The best Hacker News stories from Show from the past day
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Show HN: DBOSify – Drop-in Temporal replacement built on Postgres
Show HN: Hacker News on a train station-style flip board
Although the page itself is more just fun to have made and look at (I like the flip sound), the fun part is how I made it to verify the (and I hate to say it) vibe host service I've been working on. The recent flip board back and forth's on Twitter (X) are what inspired me.<p>The idea here is that people (like me or you) can create something neat like this, and others can remix it, change it and publish their own version. This is that all in action and it worked great. I wrote a blog about it (the blog is dogfooding, it's just an app hosted on quickish that uses the built in db lib).<p>For the HN version of this flip board I use their firebase api via the built in quickish server functions that make use of the fact that the front-end can get realtime updates (now that you mention firebase) from cloud function db updates. Of course that's over-kill but I wanted to show something fun. You can remix and host your own version for free, just need a google oauth login that's it.<p>OG flip board I built (Portland Based - Current Weather): <a href="https://popflame.quickish.space/flipboard-preview" rel="nofollow">https://popflame.quickish.space/flipboard-preview</a><p>Blog post that dives a tiny bit deeper: <a href="https://popflame.quickish.space/blog/hacker-news-on-a-split-flap-board/" rel="nofollow">https://popflame.quickish.space/blog/hacker-news-on-a-split-...</a>
Show HN: Adrafinil – keep a lid-closed Mac awake only while agents work
A month ago there was a wave of posts and tweets about engineers walking around cafes and parks with their MacBooks propped half-open, as fully closing the lid forces sleep that stops their AI agents. Some people made snarky comments about using tmux or Amphetamine, and some defended their choice with “but I only need it sometimes, and forgetting to disable Amphetamine and finding my laptop discharged in my bag is worse.”<p>This is a solution to this problem. Unlike caffeinate, it will prevent your MacBook from sleeping even with the lid closed, with no external power or display, using pmset disablesleep 1. Unlike other sleep-preventing apps, Adrafinil only activates when there’s an agent actively doing something. It detects agent activity through hooks it installs into Claude Code, Codex, and others. To reassure you it’s working, the app shows the active status in the menu bar, and it plays a chime when you close the lid.<p>Once the agent is done, Adrafinil detects it and lets the laptop go to sleep by setting pmset disablesleep back to 0. It will also let it sleep in case of overheating. And if you want to manually toggle it, you can install an optional MCP and tell your agent to keep the MacBook awake for a specific time.<p>It has four binaries, one of which is a root helper exposing a single setSleepBlocked call. All the logic and policy live in the unprivileged parts. They’re all notarized, and the app is fully open source (MIT).
Show HN: StartupsBR – A map of Brazilian startups
I couldn't find a simple way to explore the Brazilian startup ecosystem geographically, as I can in other places like the Bay Area or London, so I built one.<p>The map currently includes hundreds of startups from Sao Paulo and their job opportunities.<p>The most interesting thing I've learned so far is how clustered startup activity is in a handful of areas.<p>I'd love to hear your thoughts.<p>The EN version: <a href="https://www.startupsbr.com/sao-paulo" rel="nofollow">https://www.startupsbr.com/sao-paulo</a>
Show HN: WebBase-III – dBASE III rebuilt in the browser with its own interpreter
Show HN: WebBase-III – dBASE III rebuilt in the browser with its own interpreter
Show HN: Overfitted a 900KB Transformer to Compress a 100MB CSV into 7MB
I built an experiment that uses an overfitted transformer and arithmetic coding to compress individual files.<p>Instead of training the model to generalize, I train a 900KB transformer to memorize a single file and predict the next byte. Those predictions are fed into an arithmetic coder to produce the compressed output.<p>On a 100MB NYC taxi CSV, it compresses to about 7MB (~0.5 bits/byte). On a 100MB slice of enwik9, it compresses to about 21MB (~1.68 bits/byte).<p>It's pretty slow right now (roughly 20–30 minutes of training and 45 minutes each for compression and decompression on my AMD 7800XT).<p>Checkout the repo - <a href="https://github.com/samyak112/pym-particles" rel="nofollow">https://github.com/samyak112/pym-particles</a>
Show HN: Overfitted a 900KB Transformer to Compress a 100MB CSV into 7MB
I built an experiment that uses an overfitted transformer and arithmetic coding to compress individual files.<p>Instead of training the model to generalize, I train a 900KB transformer to memorize a single file and predict the next byte. Those predictions are fed into an arithmetic coder to produce the compressed output.<p>On a 100MB NYC taxi CSV, it compresses to about 7MB (~0.5 bits/byte). On a 100MB slice of enwik9, it compresses to about 21MB (~1.68 bits/byte).<p>It's pretty slow right now (roughly 20–30 minutes of training and 45 minutes each for compression and decompression on my AMD 7800XT).<p>Checkout the repo - <a href="https://github.com/samyak112/pym-particles" rel="nofollow">https://github.com/samyak112/pym-particles</a>
Show HN: Smart model routing directly in Claude, Codex and Cursor
We built a model router that plugs into coding agents (e.g. Claude Code, Codex, Cursor, etc.) and intelligently sends requests to the best model to serve them. Here's a quick demo of running it locally: <a href="https://www.youtube.com/watch?v=isKhAyivtfM" rel="nofollow">https://www.youtube.com/watch?v=isKhAyivtfM</a>.<p>At Weave, we write most of our code with AI, and it's been getting more expensive. This came to a head when Opus 4.7 was released and, thanks to its tokenizer changes, our costs shot up. We knew we didn't need Opus for <i>everything</i> but we didn't want to lose out on the intelligence for the cases where you really need it. So we decided to build a model router to handle this for us.<p>The Weave Router acts as an Anthropic/OpenAI endpoint specifically for coding agents. It looks at every inference request and intelligently (more on that in a sec) decides what model to send it to, handling all the translations required along the way. So it can use faster/cheaper models (e.g. DeepSeek v4, GLM 5.2, Kimi K2.6) when possible, and frontier models (Opus 4.8 & GPT 5.5 (& Fable whenever it's back)) when necessary.<p>How do we know what model to route to? We trained an RL model on tens of thousands (so far!) of agent traces. We reward the routing model when it selects an LLM that successfully completes the given task.<p>Here's an example: if you ask the router to plan a complex change, it will (probably) route that request to Opus 4.8. Subagents exploring the codebase to gather context will be routed to more suitable models (e.g. DeepSeek V4 Flash). Then when you have the plan ready to implement, it will be (most likely) be handed to a quicker model (e.g. GLM 5.2) to carry it out.<p>We've been using this internally for the last month or so. We've saved 40% on tokens vs. what we otherwise would have paid, with no noticeable differences in quality or velocity.<p>The router is source-available under Elastic License 2.0, so you can self-host it. Or if you prefer, you can also use our hosted version: weaverouter.com.<p>I'll be here to answer any questions you may have!
Show HN: Smart model routing directly in Claude, Codex and Cursor
We built a model router that plugs into coding agents (e.g. Claude Code, Codex, Cursor, etc.) and intelligently sends requests to the best model to serve them. Here's a quick demo of running it locally: <a href="https://www.youtube.com/watch?v=isKhAyivtfM" rel="nofollow">https://www.youtube.com/watch?v=isKhAyivtfM</a>.<p>At Weave, we write most of our code with AI, and it's been getting more expensive. This came to a head when Opus 4.7 was released and, thanks to its tokenizer changes, our costs shot up. We knew we didn't need Opus for <i>everything</i> but we didn't want to lose out on the intelligence for the cases where you really need it. So we decided to build a model router to handle this for us.<p>The Weave Router acts as an Anthropic/OpenAI endpoint specifically for coding agents. It looks at every inference request and intelligently (more on that in a sec) decides what model to send it to, handling all the translations required along the way. So it can use faster/cheaper models (e.g. DeepSeek v4, GLM 5.2, Kimi K2.6) when possible, and frontier models (Opus 4.8 & GPT 5.5 (& Fable whenever it's back)) when necessary.<p>How do we know what model to route to? We trained an RL model on tens of thousands (so far!) of agent traces. We reward the routing model when it selects an LLM that successfully completes the given task.<p>Here's an example: if you ask the router to plan a complex change, it will (probably) route that request to Opus 4.8. Subagents exploring the codebase to gather context will be routed to more suitable models (e.g. DeepSeek V4 Flash). Then when you have the plan ready to implement, it will be (most likely) be handed to a quicker model (e.g. GLM 5.2) to carry it out.<p>We've been using this internally for the last month or so. We've saved 40% on tokens vs. what we otherwise would have paid, with no noticeable differences in quality or velocity.<p>The router is source-available under Elastic License 2.0, so you can self-host it. Or if you prefer, you can also use our hosted version: weaverouter.com.<p>I'll be here to answer any questions you may have!
Show HN: Write SaaS apps where users control where their data is stored
Hello HN,<p>I would like to share with you linkedrecords.com - an open source backend as a service I'm working on since some time now. You can think of it as an firebase/convex alternative with an interesting twist.<p>In 2018 I needed to write large software requirements/architecture documents in Google Docs. While I was annoyed by the limitations of Google Docs back then (no captions on figures, no automatic heading numbering, slow when docs are bigger,...) I was still fascinated by the real time collaboration features of it. So I've started a quest to understand how it works and I begun to implement an alternative to Google Docs.<p>I was convinced that this kind of real time collaboration is the future so I've given it much thought how I could make this as generic as possible so I could use it in all future tools I would build.<p>In the same time I was playing around with firebase (surprisingly you can not build a google docs alternative with firebase that easy as their real time collaboration does not provide merging text but rather just JSON). And back then I was also convinced that backend as a service is the right way to go. I was thinking that one of the most important reason we were still writing custom backend code is because of authorization.<p>I also was faced with another problem when trying to make the backend as generic as possible: relations between entities are also domain specific. E.g. A Documents can have many comments.<p>Luckily I was intrigued by another concept back in 2018 it was called web 3.0. Back in 2018 this had nothing to do with crypto. It was used as a term to refer to the semantic web and the resource description framework as one of its standards. There are also some RDF implementations which I could have reused but they are all XML and mostly Java based. I needed something light. Instead of implementing my own RDF product I took the idea of the RDF triplestore and came up with my own interpretation of it.<p>Using concepts like: triplestores and schema-on-read, I came up with a system that does not has any business logic in its backend and while working on my Google Docs alternative I felt in love with it as I've discovered some properties I did not anticipated from the get go:<p>- Dealing with global state in react is very easy. It feels like you use an SQL client in your browser and all queries are reactive and always up to date. When writing a query you do not have to think about authorization it's all backed in.
- Because the backend is 100% free of domain specific code you can point your single page app to any linkedrecords deployment.
- You never have to write backend code
- Its quite efficient when using AI agents<p>The best way to experience it, is to follow this little tutorial: <a href="https://linkedrecords.com/getting-started/" rel="nofollow">https://linkedrecords.com/getting-started/</a><p>It takes a while to get a hang of it so you have to have an open mind.<p>I would love to read your feedback on this.
Show HN: Turn native language audio into flashcards and shadowing practice
Here is a tool I built initially for myself to help with my German and Greek language studies. It started as a hack for creating Anki cards from native language audio. It extracts the words, finds their base forms (lemmas) and groups the examples by the lemma. At some point I realised that I have a transcription with word level timestamps that opens a lot of other opportunities. So I added a mode to click the first and last word in the transcript and it starts looping with the right gap and repeat count.<p>Another feature I use a lot is selecting an audio fragment, sending a predefined prompt to an AI to "explain grammar" or "explain nuances of meaning" and I still experimenting with prompts.<p>And because shadowing is so easy I also use it as a player to improve my English pronunciation. (I am not a native English speaker.)<p>I made a quick video showing the workflow for creating Anki cards and shadowing: <a href="https://youtu.be/TaR58uuDBvU?si=o5aGLAi2S-BZ7Zy9" rel="nofollow">https://youtu.be/TaR58uuDBvU?si=o5aGLAi2S-BZ7Zy9</a><p>The app supports 15 input languages (Japanese and Chinese are the latest experimental additions), and more than 30 output languages.<p>I would really appreciate it if you could try it <a href="https://lingochunk.com/try" rel="nofollow">https://lingochunk.com/try</a>. I know there are other tools with similar functionality but I created something that fits my workflow and it is fun to build.<p>Also I struggled to find public domain audio for the try page. I'd be grateful if anyone could point me to public domain sources (I used LibriVox, Wikimedia and FSI courses), or if you're a creator, let me feature some of your own recordings with credits and links.
Show HN: Turn native language audio into flashcards and shadowing practice
Here is a tool I built initially for myself to help with my German and Greek language studies. It started as a hack for creating Anki cards from native language audio. It extracts the words, finds their base forms (lemmas) and groups the examples by the lemma. At some point I realised that I have a transcription with word level timestamps that opens a lot of other opportunities. So I added a mode to click the first and last word in the transcript and it starts looping with the right gap and repeat count.<p>Another feature I use a lot is selecting an audio fragment, sending a predefined prompt to an AI to "explain grammar" or "explain nuances of meaning" and I still experimenting with prompts.<p>And because shadowing is so easy I also use it as a player to improve my English pronunciation. (I am not a native English speaker.)<p>I made a quick video showing the workflow for creating Anki cards and shadowing: <a href="https://youtu.be/TaR58uuDBvU?si=o5aGLAi2S-BZ7Zy9" rel="nofollow">https://youtu.be/TaR58uuDBvU?si=o5aGLAi2S-BZ7Zy9</a><p>The app supports 15 input languages (Japanese and Chinese are the latest experimental additions), and more than 30 output languages.<p>I would really appreciate it if you could try it <a href="https://lingochunk.com/try" rel="nofollow">https://lingochunk.com/try</a>. I know there are other tools with similar functionality but I created something that fits my workflow and it is fun to build.<p>Also I struggled to find public domain audio for the try page. I'd be grateful if anyone could point me to public domain sources (I used LibriVox, Wikimedia and FSI courses), or if you're a creator, let me feature some of your own recordings with credits and links.
Show HN: Turn native language audio into flashcards and shadowing practice
Here is a tool I built initially for myself to help with my German and Greek language studies. It started as a hack for creating Anki cards from native language audio. It extracts the words, finds their base forms (lemmas) and groups the examples by the lemma. At some point I realised that I have a transcription with word level timestamps that opens a lot of other opportunities. So I added a mode to click the first and last word in the transcript and it starts looping with the right gap and repeat count.<p>Another feature I use a lot is selecting an audio fragment, sending a predefined prompt to an AI to "explain grammar" or "explain nuances of meaning" and I still experimenting with prompts.<p>And because shadowing is so easy I also use it as a player to improve my English pronunciation. (I am not a native English speaker.)<p>I made a quick video showing the workflow for creating Anki cards and shadowing: <a href="https://youtu.be/TaR58uuDBvU?si=o5aGLAi2S-BZ7Zy9" rel="nofollow">https://youtu.be/TaR58uuDBvU?si=o5aGLAi2S-BZ7Zy9</a><p>The app supports 15 input languages (Japanese and Chinese are the latest experimental additions), and more than 30 output languages.<p>I would really appreciate it if you could try it <a href="https://lingochunk.com/try" rel="nofollow">https://lingochunk.com/try</a>. I know there are other tools with similar functionality but I created something that fits my workflow and it is fun to build.<p>Also I struggled to find public domain audio for the try page. I'd be grateful if anyone could point me to public domain sources (I used LibriVox, Wikimedia and FSI courses), or if you're a creator, let me feature some of your own recordings with credits and links.
Show HN: MiniPCs.zip – Charting the Pareto frontier of Mini PCs
The overall idea is to chart out the thousands of Mini PCs by benchmark and reveal the Pareto Front so you can get the most Compute per Dollar. Definitely a labor of love as I have a number of Mini PCs for my "homelab" (TrueNAS, piHole, Plex, basic stuff). It uses Gemini to extract specs from listings (since they're not often strongly categorized).<p>Quick blog post here: <a href="https://luke.zip/posts/pareto-pcs/" rel="nofollow">https://luke.zip/posts/pareto-pcs/</a>
Show HN: MiniPCs.zip – Charting the Pareto frontier of Mini PCs
The overall idea is to chart out the thousands of Mini PCs by benchmark and reveal the Pareto Front so you can get the most Compute per Dollar. Definitely a labor of love as I have a number of Mini PCs for my "homelab" (TrueNAS, piHole, Plex, basic stuff). It uses Gemini to extract specs from listings (since they're not often strongly categorized).<p>Quick blog post here: <a href="https://luke.zip/posts/pareto-pcs/" rel="nofollow">https://luke.zip/posts/pareto-pcs/</a>
Show HN: Bible as RAG Database
Made this in a free evening. Index an permissive license translation of the Bible (WEB) into a RAG database to allow returning passages of similar semantic meaning. Lots of fun. For example, "more money more problems" returns Ecclesiastes 5:9-13 which, I'll just say, is spot on..<p>"Moreover the profit of the earth is for all. The king profits from the field. He who loves silver shall not be satisfied with silver, nor he who loves abundance, with increase. This also is vanity. When goods increase, those who eat them are increased; and what advantage is there to its owner, except to feast on them with his eyes? The sleep of a laboring man is sweet, whether he eats little or much; but the abundance of the rich will not allow him to sleep. There is a grievous evil which I have seen under the sun: wealth kept by its owner to his harm."<p>Anyway - thought it was fun enough to share. It's slow and I vibe coded it so I haven't sorted out how to make it not take 15 seconds to vector search against the full 4GB index.
Show HN: Bible as RAG Database
Made this in a free evening. Index an permissive license translation of the Bible (WEB) into a RAG database to allow returning passages of similar semantic meaning. Lots of fun. For example, "more money more problems" returns Ecclesiastes 5:9-13 which, I'll just say, is spot on..<p>"Moreover the profit of the earth is for all. The king profits from the field. He who loves silver shall not be satisfied with silver, nor he who loves abundance, with increase. This also is vanity. When goods increase, those who eat them are increased; and what advantage is there to its owner, except to feast on them with his eyes? The sleep of a laboring man is sweet, whether he eats little or much; but the abundance of the rich will not allow him to sleep. There is a grievous evil which I have seen under the sun: wealth kept by its owner to his harm."<p>Anyway - thought it was fun enough to share. It's slow and I vibe coded it so I haven't sorted out how to make it not take 15 seconds to vector search against the full 4GB index.
Show HN: Chess-Inspired Roguelike
Show HN: Chess-Inspired Roguelike