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GitHub Authentication issues related to API requests

The iPad was on Tailscale: a WebRTC debugging story

Show HN: Social network where inviting someone makes you accountable for them Chirpper is invite-only. When you vouch someone in, they join your TrustChain. Their behavior affects your TrustRank, and that propagates up the lineage. No moderators. The accountability is architectural, not policy-based. You can be pseudonymous, but you can't be unaccountable. Happy to get into the mechanics in comments.

Apache Burr: Build reliable AI agents and applications

Spoiling Linux Kernel with "sanctioned" code

Show HN: Turn your name into a tree in an infinite procedural shanshui landscape Hi HN! I made this after collecting hundreds of &quot;name → tree&quot; submissions at ITP.<p>Live: <a href="https:&#x2F;&#x2F;landscape.bairui.dev&#x2F;" rel="nofollow">https:&#x2F;&#x2F;landscape.bairui.dev&#x2F;</a> Source: <a href="https:&#x2F;&#x2F;github.com&#x2F;pearmini&#x2F;infinite-landscape" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;pearmini&#x2F;infinite-landscape</a> Plant a tree: <a href="https:&#x2F;&#x2F;tree.bairui.dev&#x2F;" rel="nofollow">https:&#x2F;&#x2F;tree.bairui.dev&#x2F;</a><p>Pan and zoom an infinite procedural landscape. Each name is converted to ASCII codes, which grow into a unique tree (breadth-first branching; repeated digits become mathematical roses). Mountains use midpoint displacement + Perlin noise, with SVG radial gradients in the blue&#x2F;green&#x2F;gold palette from Wang Ximeng&#x27;s &quot;A Thousand Li of Rivers and Mountains.&quot;<p>Inspired by Lingdong Huang&#x27;s {Shan, Shui}* (<a href="https:&#x2F;&#x2F;github.com&#x2F;LingDong-&#x2F;shan-shui-inf" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;LingDong-&#x2F;shan-shui-inf</a>). Every tree is someone&#x27;s name, signed with an APack stamp (<a href="https:&#x2F;&#x2F;apack.bairui.dev&#x2F;" rel="nofollow">https:&#x2F;&#x2F;apack.bairui.dev&#x2F;</a>).<p>Try planting your name, then pan along the ridgeline to find it. &quot;My trees&quot; lets you jump back to ones you planted.<p>Happy to answer questions about the terrain algo, name→tree encoding, or the Riso print we tiled at ITP Winter Show!

TorchCodec 0.14: HDR Video Decoding for CPU and CUDA, and Fast Wav Decoder

PgDog is funded and coming to a database near you

Show HN: Lightweight Task queue on Erlang/OTP, SQLite-backed, no overengineering Setting up Kafka or such enterprise oriented software with their clusters or dedicated servers is heavy and bothering enough that most small teams or indie hackers skip it entirely and making compromise to use in-memory queues.<p>I wanted something in between: a persistent queue that is simple to run (one binary, which makes one sqlite db), gets real fault isolation and crash recovery due to Elixir, easy to inspect (open ezra.db in any SQLite browser and see every task), and requires no new client library - it speaks the Redis Streams wire protocol, so any Redis client in any language just works out of the box.<p>Very short demo video: [<a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=MLYyD3DVWmE" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=MLYyD3DVWmE</a>]

Building an HTML-first site doubled our users overnight

A tool for creating and running Linux containers using lightweight virtual machines on a Mac. It is written in Swift, and optimized for Apple silicon.

利用AI大模型，一键生成高清短视频 Generate short videos with one click using AI LLM.

Advanced DNS tunneling VPN for censorship bypass, optimized beyond DNSTT and SlipStream with low-overhead ARQ, resolver load balancing, high packet-loss stability and speed.

Show HN: macOS menu bar gauges for your Claude Code quota

Port React Compiler to Rust

Show HN: Artie – Real-time data replication to your warehouse, now self-serve Hey HN, cofounder of Artie here. We’ve built a real-time data replication tool that captures every row-level change in your source database and streams it to your warehouse in under 60 seconds.<p>The last time I posted here, people had to book a call with us in order to access Artie. Today, that’s no longer the case. You can now connect your source and destination and start streaming immediately.<p>I spent years of my career building large-scale data pipelines and experienced how difficult it was to get real-time data firsthand. I believed there must be a better way to stream data into our warehouse, which resulted in Artie being born. And now with AI agents, reducing data latency has become more and more crucial as agents need to make decisions off of fresh data.<p>When I first started building Artie, I quickly learned that the components meant to keep CDC running smoothly are very much bolted on with tons of edge cases. Unfortunately in practice, they were not built to work together. We ended up dealing with schema drift, backfill race conditions, Kafka offset commits, and TOAST columns. I’d love to know if others have hit these same issues while building in-house.<p>artie.com, would love feedback!

Vibe coding my way to a healthy family: Introducing Gamow Labs

Why a Computer Science Degree Still Opens Hidden Doors

macOS Container Machines

Show HN: The agent that builds and operates its own SaaS tools For context, we started working on our general AI agent CraftBot before OpenClaw came out. It works similarly to OpenClaw and Hermes agent: control your PC to do task + memory + proactivity. However, here is the catch: it can create and operate its own SaaS tools with the concept of Living UI<p>Living UI is a system where an AI agent can scaffold and launch real, working web apps on demand. Each living UI can be a dashboard&#x2F;software&#x2F;internal tool. They are essentially just frontend with X techstack talking to a backend + database with the techstack of your choice, spun up in its own pair of ports as supervised subprocesses managed by a host process. The backend owns all the state (so the app survives page reloads, tab switches, even host restarts), while the frontend is just a dumb view that fetches data and posts user actions. CraftBot can create a project from a template, install dependencies and launch it. It can also read and write its data through a scoped HTTP client, plus built-in endpoints that return a DOM snapshot and a screenshot so the agent can see what&#x27;s on screen.<p>Currently, there are 3 ways to create a living UI<p>(1) Build from scratch. Just describe what you want, and CraftBot generates the backend, API, and UI, then iterates with you.<p>(2) Install from the marketplace. Use ready-to-use apps built by the community (we are looking for contributors!).<p>(3) Import your existing project or GitHub repo. CraftBot converts it into a Living UI and integrates itself into it (similar to CLI-anything, except the app runs directly in the agent UI).<p>Besides, if CraftBot encounters a problem it can’t solve with a simple script, it invents the Saas tool required to solve it proactively (with user approval, of course). It’s not just building a UI for you, but it’s building a workspace for itself to be more efficient.<p>The net effect: You no longer have to subscribe to Saas tools that are not built 100% for your needs, plus, the Saas tools come with their own general AI agent.