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June 28, 2026 at 04:00 PM
A way to exclude sensitive files issue still open for OpenAI Codex
Hacker News (score: 96)[Other] A way to exclude sensitive files issue still open for OpenAI Codex
browser-use/video-use
GitHub Trending[Other] Edit videos with coding agents
Show HN: Decomp Academy – Learn to decompile GameCube games into matching C
Hacker News (score: 59)[Other] Show HN: Decomp Academy – Learn to decompile GameCube games into matching C Over the past few months I've been heavily involved in the decompilation community. I've been hands-on decompiling a beloved game from my childhood (Star Fox Adventures). I started this journey with zero prior decomp experience—and to make things worse I had never really touched C nor assembly either.<p>Learning how to decompile was challenging. It's difficult to find any good learning resources for it and any open-source projects for this are inactive and/or contain little actual learning material.<p>So I put together Decomp Academy! Decomp Academy is an interactive way to learn how to decompile PowerPC assembly back into C. The site runs a live Metrowerks CodeWarrior GC/2.0 compiler, converts your C into assembly, and then checks how close your assembly matches the target. If even 1 instruction or bit is off, that's a fail. This is the gold standard for video game decompilation and this is much stricter than a normal decompile.<p>As of writing there are 250+ lessons on the site and the lessons start at the very basics so anyone with a little programming experience should be able to jump straight in, even if you're not a C expert. Some lessons also have real functions taken from live open source decomp projects (Star Fox Adventures, Mario Party 4, Pikmin, Metroid Prime). The idea being you learn everything you need to know to be able to jump in and contribute to a real decompilation project when done.<p>The site is completely free, open source and you have access to all lessons without having to sign up. All lessons are stored in markdown in the repo (src/curriculum), it's trivial to add or modify lessons. The site is very new and the lessons are rapidly changing every day with a whole C++ section on the way. The site has already been well received by the decomp community and I'm happy to share it with HN. I'm very keen on others to contribute to this project and I hope this becomes the best resource on the internet for learning the art of decompilation. Please let me know what you think!<p>Source: <a href="https://github.com/JackPriceBurns/decomp-academy-fe" rel="nofollow">https://github.com/JackPriceBurns/decomp-academy-fe</a>
Show HN: KV-psi, using Linux PSI to to trim an LLM KV cache
Show HN (score: 6)[Other] Show HN: KV-psi, using Linux PSI to to trim an LLM KV cache I thought it'd be interesting to use Linux PSI (Pressure Stall Information) for an LLM runtime to trim the KV cache. This is mainly useful imo for edge devices like the Jetson Orin super nano kit which have unified memory. I haven't benched much, but plan to do so more over time and see if I can make a real use of it as I run local LLMs. Let me know if it makes sense :P (I of course vibed this idea)
Enhancing X11 Application Security with LXC
Hacker News (score: 18)[Other] Enhancing X11 Application Security with LXC
Show HN: Adrafinil – keep a lid-closed Mac awake only while agents work
Hacker News (score: 71)[Other] 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).
Anonymous GitHub account mass-dropping undisclosed 0-days
Hacker News (score: 47)[Other] Anonymous GitHub account mass-dropping undisclosed 0-days
Fission-AI/OpenSpec
GitHub Trending[Other] Spec-driven development (SDD) for AI coding assistants.
anomalyco/opencode
GitHub Trending[Other] The open source coding agent.
Show HN: The TypeScript Semantic Layer for ClickHouse
Show HN (score: 5)[API/SDK] Show HN: The TypeScript Semantic Layer for ClickHouse I've built a type-safe semantic layer in code, for ClickHouse. If you're building analytics off ClickHouse in TypeScript, I would love your feedback.<p>With hypequery there is no platform to adopt, no YAML sprawl. It runs where your app runs.<p>Key features:<p>- Define metrics once, reuse them everywhere: Declare dimensions and measures in one place and then pull from the same source of truth.<p>- Compiles to ClickHouse SQL: No service, no proxy, no extra runtime to deploy. It's a library that generates SQL and runs where your app runs.<p>- Multi-tenancy & Authentication ready: Cross-tenant queries are blocked at the query layer, helpers to plug into your existing auth.<p>- Agent-native: A dataset is a declared set of dimensions and measures, so it doubles as an allowlist. Includes an MCP server to hand an LLM a typed catalog to query.<p>- Runtime HTTP entry point: serve() exposes any dataset as an endpoint, so the same type-safe definitions back your dashboards and your API.
DSpark: Speculative decoding accelerates LLM inference [pdf]
Hacker News (score: 600)[Other] DSpark: Speculative decoding accelerates LLM inference [pdf]
Beer CSS – Build material design in record time
Hacker News (score: 114)[Other] Beer CSS – Build material design in record time
Show HN: Hacker News on a train station-style flip board
Hacker News (score: 31)[Other] 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: Mantis, A self-hosted LLM gateway
Show HN (score: 5)[DevOps] Show HN: Mantis, A self-hosted LLM gateway Hey HNers - Riz here.<p>I got together with a few guys and we built an LLM gateway.<p>It's designed for small teams working on early-stage products, and can be deployed to AWS using a single command (i.e. `mantis deploy`).<p>It's self-hosted, and is designed to belong to you.
Slisp: Simple Lisp compiler (Linux/amd64)
Hacker News (score: 51)[Other] Slisp: Simple Lisp compiler (Linux/amd64)
How to Corrupt an SQLite Database File
Hacker News (score: 12)[Other] How to Corrupt an SQLite Database File
Previewing GPT‑5.6 Sol: a next-generation model
Hacker News (score: 972)[Other] Previewing GPT‑5.6 Sol: a next-generation model System card: <a href="https://deploymentsafety.openai.com/gpt-5-6-preview" rel="nofollow">https://deploymentsafety.openai.com/gpt-5-6-preview</a>
Show HN: Smart model routing directly in Claude, Codex and Cursor
Hacker News (score: 89)[API/SDK] 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!