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[Other] Immutable Software Deploys Using ZFS Jails on FreeBSD

[Other] Valdi – A cross-platform UI framework

[CLI Tool] Show HN: Command line YouTube downloader,a universal media solution for everyone m2m, a purely command line bash application which allows you to download any video or playlist off of youtube dailymotion and pretty much anything yt-dlp supports

[Other] Ribir: Non-intrusive GUI framework for Rust/WASM

[Other] Craft Chrome Devtools Protocol (CDP) commands with the new command editor

[Other] Show HN: I built a search engine for all domains on the internet Hi HN,<p>I built DomainExplorer.io, a search and analytics tool that lets you explore newly registered and expired domains across all TLDs — updated daily.<p>The idea came from my frustration how hard it is to search for registered&#x2F;expired domains. I wanted a simple and easy-to-use tool with web UI where you could submit queries like:<p>- Find all domains in .com and .net zones that end with &quot;chatgpt&quot;.<p>- Find all expired domains that have &quot;copilot&quot; substring in name (excluding .ai and .io zones) and their name is shorter than 12 symbols<p>- Find all domains with &quot;amazon&quot; in name and that were created earlier than June 20, 2023<p>But there was nothing like that around.<p>So I decided to built this tool myself.<p>DomainExplorer.io currently indexes 300M+ active domains from 1,500+ zone files, refreshed daily. You can filter by TLD (zone), name length, active or expired, substring or patterns (e.g. “starts with best”, “ends with copilot”, &quot;contains chatgpt&quot;), and download the results as CSV or JSON.<p>Tech stack: Go, PostgreSQL, React&#x2F;TypeScript, hosted on baremetal server (cloud is way too expensive for me for such a project), and a custom search index that I designed and built myself because ElasticSearch&#x2F;Lucene were either too slow or excessively packed with features that I did not need. As a result, I&#x27;ve built pretty lean and performant search engine for domains, you literally get results within 1-2 seconds across all 300M domains search.<p>I’d love your feedback — especially around use cases I might be missing (security research, trend tracking, brand monitoring, etc.) and any ideas for making search faster or more useful for developers.<p>Please give it a try!<p><a href="https:&#x2F;&#x2F;domainexplorer.io" rel="nofollow">https:&#x2F;&#x2F;domainexplorer.io</a>

[Other] Show HN: Dynamic code and feedback walkthroughs with your coding Agent in VSCode I&#x27;ve been programming since I&#x27;m 6 and I don&#x27;t want to quit. Since Agents came into existence I&#x27;ve been increasingly building more of the random ideas.<p><i>BUT, like many</i> I kept getting stuck and frustrated where I wanted to make changes with the Agent that I <i>knew</i> I could&#x27;ve made without it but I had *no clue* how things worked.<p>I created Intraview to help me build and maintain a mental model of what I was building (or had vibed) so I could use my knowledge to either fix it myself, or provide more directed instruction. It grew into something that&#x27;s transformed my workflow in a pleasant way.<p>Intraview is a VS Code extension that allows you to create: - Dynamic code tours built by your existing Agent - Storage and sharing of tours (it&#x27;s a file) - Batch Feedback&#x2F;commenting inline in IDE in-tour and without (it&#x27;s also a file)<p>Here&#x27;s a video walkthrough for the show vs tell crowd where I jump in a random (<i>Plotly JS</i>) open source repo and build a tour to get started: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=ROBvFlG6vtY" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=ROBvFlG6vtY</a><p>Talking tech design, this is very different than most because the whole App is cloudless. Not server less, there&#x27;s no external APIs (outside basic usage telemetry).<p><pre><code> - basic TypeScript app, JS&#x2F;CSS&#x2F;HTML - Localhost MCP server inside VS Code (one per workspace open) </code></pre> Three of the biggest challenges I faced was:<p><pre><code> - re-considering the user experience given there&#x27;s no database - trying to build a reasonable experience to manage MCP connection across so many different setups. - testing the many forks, Agents and themes because I wanted to make it look native (I&#x27;ll probably reverse course here in future iterations) </code></pre> What I&#x27;m curious about is, where do you see the value:<p><pre><code> - New project&#x2F;developer onboarding - PR reviews - Keeping up with Agentic code - Perf reviews (for EM), you could build a tour biggest contributions by a GitHub handle - Planning alignment and review with your Agent </code></pre> You can see the extension page in VS Code with these custom links <i>(Note: this redirects and requires permission to open VS Code, won&#x27;t actually install, takes another click)</i><p><pre><code> - for VS Code: https:&#x2F;&#x2F;intraview.ai&#x2F;install?app=vscode - for Cursor: https:&#x2F;&#x2F;intraview.ai&#x2F;install?app=cursor </code></pre> Once it&#x27;s installed and you confirm MCP is connected to your local server, just ask your Agent:<p><pre><code> - Create an Intraview the onboarding for this app.. - Let&#x27;s use Intraview to gather my feedback on [whatever you created]. Break down steps such that I can provide good granular feedback. </code></pre> Looking forward to your feedback and discussion.<p>And because this is HN. A relevant quotable from PG.<p><pre><code> “Your code is your understanding of the problem you’re exploring. So it’s only when you have your code in your head that you really understand the problem.” — Paul Graham</code></pre>

[Other] Show HN: ShellAI – Local Terminal Assistance with SLM

[CLI Tool] Show HN: qqqa – a fast, stateless LLM-powered assistant for your shell I built qqqa as an open-source project, because I was tired of bouncing between shell, ChatGPT &#x2F; the browser for rather simple commands. It comes with two binaries: qq and qa.<p>qq means &quot;quick question&quot; - it is read-only, perfect for the commands I always forget.<p>qa means &quot;quick agent&quot; - it is qq&#x27;s sibling that can run things, but only after showing its plan and getting an approval by the user.<p>It is built entirely around the Unix philosophy of focused tools, stateless by default - pretty much the opposite of what most coding agent are focusing on.<p>Personally I&#x27;ve had the best experience using Groq + gpt-oss-20b, as it feels almost instant (up to 1k tokens&#x2F;s according to Groq) - but any OpenAI-compatible API will do.<p>Curious if the HN crowd finds it useful - and of course, AMA.

[Other] Show HN: Flutter_compositions: Vue-inspired reactive building blocks for Flutter

[Other] Show HN: sudocode – manage specs, tasks, and context-as-code for coding agents sudocode is a lightweight context management system for coding agents that lives in your repo. It helps organize the chaos of human-AI collaboration by capturing user intent as durable specs and tracking agent activity as issues, all version-controlled with Git. This &quot;context-as-code&quot; approach reduces agent amnesia and accelerates development on long-horizon tasks.

[Other] Show HN: Cj–tiny no-deps JIT in C for x86-64 and ARM64 Hey y’all!<p>About 7 years ago, I had this idea to write a JIT with an autogenerated backend for x86 based on the ISA specs. I sketched something out and then just kinda let it sit. I picked it up again a few weeks ago and made a complete-ish backend for both x86 and ARM64. It has no dependencies, the backends are completely autogenerated (by horrible, horrible JS scripts), and I built a small abstraciton layer for things like functions prologues etc.<p>It’s super duper early and will probably break on your machine, but it’s good enough to compile some cool examples (look at the examples directory: <a href="https:&#x2F;&#x2F;github.com&#x2F;hellerve-pl-experiments&#x2F;cj&#x2F;tree&#x2F;master&#x2F;examples" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;hellerve-pl-experiments&#x2F;cj&#x2F;tree&#x2F;master&#x2F;ex...</a>, my personal favorite is the minimal language implementation: <a href="https:&#x2F;&#x2F;github.com&#x2F;hellerve-pl-experiments&#x2F;cj&#x2F;blob&#x2F;master&#x2F;examples&#x2F;minilang.c" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;hellerve-pl-experiments&#x2F;cj&#x2F;blob&#x2F;master&#x2F;ex...</a>).<p>It doesn’t have anything except basically a fancy JIT assembler with some helpers as of yet. No register allocator, a lot of ABI details will still have to be figured out manually (though of course feel free to add anything to the abstraction layer that’s generally useful and submit a PR!).<p>I honestly don’t know where I’m going with this next. I kind of stumbled into the project, and am not sure whether I’ll consider it as “exercise completed” or whether I should pursue it more. Time will tell.<p>Feedback, questions, and bug reports very welcome—especially on the codegen helpers, additional examples or cool things you come up with, or backend rough edges.<p>P.S.: I also wrote a small announcement blog post on it that you can find here (<a href="https:&#x2F;&#x2F;blog.veitheller.de&#x2F;cj:_Making_a_minimal,_complete_JIT.html" rel="nofollow">https:&#x2F;&#x2F;blog.veitheller.de&#x2F;cj:_Making_a_minimal,_complete_JI...</a>), but it honestly doesn’t add all that much interesting info that you can’t find in the repo.

[CLI Tool] Show HN: Wosp – advanced full-text search on the command line Hi, I&#x27;m Andrew Trettel. I&#x27;m a scientist and researcher. I wrote Wosp to help me search local documents using Boolean and proximity operators.<p>Wosp is a command-line program that performs full-text search on text documents. Wosp stands for word-oriented search and print. It is designed for advanced searchers. It works differently than line-oriented search tools like grep, so it can search for matches spanning multiple lines. Wosp supports an expressive query language that contains both Boolean and proximity operators. It also supports nested queries, truncation, wildcard characters, and fuzzy searching.<p>The linked GitHub repository contains all of the code to try out the program. I also wrote a blog post (<a href="https:&#x2F;&#x2F;www.andrewtrettel.com&#x2F;blog&#x2F;wosp&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.andrewtrettel.com&#x2F;blog&#x2F;wosp&#x2F;</a>) that discusses my motivations for creating Wosp in more detail, along with some additional technical discussion and diagrams.<p>If you give Wosp a try, I&#x27;d appreciate any comments or feedback you have about the experience.

[Other] Show HN: A new language for COBOL workloads, built on Go We’re building an open-source language layer on top of Go, designed specifically for COBOL-style workloads: Native decimal arithmetic (COBOL-accurate) Record structures and copybook compatibility Batch jobs and transactional orchestration as first-class constructs Sequential &#x2F; indexed file I&#x2F;O baked into the runtime Compiles through Go for speed, concurrency, and cloud deployability Think of it as Kotlin for COBOL, or “COBOL on Go” familiar to mainframe engineers, powerful for modern developers.<p>Test Results so far: NIST COBOL-85 validation: 77.61% overall (305&#x2F;393 tests) NC (Core COBOL): 97.89% (93&#x2F;95) SM (Statements): 100% (13&#x2F;13) RL (Relative I&#x2F;O): 100% (26&#x2F;26) IF (Intrinsic Functions): 100% (45&#x2F;45) IC (CALL): 96% (24&#x2F;25) Compliance tests: 100% passing Acceptance tests: 100% passing

[Testing] Hypothesis: Property-Based Testing for Python

[Other] Preventing Kubernetes from Pulling the Pause Image from the Internet

[Other] Analyzing the Performance of WebAssembly vs. Native Code

[Other] Launch HN: Plexe (YC X25) – Build production-grade ML models from prompts Hey HN! We&#x27;re Vaibhav and Marcello, founders of Plexe (<a href="https:&#x2F;&#x2F;www.plexe.ai">https:&#x2F;&#x2F;www.plexe.ai</a>). We create production-ready ML models from natural language descriptions. Tell Plexe what ML problem you want to solve, point it at your data, and it handles the entire pipeline from feature engineering to deployment.<p>Here’s a walkthrough: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=TbOfx6UPuX4" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=TbOfx6UPuX4</a>.<p>ML teams waste too much time on generic heavy lifting. Every project follows the same pattern: 20% understanding objectives, 60% wrangling data and engineering features, 20% experimenting with models. Most of this is formulaic but burns months of engineering time. Throwing LLMs at it isn&#x27;t the answer as that just trades engineering time for compute costs and worse accuracy. Plexe automates this repetitive 80%, so your team can work faster on what actually has value.<p>You describe your problem in plain English (&quot;fraud detection model for transactions&quot; or &quot;product embedding model for search&quot;), connect your data (Postgres, Snowflake, S3, direct upload, etc), and then Plexe: - Analyzes data and engineers features automatically - Runs experiments across multiple architectures (logistic regression to neural nets) - Generates comprehensive evaluation reports with error analysis, robustness testing, and prioritized recommendations to provide actionable guidance - Deploys the best model with monitoring and automatic retraining<p>We did a Show HN for our open-source library five months ago (<a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=43906346">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=43906346</a>). Since then, we&#x27;ve launched our commercial platform with interactive refinement, production-grade model evaluations, retraining pipeline, data connectors, analytics dashboards, and deployment for online and batch inference.<p>We use a multi-agent architecture where specialized agents handle different pipeline stages. Each agent focuses on its domain: data analysis, feature engineering, model selection, deployment, and so on. The platform tracks all experiments and generates exportable Python code.<p>Our open-source core (<a href="https:&#x2F;&#x2F;github.com&#x2F;plexe-ai&#x2F;plexe" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;plexe-ai&#x2F;plexe</a>, Apache 2.0) remains free for local development. For the paid product, our pricing is usage-based, with a minimum top up of $10. Enterprises can self-host the entire platform. You can sign up on <a href="https:&#x2F;&#x2F;console.plexe.ai">https:&#x2F;&#x2F;console.plexe.ai</a>. Use promo code `LAUNCHDAY20` to get $20 to try out the platform.<p>We’d love to hear your thoughts on the problem and feedback on the platform!

[Other] How devtools map minified JS code back to your TypeScript source code

[Other] Show HN: Agor → Figma for AI Coding (Open Source)