Temporal: A nine-year journey to fix time in JavaScript

Entities enabling scientific fraud at scale are large, resilient, growing (2025)

Making WebAssembly a first-class language on the Web

Where Some See Strings, She Sees a Space-Time Made of Fractals

BitNet: 100B Param 1-Bit model for local CPUs

We are Bailey and Robbie and we are working on Klaus (<a href="https:&#x2F;&#x2F;klausai.com&#x2F;" rel="nofollow">https:&#x2F;&#x2F;klausai.com&#x2F;</a>): hosted OpenClaw that is secure and powerful out of the box.Running OpenClaw requires setting up a cloud VM or local container (a pain) or giving OpenClaw root access to your machine (insecure). Many basic integrations (eg Slack, Google Workspace) require you to create your own OAuth app.We make running OpenClaw simple by giving each user their own EC2 instance, preconfigured with keys for OpenRouter, AgentMail, and Orthogonal. And we have OAuth apps to make it easy to integrate with Slack and Google Workspace.We are both HN readers (Bailey has been on here for ~10 years) and we know OpenClaw has serious security concerns. We do a lot to make our users’ instances more secure: we run on a private subnet, automatically update the OpenClaw version our users run, and because you’re on our VM by default the only keys you leak if you get hacked belong to us. Connecting your email is still a risk. The best defense I know of is Opus 4.6 for resilience to prompt injection. If you have a better solution, we’d love to hear it!We learned a lot about infrastructure management in the past month. Kimi K2.5 and Mimimax M2.5 are extremely good at hallucinating new ways to break openclaw.json and otherwise wreaking havoc on an EC2 instance. The week after our launch we spent 20+ hours fixing broken machines by hand.We wrote a ton of best practices on using OpenClaw on AWS Linux into our users’ AGENTS.md, got really good at un-bricking EC2 machines over SSM, added a command-and-control server to every instance to facilitate hotfixes and migrations, and set up a Klaus instance to answer FAQs on discord.In addition to all of this, we built ClawBert, our AI SRE for hotfixing OpenClaw instances automatically: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=v65F6VBXqKY" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=v65F6VBXqKY</a>. Clawbert is a Claude Code instance that runs whenever a health check fails or the user triggers it in the UI. It can read that user’s entries in our database and execute commands on the user’s instance. We expose a log of Clawbert’s runs to the user.We know that setting up OpenClaw is easy for most HN readers, but I promise it is not for most people. Klaus has a long way to go, but it’s still very rewarding to see people who’ve never used Claude Code get their first taste of AI agents.We charge $19&#x2F;m for a t4g.small, $49&#x2F;m for a t4g.medium, and $200&#x2F;m for a t4g.xlarge and priority support. You get $15 in tokens and $20 in Orthogonal credits one-time.We want to know what you are building on OpenClaw so we can make sure we support it. We are already working with companies like Orthogonal and Openrouter that are building things to make agents more useful, and we’re sure there are more tools out there we don’t know about. If you’ve built something agents want, please let us know. Comments welcome!

Show HN: Klaus – OpenClaw on a VM, batteries included

Elevated errors on login with Claude Code

Wiz joins Google

Lego's 0.002mm specification and its implications for manufacturing (2025)

Hey HN — we’re Rajit, Land, and Alex. We’re building Prism (<a href="https:&#x2F;&#x2F;www.prismvideos.com">https:&#x2F;&#x2F;www.prismvideos.com</a>), an AI video creation platform and API.Here’s a quick demo of how you can remix any video with Prism: <a href="https:&#x2F;&#x2F;youtu.be&#x2F;0eez_2DnayI" rel="nofollow">https:&#x2F;&#x2F;youtu.be&#x2F;0eez_2DnayI</a>Here’s a quick demo of how you can automate UGC-style ads with Openclaw + Prism: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=5dWaD23qnro" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=5dWaD23qnro</a>Accompanying skill.md file: <a href="https:&#x2F;&#x2F;docs.google.com&#x2F;document&#x2F;d&#x2F;1lIskVljW1OqbkXFyXeLHRsfMictCfuxGGwczAnB1vhk" rel="nofollow">https:&#x2F;&#x2F;docs.google.com&#x2F;document&#x2F;d&#x2F;1lIskVljW1OqbkXFyXeLHRsfM...</a>Making an AI video today usually means stitching together a dozen tools (image generation, image-to-video, upscalers, lip-sync, voiceover, and an editor). Every step turns into export&#x2F;import and file juggling, so assets end up scattered across tabs and local storage, and iterating on a multi-scene video is slow.Prism keeps the workflow in one place: you generate assets (images&#x2F;video clips) and assemble them directly in a timeline editor without downloading files between tools. Practically, that means you can try different models (Kling, Veo, Sora, Hailuo, etc) and settings for a single clip, swap it on the timeline, and keep iterating without re-exporting and rebuilding the edit elsewhere.We also support templates and one-click asset recreation, so you can reuse workflows from us or the community instead of rebuilding each asset from scratch. Those templates are exposed through our API, letting your AI agents discover templates in our catalog, supply the required inputs, and generate videos in a repeatable way without manually stitching the workflow together.We built Prism because we were making AI videos ourselves and were unsatisfied with the available tools. We kept losing time to repetitive “glue work” such as constantly downloading files, keeping track of prompts&#x2F;versions, and stitching clips in a separate video editing software. We’re trying to make the boring parts of multi-step AI video creation less manual so users can generate → review → edit → assemble → export, all inside one platform.Pricing is based on usage credits, with a free tier (100 credits&#x2F;month) and free models, so you can try it without providing a credit card: <a href="https:&#x2F;&#x2F;prismvideos.com">https:&#x2F;&#x2F;prismvideos.com</a>.We’d love to hear from people who’ve tried making AI videos: where does your workflow break, what parts are the most tedious, and what do you wish video creation tools on the market could do?

Launch HN: Prism (YC X25) – Workspace and API to generate and edit videos

Faster asin() was hiding in plain sight

Hey HN! We&#x27;re Neel and Anay, and we’re building Sentrial (<a href="https:&#x2F;&#x2F;sentrial.com">https:&#x2F;&#x2F;sentrial.com</a>). It’s production monitoring for AI products. We automatically detect failure patterns: loops, hallucinations, tool misuse, and user frustrations the moment they happen. When issues surface, Sentrial diagnoses the root cause by analyzing conversation patterns, model outputs, and tool interactions, then recommends specific fixes.Here&#x27;s a demo if you&#x27;re interested: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=cc4DWrJF7hk" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=cc4DWrJF7hk</a>.
When agents fail, choose wrong tools, or blow cost budgets, there&#x27;s no way to know why - usually just logs and guesswork. As agents move from demos to production with real SLAs and real users, this is not sustainable.Neel and I lived this, building agents at SenseHQ and Accenture where we found that debugging agents was often harder than actually building them. Agents are untrustworthy in prod because there’s no good infrastructure to verify what they’re actually doing.In practice this looks like: - A support agent that began misclassifying refund requests as product questions, which meant customers never reached the refund flow. - A document drafting agent that would occasionally hallucinate missing sections when parsing long specs, producing confident but incorrect outputs. There’s no stack trace or 500 error and you only figure this out when a customer is angry.We both realized teams were flying blind in production, and that agent native monitoring was going to be foundational infrastructure for every serious AI product. We started Sentrial as a verification layer designed to take care of this.How it works: You wrap your client with our SDK in only a couple of lines. From there, we detect drift for you: - Wrong tool invocations - Misunderstood intents - Hallucinations - Quality regressions over time. You see it on our platform before a customer files a ticket.There’s a quick mcp set up, just give claude code: claude mcp add --transport http Sentrial <a href="https:&#x2F;&#x2F;www.sentrial.com&#x2F;docs&#x2F;mcp">https:&#x2F;&#x2F;www.sentrial.com&#x2F;docs&#x2F;mcp</a>We have a free tier (14 days, no credit card required). We’d love any feedback from anyone running agents whether they be for personal use or within a professional setting.We’ll be around in the comments!

Launch HN: Sentrial (YC W26) – Catch AI Agent Failures Before Your Users Do

AI Agent Hacks McKinsey

Hi HN, I forked chromium and built agent-browser-protocol (ABP) after noticing that most browser-agent failures aren’t really about the model misunderstanding the page. Instead, the problem is that the model is reasoning from a stale state.ABP is designed to keep the acting agent synchronized with the browser at every step. After each action (click, type, etc), it freezes JavaScript execution and rendering, then captures the resulting state. It also compiles the notable events that occurred during that action loop, such as navigation, file pickers, permission prompts, alerts, and downloads, and sends that along with a screenshot of the frozen page state back to the agent.The result is that browser interaction starts to feel more like a multimodal chat loop. The agent takes an action, gets back a fresh visual state and a structured summary of what happened, then decides what to do next from there. That fits much better with how LLMs already work.A few common browser-use failures ABP helps eliminate:
* A modal appears after the last Playwright screenshot and blocks the input the agent was about to use
* Dynamic filters cause the page to reflow between steps
* An autocomplete dropdown opens and covers the element the agent intended to click
* alert() &#x2F; confirm() interrupts the flow
* Downloads are triggered, but the agent has no reliable way to know when they’ve completedAs proof, ABP with opus 4.6 as the driver scores 90.5% on the Online Mind2Web benchmark. I think modern LLMs already understand websites, they just need a better tool to interact with them. Happy to answer questions about the architecture, forking chrome or anything else in the comments below.Try it out: `claude mcp add browser -- npx -y agent-browser-protocol --mcp` (Codex&#x2F;OpenCode instructions in the docs)Demo video: <a href="https:&#x2F;&#x2F;www.loom.com&#x2F;share&#x2F;387f6349196f417d8b4b16a5452c3369" rel="nofollow">https:&#x2F;&#x2F;www.loom.com&#x2F;share&#x2F;387f6349196f417d8b4b16a5452c3369</a>

Show HN: Open-source browser for AI agents

<a href="https:&#x2F;&#x2F;www.pcmag.com&#x2F;news&#x2F;asus-co-ceo-macbook-neo-is-a-shock-to-the-pc-industry" rel="nofollow">https:&#x2F;&#x2F;www.pcmag.com&#x2F;news&#x2F;asus-co-ceo-macbook-neo-is-a-shoc...</a>

The MacBook Neo

Hi HN,
I’m a chemical engineer and I manage logistics at a refinery down in Texas. Whenever I try to explain downstream operations to people outside the industry (including my kids), I usually get blank stares. I wanted to build something that visualizes the concepts and chemistry of a plant without completely dumbing down the science, so I put together this 5-minute browser game.Here&#x27;s a simple runthrough: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=is-moBz6upU" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=is-moBz6upU</a>. I pushed to get through a full product pathway to show the V-804 replay.I am not a software developer by trade, so I relied heavily on LLMs (Claude, Copilot, Gemini) to help write the code. What started as a simple concept turned into a 9,000-line single-page app built with vanilla HTML, CSS, and JavaScript. I used Matter.js for the 2D physics minigames.A few technical takeaways from building this as a non-dev:
 * Managing the LLM workflow: Once the script.js file got large, letting the models output full file rewrites was a disaster (truncations, hallucinations, invisible curly-quote replacements that broke the JS). I started forcing them to act like patch files, strictly outputting &quot;Find this exact block&quot; and &quot;Replace with this exact block.&quot; This was the only way to maintain improvements without breaking existing logic.* Mapping physics to CSS: I wanted the minigames to visually sit inside circular CSS containers (border-radius: 50%). Matter.js doesn&#x27;t natively care about your CSS. Getting the rigid body physics to respect a dynamic, responsive DOM boundary across different screen sizes required running an elliptical boundary equation (dx * dx) &#x2F; (rx * rx) + (dy * dy) &#x2F; (ry * ry) &gt; 1 on every single frame. Maybe this was overkill to try to handle the resizing between phones and PCs.* Mobile browser events: Forcing iOS Safari to ignore its default behaviors (double-tap zoom, swipe-to-scroll) while still allowing the user to tap and drag Matter.js objects required a ridiculous amount of custom event listener management and CSS (touch-action: manipulation; user-select: none;). I also learned that these actions very easily kill the mouse scroll making it very frustrating for PC users. I am hoping I hit a good middle ground.* State management: Since I didn&#x27;t use React or any frameworks, I had to rely on a global state object. Because the game jumps between different phases&#x2F;minigames, I ran into massive memory leaks from old setInterval loops and Matter.js bodies stacking up. I had to build strict teardown functions to wipe the slate clean on every map transition.The game walks through electrostatic desalting, fractional distillation, hydrotreating, catalytic cracking, and gasoline blending (hitting specific Octane and RVP specs).It’s completely free, runs client-side, and has zero ads or sign-ups. I&#x27;d appreciate any feedback on the mechanics, or let me know if you manage to break the physics engine. Happy to answer any questions about the chemical engineering side of things as well.For some reason the URL box is not getting recognized, maybe someone can help me feel less dumb there too. 
<a href="https:&#x2F;&#x2F;fuelingcuriosity.com&#x2F;game" rel="nofollow">https:&#x2F;&#x2F;fuelingcuriosity.com&#x2F;game</a>

Show HN: Vanilla JavaScript refinery simulator built to explain job to my kids

Demo: <a href="https:&#x2F;&#x2F;aether.saphal.me" rel="nofollow">https:&#x2F;&#x2F;aether.saphal.me</a>
GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;saphalpdyl&#x2F;Aether" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;saphalpdyl&#x2F;Aether</a>Aether is a multi-BNG (Broadband Network Gateway) ISP infrastructure lab built almost from scratch that emulates IPoE IPv4 subscriber management end-to-end. It supports IPoE&#x2F;Ipv4 networks and runs a python-based vBNG with RADIUS AAA, per-subscriber traffic shaping, and traffic simulation emulated on Containerlab. It is also my first personal networking project, built roughly over a month.Motivations behind the projectI&#x27;m a CS sophomore. About three years ago, I was assigned, as an intern, to build a OSS&#x2F;BSS platform for a regional ISP by myself without mentoring. Referencing demo.splynx.com , I developed most of the BSS side ( bookkeeping, accounting, inventory management ), but, in terms of networking, I managed to install and setup RADIUS and that was about it. I didn&#x27;t have anyone to mentor me or ask questions to, so I had given up then.Three years later, I decided to try cracking it again. This project is meant to serve as a learning reference for anyone who&#x27;s been in that same position i.e staring at closed-source vendor stacks without proper guidance. This is absolutely not production-grade, but I hope it gives someone a place to start.Architecture overviewThe core component, the BNG, runs on an event-driven architecture where state changes are passed around as messages to avoid handling mutexes and locks. The session manager is the sole owner of the session state. To keep it clean and predictable, the direBNG never accepts external inputctly. The one exception is the Go RADIUS CoA daemon, which passes CoA messages in via IPC sockets. Everything the BNG produces(events, session snapshots) gets pushed to Redis Streams, where the bng-ingestor picks them up, processes them, and persists them.Simulation and meta-configsI am generating traffic through a simulator node that mounts the host&#x27;s docker socket and runs docker exec commands on selected hosts. The topology.yaml used by Containerlab to define the network topology grows bigger as more BNG&#x27;s and access nodes are added. So aether.config.yaml, a simpler configuration, is consumed by the configuration pipeline to generate the topology.yaml and other files (nginx.conf, kea-dhcp.conf, RADIUS clients.conf etc.)Known Limitations- Multiple veth hops through the emulated topology add significant overhead. Profiling with iperf3 (-P 10 -t 10, 9500 MTU, 24 vCPUs) shows BNG→upstream at ~24 Gbit&#x2F;s, but host→BNG→upstream drops to ~3.5 Gbit&#x2F;s. The 9500 MTU also isn&#x27;t representative of real ISP deployments. This gets worse when the actual network is reintroduced capping my throughput to 1.6 Gbits&#x2F;sec in local.
- The circuit ID format (1&#x2F;0&#x2F;X) is non-standard. I simplified it for clarity.
- No iBGP or VLAN support.
- No Ipv6 support. I wanted to target IPv4 networks from the start to avoid getting too much breadth without a lot of depth.Nearly everything I know about networking (except some sections from AWS) I learned building this. A lot was figured out on the fly, so engineers will likely spot questionable decisions in the codebase. I&#x27;d genuinely appreciate that feedback.Questions- Currently, the circuit where the user connects is arbitrarily decided by the demo user. In a real system with thousands of circuits, it&#x27;d be very difficult to properly assess which circuit the customer might connect to. When adding a new customer to a service, how does the operator decide, based on customer&#x27;s location, which circuit to provide the service to ?