primitivesuave
primitivesuave on Hacker News
This is amazing work!! When I started this project, seeing a contribution like this was the dream, so thank you for making it happen!
I'll find a way to coordinate with you about reviewing and merging this in.
Glad to have found another one! I have the iOS/Android app ready and am going through the app store approval process, should be available very soon :)
Posted by
primitivesuave on Friday October 23, 2026 @01:13PM
from the show-hn dept.
https://drop7.dev
Sixteen years ago, I wrote a Java program which tried to pick the ideal move in a puzzle game called Drop7. On each turn, the player only has seven choices for their next move, but there is also an element of chance which turns this simple game into a surprisingly difficult problem involving search, hidden information, long-term planning, and chance.I renewed my investigation this weekend, into...
Thank you for the link! I love Observable notebooks.
Thank you! Very honored to be considered an educational gem :)
This is such a great idea. I didn't know about WebXR before reading your comment, and was delighted to see that this is a relatively easy thing to implement. I need to find some VR goggles to borrow so I can test this out, but I'll optimistically push out an update within the next day with the WebXR update.
Thank you!! I was also hitting performance issues, especially on mobile - I think the latest version has gotten it a bit closer to a smoother experience, but there is still a lot of low-hanging fruit on making this more fluid (especially the step transitions).
Yours is amazing work, and certainly a higher degree of fidelity than I was able to achieve with AI assistance. The initial motivation behind this was largely driven by curiosity around the rotor motion (the ratchet and pawl assembly), and then into how the wiring actually works. For my brain, I needed to press the keys a hundred times and watch the current flow before it started making sense.
I'm curious about how you worked out the inner dimensions and part placements so accurately. Thank you for providing this marvelous free resource!
I revamped the mobile experience last night, let me know what you think!
Thank you for the kind words! As mentioned in the other comment below, I'll open-source it very soon and update the site with a GitHub link.
Thank you for the suggestion and the kind words! Completely agree that the navigation is a bit unintuitive, will work on fixing that tonight :)
I will open-source it very soon! I was a bit nervous about putting it out there before I'm sure that the machines are absolutely accurate, especially the more niche ones where I had to make some inferences about the wiring. Will add the GitHub link to the site when I've had a chance to review everything for accuracy, and will probably end up moving some of my "educated guesses" off the main branch.
Thank you for the tip about mobile performance, my apologies for neglecting it and I'm working on fixing it right now!
Posted by
primitivesuave on Tuesday September 29, 2026 @01:15PM
from the show-hn dept.
https://enigma.design
I watched the excellent Veritasium video [1] on the Enigma machine, and watched the full animation by Jared Owen [2], but was still a bit confused on how the inner mechanics of an Enigma machine work. I used Astra to build out the inner components through a combination of reference images, writing out hundreds of extremely detailed prompts, and building my own inspection tools to ensure that...
The recent Epic vs Health Gorilla lawsuit is an example of how your medical records have almost certainly made it to the hands of many people you will never know about.
Rather than investigate all the things where investigative journalism could potentially make a difference to real human beings' lives, the Guardian has chosen to pursue a plea for the majority owner of Meta's voting shares (61%) to step down from his position of power. Let us politely ask Sisyphus to stop pushing the boulder instead.
Posted by
primitivesuave on Tuesday August 25, 2026 @12:17PM
from the show-hn dept.
https://drop7.dev
Sixteen years ago, I wrote a Java program which tried to pick the ideal move in a puzzle game called Drop7. On each turn, the player only has seven choices for their next move, but there is also an element of chance which turns this simple game into a surprisingly difficult problem involving search, hidden information, long-term planning, and chance.I renewed my investigation this weekend, into...
I've been meaning to write something about how I did it, and have been putting it off for a long time. I wrote all the tools myself - by that, I mean that everything was a web app running in my browser.
My advice would be to first set up an automation for yt-dlp to pull the media, then use Whisper to build a transcription pipeline. Chunk the transcript based on desired result granularity, then store embeddings in local Qdrant. It helps to use an orchestrator to handle all of this - my current recommendation is Dagster (dagster.io).
Excellent guess, and the documentary
All The Queen's Horses does a much better job explaining that story than I ever could!
This one is about Dolton, IL - the series is called "Dolton Documentaries" on YouTube.
Honored by your interested :) It is called "Dolton Documentaries".
My favorite real-world example that I worked on: I created a YouTube documentary series about corruption in a small town in Illinois. This required downloading thousands of hours of government meeting videos from YouTube, transcribing + chunking + embedding, summarizing meeting segments, running a couple passes of validation, then searching for interesting storylines. I also scraped thousands of public documents which exposed campaign finance violations and some truly nefarious stuff going on behind the scenes.
I did 90-95% of the work on this with a local GPU. I still ran Claude and Codex, but they were just writing code to orchestrate API calls against local models, local Whisper, etc. Doing the same with the public cloud would have cost thousands of dollars, instead it cost a few hundred dollars for a frontier lab subscription and tens of dollars for electricity.
I recently got into the DGX Spark and just a month ago, got an AMD Ryzen developer platform. Both are incredibly useful tools for some upcoming projects I'm working on (also related to government corruption), but in my limited experience of trying to run opencode on them, the "good models" are still completely unusable because the system prompt alone requires a minute of thinking.
My non-technical teammates use Claude Cowork extensively. We set up MCP servers to give them audited access to certain internal services, while they just have to think of MCP as a "connector" which they can configure in the GUI.
It's great to see SOC2 going in this direction. I've had to set up all kinds of compliance automation over the past decade (mainly Drata, Vanta, Oneleet), but at the end of the day it's a huge pain grabbing screenshots for what feels like a very performative process.
I asked a SOC2 auditor a while back about why they don't just make their own compliance automation dashboard, so we can pre-fill all their specific requests. They mentioned that certain rules are in place to separate evidence preparation from the actual auditing firms. However, after doing some armchair ChatGPT research, it seems like an audit firm could potentially be permitted to provide evidence management software, as long as you're not guaranteeing an audit result or preventing people from taking the evidence elsewhere. Perhaps you could shed light on the legal aspects and AICPA guidance here for providing evidence collection as AI skills to the companies you audit?
FWIW, Peter Norvig also gave an updated take on what programming will look like with LLMs around 2 years ago. It did give me some hope back then, but with the development of Fables and Kimis and Sols I think it's truly anyone's guess where the art of programming will go.
https://www.youtube.com/watch?v=ia6aJIplmtc
I deployed a Lambda function behind CloudFront which rendered a simple HTML page with the query results from executing some SQL over the dataset. I served millions of page views for next to nothing because most pages were already in the cache.
I don't know where you get this expectation that people should anticipate that a crawler might try every possible combination of query parameters, thereby missing the cache on each one. Most people consider it a bitter and arrogant perspective, which is why this got downvoted.
Yes, if I wanted to put a nice HTML interface over the query results then I would still end up with the same problem where some combinatoric explosion of query parameters to the `/search` endpoint, most of which are cache misses, leads to many many TBs of network egress.