Show HN: Calculating prices in work hours, not dollars https://bit.ly/43LrAc3

Show HN: Calculating prices in work hours, not dollars Ever looked at a price tag and thought, How many hours do I need to work for this? Instead of just seeing numbers, what if you could instantly see the cost in terms of your time? That’s why I built Time for Price — a simple browser extension that converts prices into work hours based on your income. Whether you're shopping online or budgeting, it helps you make decisions with time in mind, not just money. Just enter your hourly wage, and the extension automatically overlays the converted value on any product page. No more impulse buys—just instant, clear insight into what something really costs you. We’re launching soon! Join the waitlist at https://bit.ly/4iD7lSc to get early access. https://bit.ly/4iD7lSc March 27, 2025 at 01:36AM

Show HN: Taildrops – Free Tailwind CSS 4 code snippets https://bit.ly/4hRIk4p

Show HN: Taildrops – Free Tailwind CSS 4 code snippets Free Tailwind CSS 4 Components — and this is just the beginning! I’ve been sharing a bunch of free Tailwind CSS components on X, but honestly, they just keep getting buried in the timeline. It’s super frustrating when something you put effort into disappears so quickly. That’s why I decided to put everything on a website. Now you can easily find all the components I’ve shared in one place, and I’ll keep adding any new ones I create. It feels good to have a space where they won’t get lost. Check them out if you’re interested — I’d love to hear what you think! https://bit.ly/4iIN8uc March 26, 2025 at 10:29PM

Show HN: I made a fetch client builder to make API calls simpler and safer https://bit.ly/4iI9lZC

Show HN: I made a fetch client builder to make API calls simpler and safer I built this library because I kept rewriting the same fetch wrapper for every project. Each time, I needed the same core features: - Make fetch throw errors to integrate smoothly with libraries like TanStack Query - Add sensible defaults to the Fetch API, like a base URL and authentication headers - Validate responses for type safety when OpenAPI isn’t an option I also wanted the library to feel exactly like using fetch — no new API to learn, and no extra friction for my teammates. While there are other great options out there, I found many were either too rigid or too bulky. Doesn’t it feel wrong to ship a 14kb fetch library to the client? To keep up-fetch small and flexible, I took a simple approach: lightweight defaults, paired with inversion of control, so users can easily override what they need. The result? up-fetch weighs just 1.6kb gzipped, with built-in validation (powered by Standard Schema), configurable options, retries, timeouts, streaming & progress tracking, lifecycle hooks, and more. Check it out if you’ve got a minute — I’d love to gather some feedback! https://bit.ly/4iGGtRd March 26, 2025 at 01:11PM

Show HN: Matrix-themed Nostr note composer https://bit.ly/42gMhLu

Show HN: Matrix-themed Nostr note composer https://bit.ly/42hNlii March 26, 2025 at 01:06AM

Show HN: A website for sharing the "Good, Bad, and Why"s of urban spaces https://bit.ly/4j7VonE

Show HN: A website for sharing the "Good, Bad, and Why"s of urban spaces Hello HN! We're a small team in Kyoto building a website called dédédé ( https://bit.ly/4jof9rd ) that invites people to share the various positives, negatives, oddities, etc. they find in urban spaces. The project grew out of an earlier effort where we'd built an app that assisted participatory urbanism workshops run by local nonprofits. With the new platform, we're trying to build something similar but more casual and hopefully with broader appeal, that'll be fun to use even outside of formal workshop situations. We'd love to hear your thoughts! https://bit.ly/4jof9rd March 24, 2025 at 10:48PM

Show HN: I'm a teacher and built an AI presentation tool https://bit.ly/4jjeWWf

Show HN: I'm a teacher and built an AI presentation tool Hi, I'm a high school teacher from Australia and I've built what I'd like to think is a pretty nifty ChatGPT powered presentation tool for teachers. I'd love it if you could have a look at it and give me some of your feedback. I don't think there's much overlap with the HN crowd and school teachers, but I've been coming here for many years and thought I'd post here and see what you all think. Check it out if you have a minute and I'd be super happy to hear your feedback too. https://bit.ly/4iYGmAr You can jump in and have a play with the tool all you like ;) Cheers, Eli March 23, 2025 at 06:58AM

Show HN: X DMs suck so we built a better one https://bit.ly/4hMMrPt

Show HN: X DMs suck so we built a better one https://bit.ly/4iGvNCg March 24, 2025 at 07:22PM

Show HN: I Developed AI Memory Booster: Self-Hosted AI with Long Term Memory https://bit.ly/4kYjcfs

Show HN: I Developed AI Memory Booster: Self-Hosted AI with Long Term Memory I recently developed and open-sourced a project called AI Memory Booster, which combines Ollama (for running local LLaMA models) with ChromaDB to give AI systems persistent memory across sessions. The project is fully self-hosted and privacy-first — everything runs locally via a Node.js API, a simple React UI, and Docker support for easy deployment. Key Features: 1. Ollama-powered inference (LLaMA 3.2 and other models). 2. Persistent memory via ChromaDB (store and recall data across sessions). 3. Works on CPU or GPU, tested on local laptops and free-tier cloud VMs. 4. API-first approach with /learn and /recall endpoints. 5. Ready-to-use React web interface + install.sh script for fast setup. Use Cases: 1. Build a local AI chatbot with memory. 2. Power a self-hosted assistant that remembers conversations or tasks. 3. Add a memory layer to Ollama agents or automation workflows. 4. Integrate into existing Node.js applications. The source code is now available on Github: https://bit.ly/4kTwKbY I’d love feedback from the community — especially ideas on improving long-term memory handling or other integrations you’d find useful! https://bit.ly/4kZA6KD March 24, 2025 at 07:23AM

Show HN: Emulating Tamagotchi P1 in the Browser https://bit.ly/4l6B6wy

Show HN: Emulating Tamagotchi P1 in the Browser Hi! I wanted to play the original Tamagotchi in my browse but couldn't find any, so I built one myself. I hope you enjoy it as much as I do. https://bit.ly/4iXguF9 March 24, 2025 at 06:54AM

Show HN: IRD – Reversible Debugger for Code and Quantum Algorithms https://bit.ly/4iVksxT

Show HN: IRD – Reversible Debugger for Code and Quantum Algorithms https://bit.ly/4l9RRaf March 23, 2025 at 10:24PM

Show HN: AI Associate for lawyers controlled by voice https://bit.ly/4kXL3wi

Show HN: AI Associate for lawyers controlled by voice https://www.youtube.com/watch?v=nN5zDAjsEL0 March 24, 2025 at 01:12AM

Show HN: Don't click this button – testing the internet's patience https://bit.ly/41REmmI

Show HN: Don't click this button – testing the internet's patience This weekend I was looking for a side project to play around with Go so I built a simple web experiment to test the self control of the internet: it has a single button, a live click counter, and a timer. I want to see how long the internet can collectively resist clicking it. The backend is a very simple Go binary with Go's std http server, web sockets, a WAL-style log of clicks, plain CSS and Comic Sans. Inspired by Silicon Valley's (HBO series) Bro app, OneMillionCheckBoxes and Cookie Clicker https://bit.ly/4iwASwW March 23, 2025 at 01:37AM

Show HN: DAPS – Prime-Adaptive Search for Discontinuous Optimization Problems https://bit.ly/41QzsX4

Show HN: DAPS – Prime-Adaptive Search for Discontinuous Optimization Problems I've been working on a global optimization algorithm that uses prime number-based adaptive grid search. It dynamically adjusts resolution by increasing or decreasing prime numbers as "resolution knobs" — allowing it to handle discontinuities, sharp valleys, and chaotic landscapes better than naive grid search. The repo includes Python and PyTorch-compatible versions, benchmarks against grid search, and a research paper. Would love feedback from optimization, ML, or numerical analysis folks. Curious if anyone sees potential applications or improvements. GitHub: https://bit.ly/41VqJ61 Paper: https://bit.ly/4io0lIR.... https://bit.ly/41VqJ61 March 23, 2025 at 06:49AM

Show HN: I build a tool that will tell you what to respond in negotations https://bit.ly/4hzbAgj

Show HN: I build a tool that will tell you what to respond in negotations After reading the book Getting to Yes, I really want some tool to help me negotiate more efficiently without having to memorize everything principle. You start by putting in interests of each party, then you can explore different functions: how to respond to the other party, explore objective criteria out there or brainstorm more negotiation options. Still working on it! Leave me feedback if you have any suggestions! https://bit.ly/4iUvqnw March 22, 2025 at 11:01PM

Show HN: I Made a Language to Be JavaScript's Nanny https://bit.ly/4kWu2T9

Show HN: I Made a Language to Be JavaScript's Nanny I'm working on a language called Chicory. It's yet-another compiles to JS(X) language. I'd value any feedback. See also https://bit.ly/42didzt https://bit.ly/4l3GYXo March 22, 2025 at 09:09PM

Show HN: I made a VS Code snippets extension to store code easier https://bit.ly/4c8iU1z

Show HN: I made a VS Code snippets extension to store code easier https://bit.ly/41RcRJP March 22, 2025 at 09:53AM

Show HN: Font Pair – I was wasting hours choosing fonts, so I built this https://bit.ly/4iRiLBM

Show HN: Font Pair – I was wasting hours choosing fonts, so I built this Hey HN I built this little tool to solve a personal pain — I always get stuck picking fonts while designing or building something. So I created Font Pair – a one-click font pairing tool. You can: - Shuffle heading + body font combos - Filter by serif, sans, display - Preview them instantly - Use keyboard shortcuts (S, H, B) for speed Would love feedback from devs/designers here. Built with just HTML/CSS/JS. Thanks! https://bit.ly/4iIXISh March 22, 2025 at 04:48AM

Show HN: Get hired faster by reaching decision-makers early https://bit.ly/4iqQkuB

Show HN: Get hired faster by reaching decision-makers early I built Insider Openings because I know how frustrating job searching can be. You spend hours tweaking resumes, writing cover letters, applying through job boards… and then? Crickets. I’ve been there, wondering if anyone even saw my application. But after years of working with startups, I noticed something most job seekers don’t see is that when a company raises funding, they’re about to grow. They start hiring fast, often before a job ever hits a careers page. That’s when the window of opportunity is wide open… but no one’s talking about it. So I thought, what if I could give job seekers a head start? A list of companies fresh off a funding round, along with direct contacts to the people actually making hiring decisions? That’s how Insider Openings was born. https://bit.ly/4ik9K49 March 22, 2025 at 12:00AM

Show HN: Personal Best, the highest-ranking personal blogs of Hacker News https://bit.ly/4hutErZ

Show HN: Personal Best, the highest-ranking personal blogs of Hacker News https://bit.ly/4huugO9 March 21, 2025 at 03:14PM

Show HN: Torch Lens Maker – Differentiable Geometric Optics in PyTorch https://bit.ly/4l1blhd

Show HN: Torch Lens Maker – Differentiable Geometric Optics in PyTorch Hello HN! For the past 6 months I've been working on an open source python library that implements differentiable geometric optics in PyTorch. It's very experimental still, but eventually the goal is to use it to design optical systems with a state of the art optimization framework and a beautiful code based API. Think OpenSCAD, but for optical systems. Not only is PyTorch's autograd an amazing general purpose optimizer, but torch.nn (the neural network building blocks) can be used pretty much out of the box to model an optical system. This is because there is a strong analogy to be made between layers of a neural network, and optical elements in a so-called sequential optical system. So the magic is that we can stack lenses as if we were stacking Conv2D and ReLu layers and everything works out. Instead of Conv2D you have ray-surface collision detection, instead of ReLu you have the law of refraction. Designing lenses is surprisingly like training a neural network. Check out the docs for examples of using the API. My favorite one is the rainbow :) https://bit.ly/4kNRGBe... You should be able to `pip install torchlensmaker` to try it out, but I just set it up so let me know if there's any trouble. I was part of the Winter 1'24 batch at the Recurse Center ( https://bit.ly/48VxRBf ) working on this project pretty much full time. I'm happy to talk about that experience too! https://bit.ly/4iKK1lf March 21, 2025 at 02:29PM