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The lifesaving secret hidden inside a horseshoe crab's blue blood

US hires over 2k video gamers as air traffic controllers

pg_clickhouse v0.10: Subquery pushdown and 1000x faster TPC-H queries

Making holograms with a pen plotter

The Tradeoffs Facing Japan's Economy

Show HN: Pulp – Zero-allocation C11 telemetry engine (28M logs/SEC to disk)

Show HN: TermDOM – HTML, CSS and JavaScript (With a Real DOM) for TUIs and CLIs TermDOM renders a real DOM styled with real CSS to terminal cells. You build a document with createElement or innerHTML, or any frontend web framework, and it automatically produces colored ANSI output, with browser-style layout, text wrapping and flexbox included. The library can also be used to translate HTML to static ANSI.<p>Full disclaimer: This project was started a year ago and written entirely by Claude. I mainly provided QA and words of encouragement (yelling).

Go is an ideal language for AI-assisted software engineering

29 editorial diagram types for Claude Code. Self-contained HTML + SVG. No shadows, no Mermaid-slop.

Show HN: Git-knife – edit commit messages, authors, and dates like a spreadsheet

Show HN: Tokyo Trains Semi inspired by the 3d Shinjuku station that was posted again recently, I noticed it was missing a large portion of the &quot;complex&quot; where &quot;complex&quot; is defined loosly has how far you can walk without stepping outside.<p>So I asked Claude to make a 3d map of all Tokyo Trains, no libraries, and let you zoom into stations, and the first version with both map and the Shinjuku complex was ready in about 3 hours. It spent another 7 or so in various nit picky things I asked for to get to the current version.<p>I know these will only get better but I think the thing I find most interesting is no libraries needed. Claude can write the shaders from scratch, it can do both WebGPU and WebGL, and it can often write optimal solutions. For example, the entire map&#x2F;station&#x2F;trains is rendered in 5 draw calls. I didn&#x27;t ask for that, it just did it.<p>This one has lots of imprefections. Most of that comes down to data and&#x2F;or deciding how to use the data provided. For example, AFAICT there is nothing that says &quot;these parts make the complex&quot;. It&#x27;s something you either need to derive or hand code rules&#x2F;lists (include this, don&#x27;t include that).<p>Anyway, I know not everyone is into it but I&#x27;m having fun.

Launch HN: Keet (YC S24) – An app to create video courses on anything Hi HN! We’re Zack and Tommy the Co-Founders of Keet (<a href="https:&#x2F;&#x2F;trykeet.com">https:&#x2F;&#x2F;trykeet.com</a>). We are building a mobile app that generates courses on any topic, with short videos for explanation and games for reinforcement. Courses mirror a real curriculum to help you learn over an extended period of time.<p>Tommy and I met in linear algebra class in college and spent the next 4 years taking classes together. Our friendship was formed around learning new things. In school, someone else designs the curriculum, delivers the content, and writes the assessments. All you have to do is show up. Learning without this structure was frustrating, and there was a lot of friction to get started.<p>Zack has a coffee obsession and struggled to assemble youtube videos, conversations with ChatGPT, and the books he was reading into a coherent understanding of all of the different variables that go into brewing a cup of coffee. His attempts gave him the freedom to follow his curiosity, but the instructional design was difficult. Every piece of content either presumed some prerequisite knowledge or none at all.<p>Keet is our attempt at providing the autonomy to teach yourself anything while adding a structure conducive to learning. It finds a custom starting point and sequences lessons in a logical order.<p>We have found Keet most useful in the following scenarios:<p>- You have a subject matter interest that you enjoy passively learning about. (i.e. you really enjoy learning about medieval history and generate courses on medieval engineering)<p>- You want to explore a niche topic of a subject area you already know a lot about. (i.e. You know a lot about biology but want to explore how migratory animals sense Earth’s magnetic field.)<p>- You see a really niche topic get mentioned somewhere you want to explore more (i.e History of Penny Universities, Double Entry Book keeping or Robert Moses and the creation of the BQE)<p>When you create a course we ask some questions about how difficult it should be, how much depth the course should go into, and a few optional intent questions to understand what content you want to learn about. In the future, we’d like to have a global prerequisite map so that we can understand what each user already knows, so we can generate tailored courses to someone’s prerequisite knowledge. If someone majored in Computer Science, for example, their course should look pretty different to someone who might have no background in STEM.<p>After understanding your goals and intent, we categorize the course based on Biglan categories. Biglan categories have four quadrants:<p>- Hard–Pure (e.g., mathematics, theoretical physics)<p>- Hard-Applied (e.g., engineering, and applied sciences)<p>- Soft–Pure (e.g., history, literature, philosophy)<p>- Soft-Applied (e.g., policy, management, education, social work)<p>We use these categories to adjust instructions to better suit the topic. One instance of this is when searching for examples. A hard-pure course will look for worked problems, proofs, and real world cases, whereas soft-pure courses use primary source narratives and contrasting perspectives.<p>We tried building this as a website and then as a mobile app with just text. The website was bad because we couldn’t engage with the content from anywhere, and when we did engage, the text was boring and couldn’t add clarity to complex ideas. Vox and 3B1B videos made complex ideas accessible, which inspired us to move towards video based lessons. There was never one aha moment that made it work. Over the course of the past year, we’ve been using and iterating on the product until we enjoyed using it.<p>We have two types of explainer videos that are built using Manim (<a href="https:&#x2F;&#x2F;www.manim.community&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.manim.community&#x2F;</a>) and Remotion (<a href="https:&#x2F;&#x2F;www.remotion.dev&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.remotion.dev&#x2F;</a>). Manim is used for videos that require math visualizations while the Remotion videos are intended to animate processes and show primary source material to mimic something like a Vox video.<p>We are also building more engaging ways to complete assessments via custom activities. For example, in a genetics course, learners might interact with a Watson-Crick DNA model rather than answering a multiple choice question about base pairs.<p>You can download the Test flight beta (<a href="https:&#x2F;&#x2F;testflight.apple.com&#x2F;join&#x2F;wkWW2enA" rel="nofollow">https:&#x2F;&#x2F;testflight.apple.com&#x2F;join&#x2F;wkWW2enA</a>) today. We are giving 3 free course generations to every user. You can use the code “KEETHN” on the waitlist screen. When you download the app, try to generate a course on a niche interest&#x2F;something very specific. The coolest courses that we’ve seen are generated in those categories.<p>[ Notes ]<p>- Personalization is still early. Today, Keet mostly adapts around the topic and course goal; we want it to adapt much more around a learner’s background, pace, and weak spots.<p>- Course generation is slow. We made a deliberate trade off to sacrifice generation time in order to gain higher quality courses, since users are going to be taking these courses for an extended period of time.<p>- We are actively working to improve reinforcement quality. It is easy to generate quizzes, but much harder to generate interactions drive home the concept.<p>[ Pricing ]<p>We plan to have a monthly subscription that gives users credits they can use to generate courses. This will be a model similar to Suno (<a href="https:&#x2F;&#x2F;suno.com&#x2F;" rel="nofollow">https:&#x2F;&#x2F;suno.com&#x2F;</a>).

Flock wanted to tap dashcams in rideshare vechicles to add to surveillance data

Stealing Reasoning Traces from Proprietary LLM APIs

Neutrinos from Deep Inside Earth Provide a New Picture of the Mantle

Show HN: Parley – your coding agent can talk to a teammate's agent Hi HN,<p>I saw one friction point when working as part of a team that uses coding agents extensively - there is nothing to enable coordination between agent used by people in a team. Many times my agent would ask me to decide upon something with a fellow teammate, for which I have to serve as the network layer.<p>So I built Parley where agents can connect to the hub over MCP with their own team-scoped token. An agent addresses a teammate&#x27;s agent by name and ask questions&#x2F;handover tasks. Agents can also use file claims to signal what files they are working on, to highlight overlapping work. Everything is recorded for audit.<p>If an agent needs human decision&#x2F;approval, it can ping over Slack&#x2F;Telegram, and get replies over the same.<p>The hard part was making an agent wake up from an idle session and start working, so I built an optional feature called Claude Live Wake. If the exact project session is already running, Parley can wake the idle Claude session using channels, and notify it that eligible work is waiting.<p>Another challenge was trust- anything another agent sends has to be treated as untrusted input. Every message is tagged by origin - human, agent, or system. Message bodies only enter an agent when it explicitly fetches instead of injecting mid turn. These are specifically mentioned to be treated as string messages instead of prompts&#x2F;commands.

Animation engine for explanatory math videos

What I learned by putting GitHub Copilot behind a MitM proxy

Closing Canario Terminal source code

France to ban unsolicited telemarketing calls