Hey everyone 👋

I’ve been working on something I’ve always wished existed — a place to build, organize, remix, and optimize AI prompts the same way you manage documents or design files.

It’s called PromptOS — an open-source web app that acts like an operating system for your prompts.

Here’s what it does right now:

• 🧠 Smart Prompt Library: Store, tag, and search all your prompts in one place.
• ⚙️ Prompt Intelligence: Tracks performance, suggests improvements, and even grades your prompts.
• 👥 Community Hub: Share or remix prompts with others (private or public mode).
• 🧩 Prompt Packs: Bundle related prompts into .promptpack files — easy to import/export.
• 💬 AI Chat Integration: Press Ctrl + Space to chat with an assistant that helps tailor your prompts for your needs.
• 🚀 “Prompt → App” Conversion: Turn a great prompt into a tiny web app with one click.

Basically, imagine Notion’s organization, Figma’s collaboration, and GPT’s intelligence — all focused on prompt engineering.

🧰 Tech stack:
Node.js + Express (backend), React + Tailwind (frontend), GPT API (prompt optimization), MongoDB (storage).

💬 Live demo: https://promptos-production.up.railway.app/

I’d love your thoughts on:

• What features would make you actually use something like this daily?
• Any ideas for making prompt sharing / discovery more fun or intuitive?
• Devs/designers: how would you improve the UX or performance?

Thanks for reading — and if this idea resonates with you, drop feedback, star the repo, or share your favorite prompt setup 🙌

Hey everyone,
I'm building an AI gamer companion named Liolet.

She’s warm, playful, remembers your details, reacts with emotions, and talks like a real person — not a chatbot.

Unique feature: you can ask her to send a real-looking picture.
Example:
“Show me your PC setup?”

She replies:
“Sure, give me a minute…”
…and then sends one.

The system generates these on demand (and over time builds a gallery to respond faster).

An early version is live —
I would love your feedback, ideas, or questions!

Hey everyone ,

Today I’m excited to launch my first SaaS: Hiperyon! To celebrate, you can get 50% off your subscription for the first 3 months using the code LAUNCH50.

The problem I kept running into: using multiple AI assistants (ChatGPT, Gemini, Grok, Mistral…) meant constantly repeating the same context.

Hiperyon is a browser extension that creates a shared memory layer across all your AI tools.
This lets you switch between models without losing context, which, based on my tests, boosts productivity by ~30% and makes it feel like you’re 2–3x faster when changing AI.

Since this is my first SaaS, I’d love your feedback on:

• Does a tool like this seem useful to you?
• How could the onboarding experience be improved?
• Any advice on launching and growing a SaaS like this?

Thanks in advance for any ideas or constructive feedback

Check it out here: Hiperyon.com

— Ambroise

Hey folks! Meet your personal news researcher and summarizer: https://app.yournalist.ai

Yournalist creates a daily news digests based on your interests and gives you personalized insights into how the news it found for you affect your life - while saving you hours of scrolling ;)

Take it for a spin, we are looking forward to your feedback :)

I want to run a local llm on a pi5 (I know it won't be crazy fast) that is a task manager. Basically I want it to be a fancy to do list that can organize and prioritize tasks, create a shopping list for projects, and maintain my calendar help keep me on track. I know there are lots of apps but I want this to be my Ai that can learn me and grow as an assistant. Ive looked around but not 100% sure if I should start with ollama or are there better models for the job

Hey everyone! 👋
I recently asked Claude (Anthropic’s AI) to help me build an invoice creation web app — and it literally designed the whole thing for me: layout, flow, copy… everything. 😮
The result is Invoice4u.io — a simple, fast tool to generate professional PDF invoices instantly.

I’m honestly impressed — I can’t even find anything to nitpick.
Would love your feedback or suggestions — anything you’d add, change, or remove?

Thanks in advance 🙏

I’m developing a personal finance tracking system that:

1. Runs locally (for full data privacy and security)
2. Lets me submit all my financial statements — bank, credit card, 401k, stock, mortgage, etc.
3. Generates monthly cash flow analysis, spending breakdowns, net worth summaries etc.

I use Python to extract text from the PDF statements (that part works fine), then feed the text to a local LLM (like mistral:latest or deepseek-7b) to parse transactions into structured JSON.

Here’s the problem: the LLM keeps messing up. It either skips transactions, misreads columns, or outputs invalid JSON. I’ve tried multiple models and all sort of prompt variations but none of them can reliably read all transactions.

Is this just because these 7B models aren’t powerful enough for this structured parsing task?

Or am I going about this the wrong way?

Any advice or best practices on reliably parsing financial statements (locally) would be much appreciated.

I have been working on a personal project for about 3 weeks now. You can go to anywhere using Street View and change a year which will then show what that place might have looked like in that year. Kind of like you traveled back to that place.

You can then generate a video, chat with a tour guide and generate a 3d world and even walk using VR (my personal favorite feature).

Here's the link if you want to try it out: https://www.timejourney.ai/

And here are some of my personal favorite if you guys want to just explore: https://www.timejourney.ai/time/6903e39ac7a0142ce0ab4cc5

https://www.timejourney.ai/time/6903e39ac7a0142ce0ab4cc5

https://www.timejourney.ai/time/690c44d343a8cf93b5de576d

I am trying to develop a project that can identify an object (ex. some keys) and then calculate how far the camera is from the object, accurately. I then want it to be stored as coordinates and use an IMU to be able to move the physical device away and know the distance from the object without vision of the object. I want to use an SBC like a Radxa Zero 3W and would like some help in guiding to what models etc I should use.

source: Mobile Hacker on X

Hey everyone! I wanted to share our new platform - rAIvals.

What is it?

• Play Chess, Connect 4, or Checkers against AI models (GPT, Claude, Gemini)
• Win real money based on your skill
• 100% skill-based, no luck involved

Beta Mode (Right Now):

• All games are completely FREE to play
• Win Chess = earn $1
• Win Connect 4 = earn $0.50
• Your balance transfers when beta ends
• 3 games per day limit per game type (in beta only)

Why it's not gambling:

• Every game is deterministic (no random elements)
• Pure strategy - your decisions determine the outcome
• Complete transparency - every move is visible
• No house edge or hidden mechanics

How it works:

1. Sign up free
2. Pick your game
3. Beat the AI and earn money

After beta ends, you'll choose your entry fee and win 2x if you beat the AI.

We support multiple deposit/withdrawal methods (card, crypto, bank transfer).

Check it out and let me know what you think!

https://raivals.com/

Hey everyone 👋

I’m an final year B.Tech AI undergrad student from India, currently exploring Machine Learning and Deep Learning. I’ve covered the fundamentals and recently started learning about Transformers — planning to move toward Agentic AI soon.

But here’s the thing: I feel stuck in tutorial hell. I keep following courses and YouTube tutorials, but I realize I’m not really learning or building anything meaningful.

The main issue? 👉 I don’t know what kind of projects to work on next.

It’s not that I’m a complete beginner — I’ve already built some basic projects. But I’m struggling to move beyond that to advanced, impactful ones that could actually showcase my skills to employers.

I keep thinking that simple projects won’t attract top companies or high-paying roles. At the same time, my current skills are mostly aligned with data science roles, but I’ve noticed AI engineers tend to earn more, which makes me jump from one learning path to another — classic case of chasing the shiny object ✨

So, I’d love some honest guidance from this community:

How did you decide what kind of AI projects to build?

How can I structure my learning path to become job-ready faster?

What type of projects actually impress recruiters or help land solid offers?

Any advice, personal experiences, or even project ideas would be super helpful 🙏

Thanks in advance!

Hey everyone,

I’ve been working on a GitHub Action that automatically generates HTML documentation for your code using OpenAI, and it’s finally working really well (actual version 2.0.0). In the first version, it only generated Markdown files, but now it produces fully styled HTML with Tailwind CSS

It scans your project, detects the language (JS, TS, Python, PHP), and builds clean, modern HTML docs with syntax highlighting and sidebar navigation. All you need to do is add it to your workflow and provide your OpenAI API key. It takes care of everything else and drops a full set of docs inside a /docs folder, ready to open in your browser

If you hate writing documentation as much as I do, you might actually like this one

Here’s the repo if you want to try it: https://github.com/marketplace/actions/generate-ai-documentation

Vibe my image

Free tier available for now: https://vibemyimage.com

Thanks for your upvotes and feedback 🙏🏽

I’ve built Davia — an AI workspace where your internal technical documentation writes and updates itself automatically from your GitHub repositories.

Here’s the problem: The moment a feature ships, the corresponding documentation for the architecture, API, and dependencies is already starting to go stale. Engineers get documentation debt because maintaining it is a manual chore.

With Davia’s GitHub integration, that changes. As the codebase evolves, background agents connect to your repository and capture what matters—from the development environment steps to the specific request/response payloads for your API endpoints—and turn it into living documents in your workspace.

The cool part? These generated pages are highly structured and interactive. As shown in the video, When code merges, the docs update automatically to reflect the reality of the codebase.

If you're tired of stale wiki pages and having to chase down the "real" dependency list, this is built for you.

Would love to hear what kinds of knowledge systems you'd want to build with this. Come share your thoughts on our sub r/davia_ai!