Show HN: Blunderchess.net – blunder for your opponent every five moves https://ift.tt/K1n4aOp

Show HN: Blunderchess.net – blunder for your opponent every five moves blunderchess.net is an open source, peer-to-peer chess app where every five moves, players each get to make one blunder-move for their opponent https://ift.tt/PjS3X9k February 16, 2025 at 05:52AM

Show HN: Edit Any Record on ATProto with History https://ift.tt/fJMV9TS

Show HN: Edit Any Record on ATProto with History https://ift.tt/zXeZt6c February 16, 2025 at 02:24AM

Show HN: I got frustrated with CRMs, so I'm building my own for startups https://ift.tt/0lC6ZgS

Show HN: I got frustrated with CRMs, so I'm building my own for startups After trying a bunch of CRMs for my startup, I kept running into the same issues—overpriced plans that scale aggressively or bloated features that just slow me down. I wanted something simple, affordable, and actually built for startups, so I decided to build it myself: Leadchee.com. Fixed pricing, no nonsense. Curious—how do you all handle CRMs? Do you stick with the big players, go for niche tools, or build your own? Would love to hear your thoughts! https://leadchee.com February 14, 2025 at 09:25PM

Show HN: Open-Sourcing My LLM Drag and Drop Website Builder https://ift.tt/RJxYZUl

Show HN: Open-Sourcing My LLM Drag and Drop Website Builder Hey HN - OP here. I wrote some about this project in the following link, and there's a video demo as well: https://ift.tt/yMhrUf9... This has been one of my favorite things I've ever worked on - the way the LLM collaborates with the user to accelerate tedious and hard work, the way you can directly edit the code instead of dealing with a panel of visual editing toggles - I think it has a lot of potential but I don't have time to pursue it anymore so open-sourcing it. The idea for this came out of conversations with a few people who were struggling with frontend development. For technical people, strictly using an LLM to write code can be tedious. To combat this, LLM usage is limited to getting started quickly, improving design, and wiring up frontend state. On the other hand, writing frontend code feels less efficient than just moving things around on a screen. Hence the drag and drop interface that makes it fast to build. Finally, I despise the visual editing toggles on Figma / Bubble / Squarespace / etc. The amount of hunt and peck to simply adjust a font a bit and change some colors or add a shadow is a huge time suck. So I built a way to directly edit the underlying React code when styling - just add or remove tailwind classes. IMO the craziest thing is that all of the code is just stored on the frontend in a config language of sorts. It is inflated at runtime and can be updated without any hot reload. There is no "underlying React code" for the app you're building here - in order to edit the code, I convert the config into React code, then convert back to a config, which triggers updates in the dom. Anyways, I think there's a lot of clever stuff in here, but then again I wrote it. Happy to answer any questions and hope this is interesting/helpful to someone else out there. https://ift.tt/xMa49uW February 14, 2025 at 11:38PM

Show HN: Live webcam metal pin toy simulation powered by WebGPU depth estimation https://ift.tt/V5RvpjG

Show HN: Live webcam metal pin toy simulation powered by WebGPU depth estimation https://ift.tt/ui0TMOo February 14, 2025 at 11:33PM

Show HN: Dockershrink – AI Assistant to reduce the size of Docker images https://ift.tt/eJhObNw

Show HN: Dockershrink – AI Assistant to reduce the size of Docker images For the past few months, I've been hacking around a project I call Dockershrink. It automates a simple task: Take a Dockerfile and optimize its code with the goal of reducing the size of the final Docker image. People don't realize that we can apply some very basic techniques to reduce, for eg, a 2GB image down to just ~100MB: - Multistage builds with light-weight base image for final stage - Remove unused dependencies - Optimizations specific to the tech stack And I feel like I've already done this optimization for my personal projects and backend apps at my job(s) a couple of times. The project currently uses GPT-4o (open source so you can run it locally) and only works for Nodejs projects. There are a couple of reasons why I think dockershrink can be better than using just Vanilla LLM or Github Copilot/Cursor: - Image optimization can benefit from a lot of custom prompting, especially when you have insights about specific tech stacks. Describing techniques deeply in the prompt gave better results than simply asking the LLM to "optimize code for bloat reduction". - A RAG approach will be truly beneficial. I plan on giving dockershrink access to up-to-date documentations of Docker, Bash and all programming languages out there. Additionally, it can be given a few suitable chunks of code to enhance the context. - Analysing custom base images: most orgs have their customized base images. Adding context about these can further help Dockershrink make better decisions. Try it out - "brew install dockershrink" Happy to hear your thoughts! https://ift.tt/2Og6uIC February 14, 2025 at 04:15AM

Show HN: SQL Noir – Learn SQL by solving crimes https://ift.tt/ULg5W6B

Show HN: SQL Noir – Learn SQL by solving crimes I built SQL Noir, an interactive detective game that challenges you to solve mysteries using real SQL queries. It’s fully open source, designed to give you a practical and immersive way to learn SQL while engaging with a narrative-driven mystery. https://www.sqlnoir.com February 14, 2025 at 03:19AM