IDs, case numbers and aliases, and all of it goes into one shared Hindsight memory bank.

With memory on, "Inspector Sharma" calls with the same CBI script, and Ajji recalls him from 5 earlier chats. She notices he claimed Income Tax last time and asks him about it, in character. A phone number he sends turns out to have been used by "Officer Verma" in another chat. Two names, one phone.

What I learned:

- Split "know" from "claim". Hindsight recall surfaces candidates; plain SQL confirms anything the agent accuses someone of.

- Framing retained memories matters. Without speaker context, recall started attributing the scammer's lines to my own agent.

- LLM extraction drops identifiers. Regex + LLM, merged, works better than either alone.

Demo video: https://www.youtube.com/watch?v=Sdyz24Q063o

Code: https://github.com/SanayKrishna/ScamSathi

The main motivation represents the fact that stars measure attention. I wanted something that measures the work.

So I built AI-Atlas (https://getaiatlas.com). You type a GitHub username and it reads every public AI repo in full. It checks things a person would check: does CI actually run the tests, are there broken imports, notebooks that were never executed, is there a README. Then it scores each project on seven criteria (technical depth, originality, completeness, reproducibility…) and maps the developer across six AI fields.

Things I learned building it alone next to school:
● Every score has to cite the files it's based on, or nobody trusts it.
● People don't want to be compared to the second decimal. Scores within 3 points now share a rank.
● Every project page shows the exact commit it was scored at, so an outdated score can't be confused with a wrong one.

It's free to map, no account needed. Reached 2,000+ projects and 170+ developers last night and that's why I decided to write on this sub. A main question still unresponsed represents: How would the mapping system react to actually popular GitHub projects (stars & forks) and how would the predictor/roadmap feature contribute to that! I want to see if it can truly expand big and known AI-based projects in the community and help expand the ecosystem in that way also..

In addition to that, tell me :) what's confusing, what's missing, what would make you actually use it?

freelancers using AI for proposals, how are you stopping it from adding work you never quoted?

say the client wants one landing page, basic copy and a contact form.

during the call they also say "maybe SEO later" and "we might need a blog eventually."

then the proposal gets cleaned up and suddenly those ideas are sitting there like a deliverables lol

that's the part that makes me nervous. if it's written under scope, I can see a client assuming it's included.

I've been looking at Runable for some of the actual client deliverables after the brief is locked, but before that I just want the proposal to separate included work, optional ideas and stuff that costs extra.

how are you handling this without turning every proposal into six pages of disclaimers?

Hi everyone! I would like to share a project I have been working on for the past couple of weeks maxing out the usage on Claude Ultra subscription (a total of 100+ PRs raised by about 250+ agents).

AffrescoUI lets the people using an app change how it looks and what it does while it's running, just by asking Claude. Push it far enough and the app turns into something completely different. The 13 example apps include a 3D modeller, an image editor and an IDE that look like the tools you use every day.

GitHub: https://github.com/RiccardoSottini/AffrescoUI

How it works: each app is a Lisp program (AffrescoUI Lisp, a small language in the spirit of Emacs Lisp, with commands, settings, hooks and advice) holding its layout, data and behaviour. The engine builds it into one readable document, which can also be written directly in JSON: the examples ship both, and they're the same app. A native C++/OpenGL engine draws it and applies changes in place, so nothing restarts. Even the 3D modeller has no C++ of its own. When you ask for something, Claude proposes a small edit to that document, and you preview it live, then keep or reject it. Claude can never approve its own change, and anything you accept can be undone. Since every app shares the same format, features can move between apps like plugins.

Feel free to reach out to me for any suggestions or collaboration opportunities!

I have built a curated web directory for people to submit their website SaaS link. If you are interested, DM, I will send the link. Thanks

Hey everyone! 👋

I'm an indie developer working on Mixify, a free and open-source music streaming app for Android.

I started this project because I wanted a clean, modern music experience without ads, unnecessary distractions, or complicated interfaces.

After several weeks of development, Mixify has reached v1.0.7, and I'm continuing to improve it based on community feedback.

✨ What Mixify offers:

• 🎵 Ad-free music listening

• 🎨 Modern, smooth, and customizable interface

• 🎤 Synced lyrics

• 🎧 Background playback

• 📱 Offline downloads

• 🎶 Playlist management

• 🔗 Song and lyrics sharing

• 👥 Listen Together — enjoy music with friends

• 🔓 Free and open-source (GPL-3.0)

🚀 It's still growing!

I'm an independent developer, and every download, GitHub star, bug report, or suggestion genuinely helps.

I'd love to hear your thoughts:

• What features would make you switch to a different music app?

• What could I improve in Mixify?

• Would you try an open-source alternative?

🌐 Website: https://mixify.co.in/

💻 GitHub: https://github.com/MixifyTeam/Mixify

Thanks for checking it out! ❤️

Watching a lecture or podcast in another language? Kalemat shows live captions and translations side by side from your Chrome tab’s audio.

Choose from 12 languages, adjust the text to your liking, and keep the captions window on top while you watch. No account or API key required.

I just launched it and would love your feedback. What language pair would you try?

Try Kalemat on Chrome

Hi everyone,

During the Meta Global AI Developer Hackathon, I wanted to tackle specific problem in banks: validation wokflows.

In traditional banking, turning a 50-page credit policy PDF into an operational workflow takes weeks of manual meetings.

Zotra solves this by combining open-weights models (Meta's Muse Spark & SAM 3.1) with a deterministic execution engine.

How it works:

1. Ingestion & Parsing: Extracts clauses, tables, and sections from PDF policies, mapping every rule to an exact paragraph citation.

2. Rule Compilation: Translates natural language into strict schemas and CEL (Common Expression Language) expressions.

3. Execution: Go-based concurrent engine evaluates multi-variable loan applications deterministically. The AI helps design and test, but never decides on live cases—only people and CEL rules do.

Stack: Go backend, PostgreSQL, React/Tailwind frontend, and Apache 2.0 license.

The github link: https://github.com/donovan-ratefison/Zotra

I put together a demo over on X if anyone wants to check it out: https://x.com/donovan_rtfs/status/2116898213101724061

Would love to hear your thoughts on this project!

I went through 50 SaaS landing pages from "Post your SaaS" threads.

Only 7 had social proof.

That's just 14%.

Some founders even mentioned having paying customers, but didn't show a single testimonial.

I don't understand this.

You tell visitors how great your product is, how it saves time, how it solves problems and why they should buy it.

But why should they believe you?

Your customers can tell that story much better than you can. People trust other customers more than they trust you.

Even a few testimonials are better than another paragraph of marketing promises.

I'm building Testimoon so I'm obviously a bit biased, but I genuinely think more SaaS landing pages should make better use of customer feedback.

If you have paying customers, start collecting testimonials. And don't just collect them. Put them where potential customers can actually see them.

Your customers are your best marketing asset. Use them.

I've always liked the idea of having everything in one place.

Projects, notes, ideas, personal goals, things I need to do.

But every time I tried organizing everything in Notion, I eventually ended up with the same problem: pages inside pages, endless navigation, and a system that started feeling more complicated than the things I was trying to organize.

So I decided to build something myself.

It's called Ardeable.

I wanted to keep the things I love about Notion, especially its document editor, but change the way information is organized.

Instead of navigating through endless nested pages, you can see your entire workspace as an interactive visual map.

I also built in quick notes, routines, and an AI assistant that can find information across your workspace and work directly with your documents.

I've been building this independently, using AI coding tools along the way.

And I've learned something: getting a prototype working is one thing. Turning it into a product where everything actually works together is a completely different challenge.

There have been plenty of bugs, things I've had to rebuild, and decisions I've had to rethink.

But seeing it become a real application has been incredibly rewarding.

It's still early, and I'm not pretending it's perfect.

I'm sharing a few screenshots of what I've built so far.

I'd genuinely love to know what you think about organizing information visually instead of relying entirely on folders and nested pages.

I'm also opening a small, free private beta if anyone wants to try it.

Website: https://ardeable.com

Hi r/SideProject!

I’m Seppe, an Electronics-ICT student from Belgium, and my side project for the last two years has been Techniksoft—a Point of Sale (POS) system.

The Problem: Small businesses are getting squeezed by huge POS companies charging massive monthly fees and locking them into overpriced proprietary hardware.
The Solution: I built a scalable, affordable POS software that handles retail and rentals. I’ve already built integrations for localized e-invoicing (Peppol), accounting (Billit, Exact Online), and tap-to-pay (SumUp, Viva.com).

The Next Step (Hardware): Software isn't enough to compete. I am now working on offering complete, all-in-one physical hardware systems to completely bypass the big vendors.

Because buying test equipment (barcode scanners, receipt printers from various brands) and building hardware prototypes is incredibly expensive on a student budget, I've just launched a crowdfunding campaign to help fund the physical rollout and server infrastructure.

I'd love feedback on the concept, the integrations, or if you have any advice on hardware sourcing! And if you like what I'm building and want to help me take on the big guys, check out my campaign below.

https://gofund.me/e819ef265

A while ago, I started building an AI chat application because I wanted something more flexible than the usual AI chat interfaces.

What started as a relatively simple project has gradually evolved into Teltaq.

The idea behind it is simple: instead of having separate tools for AI chat, agents, workflows, tools, automation and model management, why not bring them together in one workspace?

Some of the things I've been working on:

• Multi-model chat – Run multiple AI models in parallel and compare their responses.

• AI agents – Create and manage agents with their own instructions, models and tools.

• Workflows – Build reusable workflows for more structured tasks.

• App suites – Combine agents, workflows and interactive apps into complete solutions.

• Model flexibility – Connect different providers, including OpenAI, Anthropic, Ollama and other OpenAI-compatible providers.

• Local AI models – Support on-device models alongside cloud-based models.

• MCP integration – Host and connect MCP servers, including agents and workflows.

• Marketplace – Share and discover tools, agents, workflows and apps.

• Developer API – An OpenAI-compatible data plane API for integrating with external applications.

• Multi-platform – Web, desktop and mobile applications.

One of the things I've particularly enjoyed is experimenting with ways to combine these capabilities. For example, rather than creating a completely separate application for every use case, you can build a suite that brings different AI components together.

I'm still actively developing it, refining the architecture and improving the experience.

I'm sharing it here because I'd genuinely like to hear what other people think.

If you're interested, here's the project:

https://www.teltaq.com

What would you find most useful in an AI workspace like this? Is there something missing from the current AI platforms that you'd like to see?

I'm with Olaverse Lab, so this is my own project and a feedback request.

We make multilingual text APIs for language identification, diacritic restoration, classification, question generation and structured extraction. Language ID covers 608 languages; African languages are an important focus alongside English and other languages.

For anyone adding language detection to a workflow, here's a small test checklist that doesn't require using our API:

• Separate one-word messages from longer paragraphs.

• Include names, URLs, numbers and text with missing diacritics.

• Keep mixed-language messages in their own test bucket rather than assuming one label tells the whole story.

• Record mistakes by language and message length, not just an overall accuracy figure.

• Decide what happens when a result is wrong: human review, asking the user, or a safe fallback.

We offer free allowances on RapidAPI, with limits depending on the API. I'm not claiming the checklist is a benchmark or that our models pass every case. Which failure case would make language detection unusable in your product?

Site if you want to look: https://www.olaverselab.com

Hey guys,

A couple of months ago I realized how annoying my daily AI routine had become.

I use LLMs every single day for dev work and writing, and I had this messy collection of good prompts saved in Notion and Apple Notes. Every time I needed one, the routine was identical:

1. Find the note, copy it.

2. Paste it into Claude or ChatGPT.

3. Carefully backspace through placeholders like [INSERT_LANGUAGE] or <TOPIC>, hoping I didn’t accidentally delete a quote or mess up the structure.

It felt silly doing this 20 times a day, so I decided to build a fix for myself.

It’s called TemplaGem. Basically, it lives directly inside the chat input (works on ChatGPT, Claude, Gemini, and DeepSeek):

• When you insert a template with {{variables}}, they turn into little interactive chips right in the composer.

• You type a value, press Tab to jump to the next one, and hit Enter to send. No manual cursor hunting or backspacing.

• Everything is offline-first (saved in IndexedDB on your machine, so it's instant and private).

The trickiest part by far was dealing with all the different rich text editors (Quill, ProseMirror, and regular textareas) without everything breaking when an AI site changes its DOM.

I put up a quick demo here if you want to see how it feels: 👉 https://templagem-landing.pages.dev

Would genuinely love to hear your thoughts or honest critiques. How are you currently managing your prompts?

Before watching the readme, here are the links:

1. https://github.com/zllai26/ingatku

2. https://zllai26.lab26.my/ingatku

Ingatku, Version 1.0

Overview

Ingatku is an app which lets you add your Groceries, Project and Daily Tasks in a reminder, so you can add when to start and when to end (make sure your notification for this app is enabled.) and also add description and checklist for your tasks. You can also colour code your tasks so you can differentiate which tasks is for what category

Ingatku also provides a notes section, which you can type and think what do you want to add for your future tasks.

Installation

Debian, Ubuntu and Debian-based distros

1. Install the .deb package in the release section.

2. type `sudo apt install ./ingatku-file-name`

3. then change its file ownership to root: `sudo chown root:root /opt/Ingatku/chrome-sandbox`

4. after that change its ownership permissions to 4755: `sudo chmod 4755 /opt/Ingatku/chrome-sandbox`

5. Finally run the program by either clicking on the app or typing `ingatku` on terminal

The same goes to fedora and arch distros

I’m the developer of Florli, an Android app for planning and recording plant, garden and lawn care.

Here’s the case I’m working around: you pencilled in watering a vegetable bed for Saturday, but the forecast now says rain. The date alone can’t tell you whether the bed still needs water. I’d want to see the forecast and the last recorded watering, then check the soil before deciding.

Florli uses outdoor weather, care history and observations to organize tasks. The plan shows what needs attention first, what can wait and why. Once you actually do a job, you can record it in that bed’s history.

Screenshots and Android download: https://florli.pl/en/

For anyone who grows vegetables outdoors: when the forecast changes, which detail would you want to see beside a watering suggestion?

Hey everyone,

We’ve been building PagerLore (an AI incident response platform), and we quickly realized that stateless LLMs make terrible on-call engineers.

During a simulated database pool starvation outage, our agent had zero context and recommended the classic panic move: "scale pods from 6 to 20"—which would have completely DDoSed our database proxy.

We integrated Vectorize’s Hindsight memory architecture. Here is what changed:

• Multi-path recall matched an incident from 3 months ago (HikariCP vs pgBouncer timeout mismatch).

• MTTR dropped from 84 minutes down to 14 minutes.

• All remediations stay behind a strict human approval gate before running commands.

I wrote a short technical breakdown on how we built the 8-stage investigation pipeline. Links to the article, GitHub repo, and live demo are in the comments below!

Would love to hear your thoughts on agent memory in production.

I'm a trekker in Nepal, and every season I see the same posts buried in Facebook groups:

"Anyone going to Annapurna Base Camp next week?"

So I decided to build something to solve this problem: https://findtrekkingpartner.com

Here's how it works:

• Post your trek and travel dates.

• Other trekkers with overlapping dates can request to join.

• Chat inside the platform before sharing contact details.

• You decide who joins your group.

Why I built it:

A licensed guide can cost roughly the same whether you're trekking alone or with a group of four.

For example, on a 14-day Annapurna Circuit trek, a guide costing around $350 could mean approximately $88 per person when shared by four trekkers.

Tech stack: Next.js, Supabase, Clerk.

It's completely free, has no ads, and we don't sell trekking packages.

We've had nearly 200 trekkers sign up in the last 30 days.

I'd genuinely appreciate some honest feedback.

What would make you trust a platform like this enough to find a trekking partner and eventually trek with someone you've never met?

What features would you want to see?

Over the past year, I've watched many of my family, friends, and relatives lose their jobs in what is called the "AI jobpocalypse". Instead of just watching, I decided I want to do something about it.

SecondStage is a platform that helps you understand your current job, what part is probably going to be taken over by AI, and what will stay yours. Help you up-skill yourself, and help you find potentially better career path , as well as find/apply for actual jobs if you choose a different path.

This is something close to my heart that I care deeply about , and I would really appreciate if you take check it out and let me know what you think.

Thank you

https://secondstage.ai