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Ryan Hendrickson

What are you building, and what does your stack look like?

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I am a Computer Science student doing research into how solopreneurs and small startups create new apps and what their stack looks like. Particularly, I'm interested in how you handle things like authentication, billing, and permissions/authorization in your apps.

Let me know what you're working on below and how you're going about it -- I'd love to connect for some quick calls to learn about your product and talk about your process in building it!

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Vatsal M

Building vibepreneur.com — a platform that validates micro-SaaS niches before you build. Stack: Next.js, Supabase, Claude for research synthesis, Airtable for content pipeline. Auth via Supabase, payments via Stripe. The interesting part of our stack is the validation pipeline: we use a mix of Reddit signal analysis, Product Hunt launch data, and real buyer intent patterns to score niches. The insight we kept hitting: most solopreneurs pick markets too broad and get crushed by incumbents, or too niche and find no buyers. We're building the gap between idea and first paying customer. Always happy to trade notes with other indie builders on what's working for auth and billing — the boilerplate stuff eats more time than it should.

Sudip Mondal

I just launched Amplitron, a free open-source guitar amp simulator!

Tech stack:

• C++17 with PortAudio for low-latency audio I/O (~1.3ms latency with 64-sample buffer at 48kHz)

• Dear ImGui for the visual pedalboard UI (drag-and-drop interface)

• Cross-platform: Windows, macOS, Linux

• 9 custom DSP effects: Noise Gate, Compressor, Overdrive, Distortion, EQ, Chorus, Delay, Reverb, Cabinet Sim

• CI/CD with automatic builds/tests on all 3 platforms

• Thread-safe audio pipeline using try_lock to prevent UI blocking

It's all open source on GitHub. Built it because commercial amp sims are expensive for casual home practice. Would love to hear from other audio devs interested in contributing!

https://www.producthunt.com/products/amplitron

https://github.com/sudip-mondal-...

Rise-n-Shine Software

I'm building lightPDF, a high-performance, minimalist document viewer for the desktop.

The main goal is to create a fast, lightweight, and privacy-respecting alternative to bloated applications like Adobe Acrobat. It's an "offline-first" app, meaning it processes all your files locally on your machine without sending them to the cloud.

Here’s a breakdown of the technology stack I'm using to achieve this:

  • Application Framework: Tauri is the core of the project. It allows me to build a native desktop application using web technologies for the user interface and a Rust backend for performance-critical logic, resulting in a much smaller and more efficient app than something built with Electron.

  • Frontend: The user interface is built with React and bundled using Vite. This allows for a modern, responsive, and interactive UI.

  • Styling: I'm using Tailwind CSS to rapidly design and style the user interface, keeping it clean and consistent.

  • Backend: The backend logic is written in Rust. This provides memory safety, speed, and the ability to interface directly with low-level libraries, which is perfect for a high-performance application.

  • Core Rendering Engine: For the most demanding task—rendering documents—the Rust backend integrates with PDFium, Google's native C++ library that powers the PDF rendering in Chrome. This is the key to achieving "extreme performance" when opening large PDFs or comic book archives.

Its already in a beta stage and the idea is to try and keep it lightweight and free. The plan is to keep exe installer below 15mb(dll itself is around 6 mb) msi below 10 and overall HD usage below 20mb's.

Doron Sun

Building InterviewAI an AI mock interviewer that speaks to you in real-time, asks follow-up questions,

  and gives instant feedback. Stack: Next.js 15, Groq (llama-3.3-70b for questions + Whisper for

  speech-to-text), Web Speech API for TTS. Biggest challenge was making the AI sound like a real interviewer

  and not a chatbot 😅

Eric Buckner

Great question! I’ve been building an AI-powered design app called InkPulse AI.

It started as a tattoo design tool, but I’m realizing it’s evolving into more of a general AI design studio.

Right now it lets users:

  • Generate designs from prompts (tattoos, t-shirts, stickers, etc.)

  • Edit and customize them

  • Try designs on (for tattoos or mockups)

Tech-wise I’m using:

  • Flutter for the mobile app

  • Firebase (Firestore + functions)

  • OpenAI + Replicate for image generation (testing multiple models right now like DreamShaper, Flux, Ideogram)

Biggest challenge so far has been balancing quality vs cost vs speed across different models depending on the style.

Curious how are others here handling multi-model setups or prompt consistency across different generators?

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