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Monday, 30 March 2026
Show HN: Will AI take my job https://bit.ly/4s5J0IH
Show HN: Will AI take my job https://bit.ly/4dj3LNt March 31, 2026 at 04:43AM
Show HN: I turned a sketch into a 3D-print pegboard for my kid with an AI agent https://bit.ly/4tnBPge
Show HN: I turned a sketch into a 3D-print pegboard for my kid with an AI agent We have pegboards and plywood all over our apartment, and I had an idea to make a tiny pegboard for my kid, Oli. So I naturally cut the wood, drilled in the holes, sat down at the computer to open Fusion 360 and spend an hour or two drawing the pieces by hand. Then I looked at the rough sketch Oli and I had made together, took a photo of it, pasted it into Codex, and gave it just two dimensions: the holes are 40mm apart and the pegs are 8mm wide. To my surprise, 5 minutes later my 3D printer was heating up and printing the first set. I ran it a few times to tune the dimensions for ideal fit, but I am posting the final result as a repository in case anyone else wants to print one, tweak it, or have fun with it too. I am already printing another one to hang on our front door instead of a wreath, so people visiting us have something fun and intriguing to play with while they knock. This is also going onto my list of weird uses of AI from the last few months. https://bit.ly/4taIsSS March 31, 2026 at 12:20AM
Show HN: Codemaxxing – Maximize your slop abilities https://bit.ly/4c1dIN7
Show HN: Codemaxxing – Maximize your slop abilities I built a CLI tool to generate as much slop as possible https://bit.ly/4bQQtFu March 30, 2026 at 11:37PM
Show HN: The Alphabetical Clock https://bit.ly/4dbTkv0
Show HN: The Alphabetical Clock https://bit.ly/4dQyf9y March 30, 2026 at 08:19AM
Sunday, 29 March 2026
Show HN : DrawX - Excalidraw with Back End https://bit.ly/4v0Co0V
Show HN : DrawX - Excalidraw with Back End https://bit.ly/4s0PWXq March 30, 2026 at 06:17AM
Show HN: React-Rewrite – Figma for localhost that directly edits your codebase https://bit.ly/4uYirYF
Show HN: React-Rewrite – Figma for localhost that directly edits your codebase https://bit.ly/3Q8An2A March 30, 2026 at 03:59AM
Show HN: Real-time visualization of Claude Code agent orchestration https://bit.ly/4dOFIpE
Show HN: Real-time visualization of Claude Code agent orchestration https://bit.ly/3NVpRep March 30, 2026 at 03:21AM
Saturday, 28 March 2026
Show HN: a Rust CLI to automatically swap monitor focus based on your gaze https://bit.ly/4dMxuyj
Show HN: a Rust CLI to automatically swap monitor focus based on your gaze https://bit.ly/4bAPH0s March 28, 2026 at 08:38PM
Show HN: EnterpriseFizzBuzz – 622K lines of production-grade FizzBuzz https://bit.ly/4uWxfqD
Show HN: EnterpriseFizzBuzz – 622K lines of production-grade FizzBuzz https://bit.ly/4dm1ukF March 28, 2026 at 11:11PM
Show HN: Windows 95–style Weather App for iPhone https://bit.ly/411mEwU
Show HN: Windows 95–style Weather App for iPhone I built a Windows 95–style weather app for iPhone. https://apple.co/3PPiTrX March 28, 2026 at 11:06PM
Show HN: NUPA is Pax Economica, 6,480x more stable than current US economy https://bit.ly/4bReHiG
Show HN: NUPA is Pax Economica, 6,480x more stable than current US economy NUPA: private post-scarcity OS using BLM land leases + contract law. 100M Monte Carlo runs show 99.999999% survival, 6,480x more resilient than US GDP under systemic noise. Fixed Cost Arbitrage beats AI job loss—humans cheaper than robots. No taxes, no strikes. Python scripts on repo in /simulations folder. Repo: https://bit.ly/4m6ofLB... Short explainer video: https://youtu.be/RE560yVFb0I?si=UlVPkmCkrsg24Dzj March 28, 2026 at 07:44AM
Friday, 27 March 2026
Show HN: VizTools – 16 free tools for PMs and freelancers, deliberately no AI https://bit.ly/4cfQvaj
Show HN: VizTools – 16 free tools for PMs and freelancers, deliberately no AI I've been building AI products for a while. For this one I made a deliberate choice: none of the 16 tools use AI. Meeting cost calculators, freelance rate calculators, PRD generators, runway calculators, sprint retro boards — these problems don't need a language model. They need a well-designed form and correct arithmetic. Built on Nuxt 4 + Vue 3, fully static, runs in your browser. No account required to use anything. Optional Firebase auth only kicks in if you want to save output. Irony worth naming: Claude Code was my pair programmer throughout. The choice wasn't anti-AI — it was about using the right tool for the right problem. Happy to talk stack, the non-AI tradeoffs, or anything else. https://bit.ly/4bPwLd9 March 28, 2026 at 06:36AM
Show HN: Open Source 'Conductor + Ghostty' https://bit.ly/48biqXm
Show HN: Open Source 'Conductor + Ghostty' Our team works with Claude Code, Codex, Gemini all day. We love Ghostty, but wanted something where we could work in multiple worktree at once and have multiple agents run. We decided to open source the internal team we use. Hope you might find it useful. Freel free to contribute or fork. * Cross-platform (Mac, Linux, Windows) all tested * MIT License Features: * Notifications, but also manual 'mark-as-unread) for worktrees (like Gmail stars) * Status indicators work for all terminals inside a wroktree * GH integrations (show PR status) and link GH issues * Can add comments to worktrees (stay organized) * File viewer, Search, diff viewer (can make edits + save) Note: Yeah there are "similar" programs out there, but this one is ours. But I'm happy if our software works for you too! https://bit.ly/4t8okkc March 27, 2026 at 11:26PM
Show HN: Twitch Roulette – Find live streamers who need views the most https://bit.ly/4uVAbE1
Show HN: Twitch Roulette – Find live streamers who need views the most Hey HN, I re-launched twitchroulette.net with a lot of new features and stats and I would love for people to check it out. The idea is you can easily browse the less browsed parts of twitch and find cool and new streamers to say hi to, and maybe make some new friends. I also added some real time stats and breakdowns per channel and I think some of the things they show are pretty interesting. Check it out! https://bit.ly/3fvn7hM March 27, 2026 at 11:22PM
Thursday, 26 March 2026
Show HN: Sup AI, a confidence-weighted ensemble (52.15% on Humanity's Last Exam) https://bit.ly/4sAK3Bo
Show HN: Sup AI, a confidence-weighted ensemble (52.15% on Humanity's Last Exam) Hi HN. I'm Ken, a 20-year-old Stanford CS student. I built Sup AI. I started working on this because no single AI model is right all the time, but their errors don’t strongly correlate. In other words, models often make unique mistakes relative to other models. So I run multiple models in parallel and synthesize the outputs by weighting segments based on confidence. Low entropy in the output token probability distributions correlates with accuracy. High entropy is often where hallucinations begin. My dad Scott (AI Research Scientist at TRI) is my research partner on this. He sends me papers at all hours, we argue about whether they actually apply and what modifications make sense, and then I build and test things. The entropy-weighting approach came out of one of those conversations. In our eval on Humanity's Last Exam, Sup scored 52.15%. The best individual model in the same evaluation run got 44.74%. The relative gap is statistically significant (p < 0.001). Methodology, eval code, data, and raw results: - https://sup.ai/research/hle-white-paper-jan-9-2026 - https://github.com/supaihq/hle Limitations: - We evaluated 1,369 of the 2,500 HLE questions (details in the above links) - Not all APIs expose token logprobs; we use several methods to estimate confidence when they don't We tried offering free access and it got abused so badly it nearly killed us. Right now the sustainable option is a $5 starter credit with card verification (no auto-charge). If you don't want to sign up, drop a prompt in the comments and I'll run it myself and post the result. Try it at https://sup.ai . My dad Scott (@scottmu) is in the thread too. Would love blunt feedback, especially where this really works for you and where it falls short. Here's a short demo video: https://www.youtube.com/watch?v=DRcns0rRhsg https://sup.ai March 26, 2026 at 04:45PM
Show HN: Veil – Dark mode PDFs without destroying images, runs in the browser https://bit.ly/4c6B3OC
Show HN: Veil – Dark mode PDFs without destroying images, runs in the browser Hi HN! here's a tool I just deployed that renders PDFs in dark mode without destroying the images. Internal and external links stay intact, and I decided to implement export since I'm not a fan of platform lock-in: you can view your dark PDF in your preferred reader, on any device. It's a side project born from a personal need first and foremost. When I was reading in the factory the books that eventually helped me get out of it, I had the problem that many study materials and books contained images and charts that forced me, with the dark readers available at the time, to always keep the original file in multitasking since the images became, to put it mildly, strange. I hope it can help some of you who have this same need. I think it could be very useful for researchers, but only future adoption will tell. With that premise, I'd like to share the choices that made all of this possible. To do so, I'll walk through the three layers that veil creates from the original PDF: - Layer 1: CSS filter. I use invert(0.86) hue rotate(180deg) on the main canvas. I use 0.86 instead of 1.0 because I found that full inversion produces a pure black and pure white that are too aggressive for prolonged reading. 0.86 yields a soft dark grey (around #242424, though it depends on the document's white) and a muted white (around #DBDBDB) for the text, which I found to be the most comfortable value for hours of reading. - Layer 2: image protection. A second canvas is positioned on top of the first, this time with no filters. Through PDF.js's public API getOperatorList(), I walk the PDF's operator list and reconstruct the CTM stack, that is the save, restore and transform operations the PDF uses to position every object on the page. When I encounter a paintImageXObject (opcode 85 in PDF.js v5), the current transformation matrix gives me the exact bounds of the image. At that point I copy those pixels from a clean render onto the overlay. I didn't fork PDF.js because It would have become a maintenance nightmare given the length of the codebase and the frequent updates. Images also receive OCR treatment: text contained in charts and images becomes selectable, just like any other text on the page. At this point we have the text inverted and the images intact. But what if the page is already dark? Maybe the chapter title pages are black with white text? The next layer takes care of that. - Layer 3: already-dark page detection. After rendering, the background brightness is measured by sampling the edges and corners of the page (where you're most likely to find pure background, without text or images in the way). The BT.601 formula is used to calculate perceived brightness by weighting the three color channels as the human eye sees them: green at 58.7%, red at 29.9%, blue at 11.4%. These weights reflect biology: the eye evolved in natural environments where distinguishing shades of green (vegetation, predators in the grass) was a matter of survival, while blue (sky, water) was less critical. If the average luminance falls below 40%, the page is flagged as already dark and the inversion is skipped, returning the original page. Presentation slides with dark backgrounds stay exactly as they are, instead of being inverted into something blinding. Scanned documents are detected automatically and receive OCR via Tesseract.js, making text selectable and copyable even on PDFs that are essentially images. Everything runs locally, no framework was used, just vanilla JS, which is why it's an installable PWA that works offline too. Here's the link to the app along with the repository: https://bit.ly/40Z98Kh | https://bit.ly/4uVGXth I hope veil can make your reading more pleasant. I'm open to any feedback. Thanks everyone https://bit.ly/40Z98Kh March 26, 2026 at 12:47PM
Wednesday, 25 March 2026
Show HN: Optio – Orchestrate AI coding agents in K8s to go from ticket to PR https://bit.ly/4bxWNTl
Show HN: Optio – Orchestrate AI coding agents in K8s to go from ticket to PR I think like many of you, I've been jumping between many claude code/codex sessions at a time, managing multiple lines of work and worktrees in multiple repos. I wanted a way to easily manage multiple lines of work and reduce the amount of input I need to give, allowing the agents to remove me as a bottleneck from as much of the process as I can. So I built an orchestration tool for AI coding agents: Optio is an open-source orchestration system that turns tickets into merged pull requests using AI coding agents. You point it at your repos, and it handles the full lifecycle: - Intake — pull tasks from GitHub Issues, Linear, or create them manually - Execution — spin up isolated K8s pods per repo, run Claude Code or Codex in git worktrees - PR monitoring — watch CI checks, review status, and merge readiness every 30s - Self-healing — auto-resume the agent on CI failures, merge conflicts, or reviewer change requests - Completion — squash-merge the PR and close the linked issue The key idea is the feedback loop. Optio doesn't just run an agent and walk away — when CI breaks, it feeds the failure back to the agent. When a reviewer requests changes, the comments become the agent's next prompt. It keeps going until the PR merges or you tell it to stop. Built with Fastify, Next.js, BullMQ, and Drizzle on Postgres. Ships with a Helm chart for production deployment. https://bit.ly/3PyeSYX March 25, 2026 at 06:10PM
Tuesday, 24 March 2026
Show HN: Plasmite – a lightweight IPC system that's fun https://bit.ly/4lMD6um
Show HN: Plasmite – a lightweight IPC system that's fun At Oblong Industries one of the basic building blocks of everything we built was a homegrown C-based IPC system called Plasma. The message channel was an mmap'd file used as a ring buffer. All messages were human-readable, performance was good, configuration was trivial. What was especially useful (and unusual in IPC systems it seems) was the property that message channels outlive all readers and writers, and even survive reboots, because they're just files. For local IPC you don't need a broker or server process. All the engineers who ever worked at Oblong loved Plasma, so I've recreated and updated it, as Plasmite. It's written in Rust and the message format is JSON, but it's fast because it's based on lite3 ( https://bit.ly/47gEPlW ), a really cool project you should also check out. Bindings for Python, Go, Node, and C, but you can also get a lot done with just the CLI tools. The basic commands are - "feed" (to write) - "follow" (to tail) - "fetch" (to read one) - "duplex" (to have a 2-way session) I think duplex could be great for agent-agent communication, but I haven't tried this much yet. If you do, let me know! https://bit.ly/4syvmPq March 25, 2026 at 01:10AM
Show HN: Lexplain – AI-powered Linux kernel change explanations https://bit.ly/4s3xspy
Show HN: Lexplain – AI-powered Linux kernel change explanations To understand what changed between kernel versions, you have to dig through the git repository yourself. Commit messages rarely tell you the real-world impact on your systems — you need to analyze the actual diffs with knowledge of kernel internals. For engineers who use Linux — directly or indirectly — but aren't kernel developers, that barrier is pretty high. I kept finding out about relevant changes only after an issue had already hit, and it was most frustrating when the version was too new to find similar cases online. I built lexplain with the idea that it would be nice to quickly scan through kernel changes the way you'd skim the morning news. It reads diffs, analyzes the code, and generates two types of documents: - Commit analyses: context, code breakdown, behavioral impact, risks, references - Release notes: per-version highlights, functional classification, subsystem breakdown, impact analysis Documents build on each other — individual commits first, then merge commits using child analyses, then release notes using all analyses for that version. Claims based on inference are explicitly labeled. Work in progress. Feedback welcome. https://bit.ly/4t6Sqoe March 24, 2026 at 11:24PM
Monday, 23 March 2026
Show HN: OpenCastor Agent Harness Evaluator Leaderboard https://bit.ly/4bGGUc3
Show HN: OpenCastor Agent Harness Evaluator Leaderboard I've been building OpenCastor, a runtime layer that sits between a robot's hardware and its AI agent. One thing that surprised me: the order you arrange the skill pipeline (context builder → model router → error handler, etc.) and parameters like thinking_budget and context_budget affect task success rates as much as model choice does. So I built a distributed evaluator. Robots contribute idle compute to benchmark harness configurations against OHB-1, a small benchmark of 30 real-world robot tasks (grip, navigate, respond, etc.) using local LLM calls via Ollama. The search space is 263,424 configs (8 dimensions: model routing, context budget, retry logic, drift detection, etc.). The demo leaderboard shows results so far, broken down by hardware tier (Pi5+Hailo, Jetson, server, budget boards). The current champion config is free to download as a YAML and apply to any robot. P66 safety parameters are stripped on apply — no harness config can touch motor limits or ESTOP logic. Looking for feedback on: (1) whether the benchmark tasks are representative, (2) whether the hardware tier breakdown is useful, and (3) anyone who's run fleet-wide distributed evals of agent configs for robotics or otherwise. https://bit.ly/4c1pica March 23, 2026 at 11:13PM
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