The best Hacker News stories from Show from the past week
Latest posts:
Show HN: State of the Art of Coding Models, According to Hacker News Commenters
Hello HN,<p>I was away from my computer for two weeks, and after coming back and reading the latest discussions on HN about coding assistants (models, harnesses), I felt very out of the loop. My normal process would have been to keep reading and figure out the latest and greatest from people's comments, but I wanted to try and automate this process.<p>Basically the goal is to get a quick overview over which coding models are popular on HN. A next iteration could also scan for harnesses that people use, or info on self-hosting or hardware setups.<p>I wrote a short intro on the page about the pipeline that collects and analyzes the data, but feel free to ask for more details or check the Google Sheet for more info.<p><a href="https://hnup.date/hn-sota" rel="nofollow">https://hnup.date/hn-sota</a>
Show HN: GhostBox – Borrow a disposable little machine from the Global Free Tier
I built this because I was always creating machines on GH actions to test builds on different OS, and I wanted a tight CLI that could do it. I always saw Actions as this great resources and ephemeral machines you could do dev work in just were a natural way for me to work, so this grew out of that workflow.<p>I didn't expect it to blow up, so it wasn't 100% finished when I posted it. But it should stabilize pretty quickly.<p>Happy to know what you think and talk about it.
Show HN: WhatCable, a tiny menu bar app for inspecting USB-C cables
USB-C cables can be a mess. One cable charges at 5W, another does 100W and Thunderbolt 4, and they look identical in the drawer.<p>WhatCable sits in your menu bar and reads the cable data your Mac already has access to. Plug in a cable and it tells you in plain English what it can actually do: charging wattage, data speed, display support, Thunderbolt, etc.<p>Built in Swift/SwiftUI. Open source, free, no tracking.<p>GitHub: <a href="https://github.com/darrylmorley/whatcable" rel="nofollow">https://github.com/darrylmorley/whatcable</a>
Show HN: Rip.so – a graveyard for dead internet things
Show HN: Auto-Architecture: Karpathy's Loop, pointed at a CPU
Show HN: Auto-Architecture: Karpathy's Loop, pointed at a CPU
Show HN: Drive any macOS app in the background without stealing the cursor
Hi HN, Francesco from Cua here.
I hacked this project together last weekend, inspired by the Codex Computer-Use release and lessons learned from deploying GUI-operating agents for our customers.<p>The main problem: when a UI automation process controls a desktop app today, it usually takes over the human’s session. Your cursor moves, keyboard focus gets stolen, windows jump to the front, and you have to stop working until the agent is done. That is why we have historically avoided encouraging users to run these processes directly on their host machine, instead relying on VMs or GUI containers for concurrency and background execution.<p>But computer-use - the tools we give agents to operate computers like humans - does not scale cleanly that way. As models get smarter, agents need to share hosts safely, run in the background, and avoid collisions with the human or other agents using the same machine.<p>We realized macOS has no first-class API for "drive this app without touching the cursor". CGEventPost routes through the hardware input stream, so it moves your cursor. CGEvent.postToPid avoids the cursor warp, but Chromium treats those events as untrusted and silently drops clicks at the renderer boundary. Activating the target app first raises the window and pulls focus, defeating the point of background execution.<p>Cua Driver is our attempt at a real fix: a background computer-use driver for macOS that lets an agent click, type, scroll, and read native apps while your cursor, frontmost app, and Space stay where they are. The default interface is a CLI, so it is easy to script or call from any coding agent shell.<p>Try it on macOS 14+:<p>/bin/bash -c "$(curl -fsSL <a href="https://raw.githubusercontent.com/trycua/cua/main/libs/cua-driver/scripts/install.sh" rel="nofollow">https://raw.githubusercontent.com/trycua/cua/main/libs/cua-d...</a>)"<p>The first internal use case was delegated demo recording. We ask Claude Code to drive an app while 'cua-driver recording start' captures the trajectory, screenshots, actions, and click markers. The result is an agent-generated product demo, Screen Studio inspired.<p>Other things we have used it for:<p>- Replacing Vercel’s agent-browser and other browser-use CLIs. With Claude Code and Cua Driver, you do not need Chrome DevTools Protocol at all.<p>- A dev-loop QA agent that reproduces a visual bug, edits code, rebuilds, and verifies the UI while my editor stays frontmost.<p>- Personal-assistant flows that use iMessage from Claude Code, Hermes, or other general-purpose agent CLIs.<p>- Pulling visual context from Chrome, Figma, Preview, or YouTube windows I am not looking at, without relying on their APIs.<p>What made this harder than expected:<p>- CGEventPost warps the cursor because it goes through the HID stream.<p>- CGEvent.postToPid does not warp the cursor, but Chromium drops it at the renderer IPC boundary.<p>- Activating the target first raises the window and can drag you across Spaces.<p>- Electron apps stop keeping useful AX trees alive when windows are occluded without a private remote-aware SPI.<p>The unlock was SkyLight. SLEventPostToPid is a sibling of the public per-PID call, but it travels through a WindowServer channel Chromium accepts as trusted. Pair it with yabai’s focus-without-raise pattern, plus an off-screen primer click at (-1, -1), and the click lands without the window ever raising.<p>One thing we learned: the right addressing mode depends on the app. Native macOS apps usually have rich AX trees, Chromium-family apps often need a hybrid of AX and screenshots, and apps like Blender or CAD tools may expose almost no useful AX surface. The mistake is defaulting to pixels everywhere - or defaulting to AX everywhere.<p>Long technical writeup: <a href="https://github.com/trycua/cua/blob/main/blog/inside-macos-window-internals.md" rel="nofollow">https://github.com/trycua/cua/blob/main/blog/inside-macos-wi...</a><p>I would like feedback from people building Mac automation, agent harnesses, or accessibility tooling. If it breaks on an macOS app you care about, that is useful data for us.
Show HN: Live Sun and Moon Dashboard with NASA Footage
Show HN: Live Sun and Moon Dashboard with NASA Footage
Show HN: OSS Agent I built topped the TerminalBench on Gemini-3-flash-preview
Scored 65.2% vs google's official 47.8%, and the existing top closed source model Junie CLI's 64.3%.<p>Since there are a lot of reports of deliberate cheating on TerminalBench 2.0 lately (<a href="https://debugml.github.io/cheating-agents/" rel="nofollow">https://debugml.github.io/cheating-agents/</a>), I would like to also clarify a few things<p>1. Absolutely no {agents/skills}.md files were inserted at any point. No cheating mechanisms whatsoever<p>2. The cli agent was run in leaderboard compliant way (no modification of resources or timeouts)<p>3. The full terminal bench run was done using the fully open source version of the agent, no difference between what is on github and what was run.<p>I was originally going to wait for it to land on the leaderboard, but it has been 8 days and the maintainers do not respond unfortunately (there is a large backlog of the pull requests on their HF) so I decided to post anyways.<p>HF PR: <a href="https://huggingface.co/datasets/harborframework/terminal-bench-2-leaderboard/discussions/145" rel="nofollow">https://huggingface.co/datasets/harborframework/terminal-ben...</a><p>It is astounding how much the harness matters, based on this and other experiments I have done.
Show HN: OSS Agent I built topped the TerminalBench on Gemini-3-flash-preview
Scored 65.2% vs google's official 47.8%, and the existing top closed source model Junie CLI's 64.3%.<p>Since there are a lot of reports of deliberate cheating on TerminalBench 2.0 lately (<a href="https://debugml.github.io/cheating-agents/" rel="nofollow">https://debugml.github.io/cheating-agents/</a>), I would like to also clarify a few things<p>1. Absolutely no {agents/skills}.md files were inserted at any point. No cheating mechanisms whatsoever<p>2. The cli agent was run in leaderboard compliant way (no modification of resources or timeouts)<p>3. The full terminal bench run was done using the fully open source version of the agent, no difference between what is on github and what was run.<p>I was originally going to wait for it to land on the leaderboard, but it has been 8 days and the maintainers do not respond unfortunately (there is a large backlog of the pull requests on their HF) so I decided to post anyways.<p>HF PR: <a href="https://huggingface.co/datasets/harborframework/terminal-bench-2-leaderboard/discussions/145" rel="nofollow">https://huggingface.co/datasets/harborframework/terminal-ben...</a><p>It is astounding how much the harness matters, based on this and other experiments I have done.
Show HN: Free textbook on engineering thermodynamics
Author here. Feel free to send questions of any kind.
Show HN: Turning a Gaussian Splat into a videogame
Show HN: Turning a Gaussian Splat into a videogame
Show HN: A Karpathy-style LLM wiki your agents maintain (Markdown and Git)
I shipped a wiki layer for AI agents that uses markdown + git as the source of truth, with a bleve (BM25) + SQLite index on top. No vector or graph db yet.<p>It runs locally in ~/.wuphf/wiki/ and you can git clone it out if you want to take your knowledge with you.<p>The shape is the one Karpathy has been circling for a while: an LLM-native knowledge substrate that agents both read from and write into, so context compounds across sessions rather than getting re-pasted every morning. Most implementations of that idea land on Postgres, pgvector, Neo4j, Kafka, and a dashboard.<p>I wanted to go back to the basics and see how far markdown + git could go before I added anything heavier.<p>What it does:
-> Each agent gets a private notebook at agents/{slug}/notebook/.md, plus access to a shared team wiki at team/.<p>-> Draft-to-wiki promotion flow. Notebook entries are reviewed (agent or human) and promoted to the canonical wiki with a back-link. A small state machine drives expiry and auto-archive.<p>-> Per-entity fact log: append-only JSONL at team/entities/{kind}-{slug}.facts.jsonl. A synthesis worker rebuilds the entity brief every N facts. Commits land under a distinct "Pam the Archivist" git identity so provenance is visible in git log.<p>-> [[Wikilinks]] with broken-link detection rendered in red.<p>-> Daily lint cron for contradictions, stale entries, and broken wikilinks.<p>-> /lookup slash command plus an MCP tool for cited retrieval. A heuristic classifier routes short lookups to BM25 and narrative queries to a cited-answer loop.<p>Substrate choices:
Markdown for durability. The wiki outlives the runtime, and a user can walk away with every byte. Bleve for BM25. SQLite for structured metadata (facts, entities, edges, redirects, and supersedes). No vectors yet. The current benchmark (500 artifacts, 50 queries) clears 85% recall@20 on BM25 alone, which is the internal ship gate. sqlite-vec is the pre-committed fallback if a query class drops below that.<p>Canonical IDs are first-class. Fact IDs are deterministic and include sentence offset. Canonical slugs are assigned once, merged via redirect stubs, and never renamed. A rebuild is logically identical, not byte-identical.<p>Known limits:
-> Recall tuning is ongoing. 85% on the benchmark is not a universal guarantee.<p>-> Synthesis quality is bounded by agent observation quality. Garbage facts in, garbage briefs out. The lint pass helps. It is not a judgment engine.<p>-> Single-office scope today. No cross-office federation.<p>Demo. 5-minute terminal walkthrough that records five facts, fires synthesis, shells out to the user's LLM CLI, and commits the result under Pam's identity: <a href="https://asciinema.org/a/vUvjJsB5vtUQQ4Eb" rel="nofollow">https://asciinema.org/a/vUvjJsB5vtUQQ4Eb</a><p>Script lives at ./scripts/demo-entity-synthesis.sh.<p>Context. The wiki ships as part of WUPHF, an open source collaborative office for AI agents like Claude Code, Codex, OpenClaw, and local LLMs via OpenCode. MIT, self-hosted, bring-your-own keys. You do not have to use the full office to use the wiki layer. If you already have an agent setup, point WUPHF at it and the wiki attaches.<p>Source: <a href="https://github.com/nex-crm/wuphf" rel="nofollow">https://github.com/nex-crm/wuphf</a><p>Install: npx wuphf@latest<p>Happy to go deep on the substrate tradeoffs, the promotion-flow state machine, the BM25-first retrieval bet, or the canonical-ID stability rules. Also happy to take "why not an Obsidian vault with a plugin" as a fair question.
Show HN: A Karpathy-style LLM wiki your agents maintain (Markdown and Git)
I shipped a wiki layer for AI agents that uses markdown + git as the source of truth, with a bleve (BM25) + SQLite index on top. No vector or graph db yet.<p>It runs locally in ~/.wuphf/wiki/ and you can git clone it out if you want to take your knowledge with you.<p>The shape is the one Karpathy has been circling for a while: an LLM-native knowledge substrate that agents both read from and write into, so context compounds across sessions rather than getting re-pasted every morning. Most implementations of that idea land on Postgres, pgvector, Neo4j, Kafka, and a dashboard.<p>I wanted to go back to the basics and see how far markdown + git could go before I added anything heavier.<p>What it does:
-> Each agent gets a private notebook at agents/{slug}/notebook/.md, plus access to a shared team wiki at team/.<p>-> Draft-to-wiki promotion flow. Notebook entries are reviewed (agent or human) and promoted to the canonical wiki with a back-link. A small state machine drives expiry and auto-archive.<p>-> Per-entity fact log: append-only JSONL at team/entities/{kind}-{slug}.facts.jsonl. A synthesis worker rebuilds the entity brief every N facts. Commits land under a distinct "Pam the Archivist" git identity so provenance is visible in git log.<p>-> [[Wikilinks]] with broken-link detection rendered in red.<p>-> Daily lint cron for contradictions, stale entries, and broken wikilinks.<p>-> /lookup slash command plus an MCP tool for cited retrieval. A heuristic classifier routes short lookups to BM25 and narrative queries to a cited-answer loop.<p>Substrate choices:
Markdown for durability. The wiki outlives the runtime, and a user can walk away with every byte. Bleve for BM25. SQLite for structured metadata (facts, entities, edges, redirects, and supersedes). No vectors yet. The current benchmark (500 artifacts, 50 queries) clears 85% recall@20 on BM25 alone, which is the internal ship gate. sqlite-vec is the pre-committed fallback if a query class drops below that.<p>Canonical IDs are first-class. Fact IDs are deterministic and include sentence offset. Canonical slugs are assigned once, merged via redirect stubs, and never renamed. A rebuild is logically identical, not byte-identical.<p>Known limits:
-> Recall tuning is ongoing. 85% on the benchmark is not a universal guarantee.<p>-> Synthesis quality is bounded by agent observation quality. Garbage facts in, garbage briefs out. The lint pass helps. It is not a judgment engine.<p>-> Single-office scope today. No cross-office federation.<p>Demo. 5-minute terminal walkthrough that records five facts, fires synthesis, shells out to the user's LLM CLI, and commits the result under Pam's identity: <a href="https://asciinema.org/a/vUvjJsB5vtUQQ4Eb" rel="nofollow">https://asciinema.org/a/vUvjJsB5vtUQQ4Eb</a><p>Script lives at ./scripts/demo-entity-synthesis.sh.<p>Context. The wiki ships as part of WUPHF, an open source collaborative office for AI agents like Claude Code, Codex, OpenClaw, and local LLMs via OpenCode. MIT, self-hosted, bring-your-own keys. You do not have to use the full office to use the wiki layer. If you already have an agent setup, point WUPHF at it and the wiki attaches.<p>Source: <a href="https://github.com/nex-crm/wuphf" rel="nofollow">https://github.com/nex-crm/wuphf</a><p>Install: npx wuphf@latest<p>Happy to go deep on the substrate tradeoffs, the promotion-flow state machine, the BM25-first retrieval bet, or the canonical-ID stability rules. Also happy to take "why not an Obsidian vault with a plugin" as a fair question.
Show HN: I've built a nice home server OS
ohai!<p>I've released Lightwhale 3, which is possibly the easiest way to self-host Docker containers.<p>It's a free, immutable Linux system purpose-built to live-boot straight into a working Docker Engine, thereby shortcutting the need for installation, configuration, and maintenance. Its simple design makes it easy to learn, and its low memory footprint should make it especially attractive during these times of RAMageddon.<p>If this has piqued your interest, do check it out, along with its easy-to-follow Getting Started guide.<p>In any event,
have a nice day! =)
Show HN: How LLMs Work – Interactive visual guide based on Karpathy's lecture
All content is based on Andrej Karpathy's "Intro to Large Language Models" lecture (youtube.com/watch?v=7xTGNNLPyMI). I downloaded the transcript and used Claude Code to generate the entire interactive site from it — single HTML file. I find it useful to revisit this content time to time.
Show HN: How LLMs Work – Interactive visual guide based on Karpathy's lecture
All content is based on Andrej Karpathy's "Intro to Large Language Models" lecture (youtube.com/watch?v=7xTGNNLPyMI). I downloaded the transcript and used Claude Code to generate the entire interactive site from it — single HTML file. I find it useful to revisit this content time to time.
Show HN: Tolaria – Open-source macOS app to manage Markdown knowledge bases
Hey there! I am Luca, I write <a href="https://refactoring.fm/" rel="nofollow">https://refactoring.fm/</a> and I built Tolaria for myself to manage my own knowledge base (10K notes, 300+ articles written in over 6 years of newslettering) and work well with AI.<p>Tolaria is offline-first, file-based, has first-class support for git, and has strong opinions about how you should organize notes (types, relationships, etc).<p>Let me know your thoughts!