The best Hacker News stories from Show from the past day
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Show HN: ShapedQL – A SQL engine for multi-stage ranking and RAG
Hi HN,<p>I’m Tullie, founder of Shaped. Previously, I was a researcher at Meta AI, worked on ranking for Instagram Reels, and was a contributor to PyTorch Lightning.<p>We built ShapedQL because we noticed that while retrieval (finding 1,000 items) has been commoditized by vector DBs, ranking (finding the best 10 items) is still an infrastructure problem.<p>To build a decent for you feed or a RAG system with long-term memory, you usually have to put together a vector DB (Pinecone/Milvus), a feature store (Redis), an inference service, and thousands of lines of Python to handle business logic and reranking.<p>We built an engine that consolidates this into a single SQL dialect. It compiles declarative queries into high-performance, multi-stage ranking pipelines.<p>HOW IT WORKS:<p>Instead of just SELECT <i>, ShapedQL operates in four stages native to recommendation systems:<p>RETRIEVE: Fetch candidates via Hybrid Search (Keywords + Vectors) or Collaborative Filtering.
FILTER: Apply hard constraints (e.g., "inventory > 0").
SCORE: Rank results using real-time models (e.g., p(click) or p(relevance)).
REORDER: Apply diversity logic so your Agent/User doesn’t see 10 nearly identical results.<p>THE SYNTAX: Here is what a RAG query looks like. This replaces about 500 lines of standard Python/LangChain code:<p>SELECT item_id, description, price<p>FROM<p><pre><code> -- Retrieval: Hybrid search across multiple indexes
search_flights("$param.user_prompt", "$param.context"),
search_hotels("$param.user_prompt", "$param.context")
</code></pre>
WHERE<p><pre><code> -- Filtering: Hard business constraints
price <= "$param.budget" AND is_available("$param.dates")
</code></pre>
ORDER BY<p><pre><code> -- Scoring: Real-time reranking (Personalization + Relevance)
0.5 * preference_score(user, item) +
0.3 * relevance_score(item, "$param.user_prompt")
</code></pre>
LIMIT 20<p>If you don’t like SQL, you can also use our Python and Typescript SDKs. I’d love to know what you think of the syntax and the abstraction layer!</i>
Show HN: ShapedQL – A SQL engine for multi-stage ranking and RAG
Hi HN,<p>I’m Tullie, founder of Shaped. Previously, I was a researcher at Meta AI, worked on ranking for Instagram Reels, and was a contributor to PyTorch Lightning.<p>We built ShapedQL because we noticed that while retrieval (finding 1,000 items) has been commoditized by vector DBs, ranking (finding the best 10 items) is still an infrastructure problem.<p>To build a decent for you feed or a RAG system with long-term memory, you usually have to put together a vector DB (Pinecone/Milvus), a feature store (Redis), an inference service, and thousands of lines of Python to handle business logic and reranking.<p>We built an engine that consolidates this into a single SQL dialect. It compiles declarative queries into high-performance, multi-stage ranking pipelines.<p>HOW IT WORKS:<p>Instead of just SELECT <i>, ShapedQL operates in four stages native to recommendation systems:<p>RETRIEVE: Fetch candidates via Hybrid Search (Keywords + Vectors) or Collaborative Filtering.
FILTER: Apply hard constraints (e.g., "inventory > 0").
SCORE: Rank results using real-time models (e.g., p(click) or p(relevance)).
REORDER: Apply diversity logic so your Agent/User doesn’t see 10 nearly identical results.<p>THE SYNTAX: Here is what a RAG query looks like. This replaces about 500 lines of standard Python/LangChain code:<p>SELECT item_id, description, price<p>FROM<p><pre><code> -- Retrieval: Hybrid search across multiple indexes
search_flights("$param.user_prompt", "$param.context"),
search_hotels("$param.user_prompt", "$param.context")
</code></pre>
WHERE<p><pre><code> -- Filtering: Hard business constraints
price <= "$param.budget" AND is_available("$param.dates")
</code></pre>
ORDER BY<p><pre><code> -- Scoring: Real-time reranking (Personalization + Relevance)
0.5 * preference_score(user, item) +
0.3 * relevance_score(item, "$param.user_prompt")
</code></pre>
LIMIT 20<p>If you don’t like SQL, you can also use our Python and Typescript SDKs. I’d love to know what you think of the syntax and the abstraction layer!</i>
Show HN: Dwm.tmux – a dwm-inspired window manager for tmux
Hey, HN! With all recent agentic workflows being primarily terminal- and tmux-based, I wanted to share a little project I created about decade ago.<p>I've continued to use this as my primary terminal "window manager" and wanted to share in case others might find it useful.<p>I would love to hear about other's terminal-based workflows and any other tools you may use with similar functionality.
Show HN: Dwm.tmux – a dwm-inspired window manager for tmux
Hey, HN! With all recent agentic workflows being primarily terminal- and tmux-based, I wanted to share a little project I created about decade ago.<p>I've continued to use this as my primary terminal "window manager" and wanted to share in case others might find it useful.<p>I would love to hear about other's terminal-based workflows and any other tools you may use with similar functionality.
Show HN: Dwm.tmux – a dwm-inspired window manager for tmux
Hey, HN! With all recent agentic workflows being primarily terminal- and tmux-based, I wanted to share a little project I created about decade ago.<p>I've continued to use this as my primary terminal "window manager" and wanted to share in case others might find it useful.<p>I would love to hear about other's terminal-based workflows and any other tools you may use with similar functionality.
Show HN: I built a small browser engine from scratch in C++
Hi HN! Korean high school senior here, about to start CS in college.<p>I built a browser engine from scratch in C++ to understand how browsers work. First time using C++, 8 weeks of development, lots of debugging—but it works!<p>Features:<p>- HTML parsing with error correction<p>- CSS cascade and inheritance<p>- Block/inline layout engine<p>- Async image loading + caching<p>- Link navigation + history<p>Hardest parts:<p>- String parsing(html, css)<p>- Rendering<p>- Image Caching & Layout Reflowing<p>What I learned (beyond code):<p>- Systematic debugging is crucial<p>- Ship with known bugs rather than chase perfection<p>- The Power of "Why?"<p>~3,000 lines of C++17/Qt6. Would love feedback on code architecture and C++ best practices!<p>GitHub: <a href="https://github.com/beginner-jhj/mini_browser" rel="nofollow">https://github.com/beginner-jhj/mini_browser</a>
Show HN: I built a small browser engine from scratch in C++
Hi HN! Korean high school senior here, about to start CS in college.<p>I built a browser engine from scratch in C++ to understand how browsers work. First time using C++, 8 weeks of development, lots of debugging—but it works!<p>Features:<p>- HTML parsing with error correction<p>- CSS cascade and inheritance<p>- Block/inline layout engine<p>- Async image loading + caching<p>- Link navigation + history<p>Hardest parts:<p>- String parsing(html, css)<p>- Rendering<p>- Image Caching & Layout Reflowing<p>What I learned (beyond code):<p>- Systematic debugging is crucial<p>- Ship with known bugs rather than chase perfection<p>- The Power of "Why?"<p>~3,000 lines of C++17/Qt6. Would love feedback on code architecture and C++ best practices!<p>GitHub: <a href="https://github.com/beginner-jhj/mini_browser" rel="nofollow">https://github.com/beginner-jhj/mini_browser</a>
Show HN: A MitM proxy to see what your LLM tools are sending
I built this out of curiosity about what Claude Code was actually sending to the API. Turns out, watching your tokens tick up in real-time is oddly satisfying.<p>Sherlock sits between your LLM tools and the API, showing you every request with a live dashboard, and auto-saved copies of every prompt as markdown and json.
Show HN: A MitM proxy to see what your LLM tools are sending
I built this out of curiosity about what Claude Code was actually sending to the API. Turns out, watching your tokens tick up in real-time is oddly satisfying.<p>Sherlock sits between your LLM tools and the API, showing you every request with a live dashboard, and auto-saved copies of every prompt as markdown and json.
Show HN: The HN Arcade
I love seeing all the small games that people build and post to this site.<p>I don't want to forget any, so I have built a directory/arcade for the games here that I maintain.<p>Feel free to check it out, add your game if its missing and let me know what you think. Thanks!
Show HN: The HN Arcade
I love seeing all the small games that people build and post to this site.<p>I don't want to forget any, so I have built a directory/arcade for the games here that I maintain.<p>Feel free to check it out, add your game if its missing and let me know what you think. Thanks!
Show HN: The HN Arcade
I love seeing all the small games that people build and post to this site.<p>I don't want to forget any, so I have built a directory/arcade for the games here that I maintain.<p>Feel free to check it out, add your game if its missing and let me know what you think. Thanks!
Show HN: Ourguide – OS wide task guidance system that shows you where to click
Hey! I'm eshaan and I'm building Ourguide -an on-screen task guidance system that can show you where to click step-by-step when you need help.<p>I started building this because whenever I didn’t know how to do something on my computer, I found myself constantly tabbing between chatbots and the app, pasting screenshots, and asking “what do I do next?” Ourguide solves this with two modes. In Guide mode, the app overlays your screen and highlights the specific element to click next, eliminating the need to leave your current window. There is also Ask mode, which is a vision-integrated chat that captures your screen context—which you can toggle on and off anytime -so you can ask, "How do I fix this error?" without having to explain what "this" is.<p>It’s an Electron app that works OS-wide, is vision-based, and isn't restricted to the browser.<p>Figuring out how to show the user where to click was the hardest part of the process. I originally trained a computer vision model with 2300 screenshots to identify and segment all UI elements on a screen and used a VLM to find the correct icon to highlight. While this worked extremely well—better than SOTA grounding models like UI Tars—the latency was just too high. I'll be making that CV+VLM pipeline OSS soon, but for now, I’ve resorted to a simpler implementation that achieves <1s latency.<p>You may ask: if I can show you where to click, why can't I just click too? While trying to build computer-use agents during my job in Palo Alto, I hit the core limitation of today’s computer-use models where benchmarks hover in the mid-50% range (OSWorld). VLMs often know what to do but not what it looks like; without reliable visual grounding, agents misclick and stall. So, I built computer use—without the "use." It provides the visual grounding of an agent but keeps the human in the loop for the actual execution to prevent misclicks.<p>I personally use it for the AWS Console's "treasure hunt" UI, like creating a public S3 bucket with specific CORS rules. It’s also been surprisingly helpful for non-technical tasks, like navigating obscure settings in Gradescope or Spotify. Ourguide really works for any task when you’re stuck or don't know what to do.<p>You can download and test Ourguide here: <a href="https://ourguide.ai/downloads" rel="nofollow">https://ourguide.ai/downloads</a><p>The project is still very early, and I’d love your feedback on where it fails, where you think it worked well, and which specific niches you think Ourguide would be most helpful for.
Show HN: Ourguide – OS wide task guidance system that shows you where to click
Hey! I'm eshaan and I'm building Ourguide -an on-screen task guidance system that can show you where to click step-by-step when you need help.<p>I started building this because whenever I didn’t know how to do something on my computer, I found myself constantly tabbing between chatbots and the app, pasting screenshots, and asking “what do I do next?” Ourguide solves this with two modes. In Guide mode, the app overlays your screen and highlights the specific element to click next, eliminating the need to leave your current window. There is also Ask mode, which is a vision-integrated chat that captures your screen context—which you can toggle on and off anytime -so you can ask, "How do I fix this error?" without having to explain what "this" is.<p>It’s an Electron app that works OS-wide, is vision-based, and isn't restricted to the browser.<p>Figuring out how to show the user where to click was the hardest part of the process. I originally trained a computer vision model with 2300 screenshots to identify and segment all UI elements on a screen and used a VLM to find the correct icon to highlight. While this worked extremely well—better than SOTA grounding models like UI Tars—the latency was just too high. I'll be making that CV+VLM pipeline OSS soon, but for now, I’ve resorted to a simpler implementation that achieves <1s latency.<p>You may ask: if I can show you where to click, why can't I just click too? While trying to build computer-use agents during my job in Palo Alto, I hit the core limitation of today’s computer-use models where benchmarks hover in the mid-50% range (OSWorld). VLMs often know what to do but not what it looks like; without reliable visual grounding, agents misclick and stall. So, I built computer use—without the "use." It provides the visual grounding of an agent but keeps the human in the loop for the actual execution to prevent misclicks.<p>I personally use it for the AWS Console's "treasure hunt" UI, like creating a public S3 bucket with specific CORS rules. It’s also been surprisingly helpful for non-technical tasks, like navigating obscure settings in Gradescope or Spotify. Ourguide really works for any task when you’re stuck or don't know what to do.<p>You can download and test Ourguide here: <a href="https://ourguide.ai/downloads" rel="nofollow">https://ourguide.ai/downloads</a><p>The project is still very early, and I’d love your feedback on where it fails, where you think it worked well, and which specific niches you think Ourguide would be most helpful for.
Show HN: SF Microclimates
<a href="https://microclimates.solofounders.com/" rel="nofollow">https://microclimates.solofounders.com/</a>
Show HN: SF Microclimates
<a href="https://microclimates.solofounders.com/" rel="nofollow">https://microclimates.solofounders.com/</a>
Show HN: I wrapped the Zorks with an LLM
I grew up on the Infocom games and when microsoft actually open-sourced Zork 1/2/3 I really wanted to figure out how to use LLMs to let you type whatever you want, I always found the amount language that the games "understood" to be so limiting - even if it was pretty state of the art at the time.<p>So I figured out how to wrap it with Tambo.. (and run the game engine in the browser) basically whatever you type gets "translated" into zork-speak and passed to the game - and then the LLM takes the game's output and optionally adds flavor. (the little ">_" button at the top exposes the actual game input)<p>What was a big surprise to me is multi-turn instructions - you can ask it to "Explore all the rooms in the house until you can't find any more" and it will plug away at the game for 10+ "turns" at a time... like Claude Code for Zork or something
Show HN: I wrapped the Zorks with an LLM
I grew up on the Infocom games and when microsoft actually open-sourced Zork 1/2/3 I really wanted to figure out how to use LLMs to let you type whatever you want, I always found the amount language that the games "understood" to be so limiting - even if it was pretty state of the art at the time.<p>So I figured out how to wrap it with Tambo.. (and run the game engine in the browser) basically whatever you type gets "translated" into zork-speak and passed to the game - and then the LLM takes the game's output and optionally adds flavor. (the little ">_" button at the top exposes the actual game input)<p>What was a big surprise to me is multi-turn instructions - you can ask it to "Explore all the rooms in the house until you can't find any more" and it will plug away at the game for 10+ "turns" at a time... like Claude Code for Zork or something
Show HN: We Built the 1. EU-Sovereignty Audit for Websites
Show HN: We Built the 1. EU-Sovereignty Audit for Websites