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[Other] NumKong: 2'000 Mixed Precision Kernels for All

[Other] The way CTRL-C in Postgres CLI cancels queries is incredibly hack-y

[CLI Tool] Show HN: Sonar – A tiny CLI to see and kill whatever's running on localhost

[Other] Android developer verification: Balancing openness and choice with safety

[Other] From Oscilloscope to Wireshark: A UDP Story (2022)

[Other] NanoGPT Slowrun: 10x Data Efficiency with Infinite Compute

[Other] Show HN: Oku – One tab to filter out noise from feeds and content sources Hey everyone,<p>For a while now I&#x27;ve been frustrated with how I was &#x27;experiencing&#x27; the internet. From opening articles and getting bombarded with popups, banners and ads to opening feeds and seeing so much AI spam and algorithm-based content I was not interested in. If you add tab hopping to that, you get how it all becomes a confusing and not-so productive experience.<p>Oku.io is my solution to this problem. It&#x27;s a tool that allows you to create organized, clean boards with the feeds and content you&#x27;re interested in (HN Show&#x2F;Front&#x2F;Ask, ProductHunt, Reddit, RSS, and a lot more), and see them either in a grid to monitor all at once, in a focus view where you visualize one panel at a time, or in a daily&#x2F;weekly email digest that extracts the top content from each panel.<p>I&#x27;ve been actively using it and I&#x27;m happy with how it turned out. I find myself scrolling and switching tabs way less, and I feel like I&#x27;m not missing anything important anymore. Both for my work-related stuff and for my personal interests.<p>If you check it out, I&#x27;d love to hear your feedback. I&#x27;m very keen on continuing to improve it.

[Other] Google details new 24-hour process to sideload unverified Android apps <a href="https:&#x2F;&#x2F;android-developers.googleblog.com&#x2F;2026&#x2F;03&#x2F;android-developer-verification.html" rel="nofollow">https:&#x2F;&#x2F;android-developers.googleblog.com&#x2F;2026&#x2F;03&#x2F;android-de...</a>

[Other] Vectorization of Verilog Designs and its Effects on Verification and Synthesis

[Other] macOS 26 breaks custom DNS settings including .internal One of those &#x27;woke up to MacOS updates&#x27; and finding none of my dockers are reachable via dnsmasq (which I use), and low and behold, an update silently breaks custom dns resolution. Hopefully Apple will listen to the bug report I&#x27;ve made. Hold off on updating if you use this…

[API/SDK] Hyper-optimized reverse geocoding API

[Other] No-build, no-NPM, SSR-first JavaScript framework if you hate React, love HTML

[Other] I turned Markdown into a protocol for generative UI There&#x27;s a lot of work happening around both generative UI and code execution for AI agents. I kept wondering: how do you bring them together into a fully featured architecture? I built a prototype:<p>- Markdown as protocol — one stream carrying text, executable code, and data<p>- Streaming execution — code fences execute statement by statement as they stream in<p>- A mount() primitive — the agent creates React UIs with full data flow between client, server, and LLM<p>Let me know what you think!

[CLI Tool] Show HN: Agentic Copilot – Bring Claude Code, OpenCode, Gemini CLI into Obsidian Obsidian plugin that connects to CLI agents you already have installed. No built-in LLM integration, no API keys to configure in the plugin. It spawns your tool as a child process, pipes vault context into each prompt, and streams responses into a chat panel.<p>Supports Claude Code, Opencode, and any custom binary via a generic adapter. Adding a new agent is a single file. Free, proudly Open Source (MIT licensed).<p>Would love feedback on this for anyone that that tries it out.

[Other] Show HN: Ripl – A unified 2D/3D engine for Canvas, SVG, WebGPU, and the Terminal After several years, with a small hiatus in the middle, I&#x27;ve finally got Ripl to the point of being published. Ripl is a library for rendering 2D and 3D shapes to any context (canvas, SVG, WebGPU, and Terminal supported by default) using a single API. The library mimics the DOM as much as possible, replicating the event system, object graphing, CSS-like querying, gradients, and keyframe animations etc.<p>I also built a complete data visualization library using the core package which is available as @ripl&#x2F;charts. And yes, you can even render the charts to a terminal with about a 2-3 line code change :) (see the terminal demo)<p>Docs are available here: <a href="https:&#x2F;&#x2F;www.ripl.rocks" rel="nofollow">https:&#x2F;&#x2F;www.ripl.rocks</a> Demos are available here: <a href="https:&#x2F;&#x2F;www.ripl.rocks&#x2F;demos" rel="nofollow">https:&#x2F;&#x2F;www.ripl.rocks&#x2F;demos</a> Charts are avialable here: <a href="https:&#x2F;&#x2F;www.ripl.rocks&#x2F;docs&#x2F;charts" rel="nofollow">https:&#x2F;&#x2F;www.ripl.rocks&#x2F;docs&#x2F;charts</a><p>I&#x27;ve also built an interactive playground you can use to play around with it in realtime without having to install it from NPM etc. The playground is available here: <a href="https:&#x2F;&#x2F;www.ripl.rocks&#x2F;playground" rel="nofollow">https:&#x2F;&#x2F;www.ripl.rocks&#x2F;playground</a><p>The core library is quite stable and I&#x27;ll likely publish v1 in the coming weeks. The charts, 3D, and Terminal packages are still very experiemental.<p>I&#x27;d interested to hear what you all think of it.

[Testing] Bombadil: Property-based testing for web UIs by Antithesis

[Other] A sufficiently detailed spec is code

[CLI Tool] Cook: A simple CLI for orchestrating Claude Code

[Other] FastAPI-compatible Python framework with Zig HTTP core; 7x faster

[Other] Show HN: Duplicate 3 layers in a 24B LLM, logical deduction .22→.76. No training I replicated David Ng&#x27;s RYS method (<a href="https:&#x2F;&#x2F;dnhkng.github.io&#x2F;posts&#x2F;rys&#x2F;" rel="nofollow">https:&#x2F;&#x2F;dnhkng.github.io&#x2F;posts&#x2F;rys&#x2F;</a>) on consumer AMD GPUs (RX 7900 XT + RX 6950 XT) and found something I didn&#x27;t expect.<p>Transformers appear to have discrete &quot;reasoning circuits&quot; — contiguous blocks of 3-4 layers that act as indivisible cognitive units. Duplicate the right block and the model runs its reasoning pipeline twice. No weights change. No training. The model just thinks longer.<p>The results on standard benchmarks (lm-evaluation-harness, n=50):<p>Devstral-24B, layers 12-14 duplicated once: - BBH Logical Deduction: 0.22 → 0.76 - GSM8K (strict): 0.48 → 0.64 - MBPP (code gen): 0.72 → 0.78 - Nothing degraded<p>Qwen2.5-Coder-32B, layers 7-9 duplicated once: - Reasoning probe: 76% → 94%<p>The weird part: different duplication patterns create different cognitive &quot;modes&quot; from the same weights. Double-pass boosts math. Triple-pass boosts emotional reasoning. Interleaved doubling (13,13,14,14,15,15,16) creates a pure math specialist. Same model, same VRAM, different routing.<p>The circuit boundaries are sharp — shift by one layer and the effect disappears or inverts. Smaller models (24B) have tighter circuits (3 layers) than larger ones (Ng found 7 layers in 72B).<p>Tools to find circuits in any GGUF model and apply arbitrary layer routing are in the repo. The whole thing — sweep, discovery, validation — took one evening.<p>Happy to answer questions.