🛠️ All DevTools

[API/SDK] The Only QR Platform with Built-in API Generate QR codes with API access, dynamic editing, and 8 types free forever. The developer-friendly QR platform with REST API included.

[API/SDK] The universal inbox api for developers Build your own ticketing and inbox experience. Connect emails, forms, or chat messages into one API — and sync them with your favorite tools.

[Other] AI-powered blood test interpretation BloodGPT is an AI-powered platform for diagnostic laboratories and clinics that integrates seamlessly into existing workflows, interpreting blood test results in seconds and extracting data with 99.99% accuracy

[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 "context-as-code" 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.

[DevOps] 💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline

[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

[Other] AI powered Interviews - Reliable, Efficient and Trustworthy InterWiz is a B2B platform for conducting AI-based interviews, allowing companies to hire top talent quickly, effortlessly, and with superior quality. We facilitate screening interviews, in-depth technical interviews, and live coding challenges.

[IDE/Editor] Real-time security guardrails for your AI code assistant Stop insecure AI code before it lands. Snyk Studio plugs into your AI code assistants (and VS Code, Cursor, and others) to scan code suggestions in real time, flag risky patterns, and guide safer fixes by these coding agents. Snyk Studio also injects Snyk’s security expert context so your assistant can plan and apply fixes to existing vulnerabilities without ever leaving the editor and terminal.

[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)

[Other] Debugging containers that have no shell

[Other] Show HN: PingStalker – A a macOS tool for network engineers Hi HN - I’m the developer of PingStalker, a macOS utility I built to see what’s really happening on the LAN&#x2F;WLAN.<p>I live in the CLI, but when it came to discovery and monitoring, I found it limiting. So I built a GUI that brings my favorite tools together in one place.<p>PingStalker started because I wanted to know if something on the network was scanning my machine. I also wanted quick access to core details—external IP, Wi-Fi data, and local topology. Then I wanted more: fast, reliable scans using ARP tables and ICMP.<p>As a Wi-Fi engineer, I couldn’t stop there. I kept adding ways to surface what’s actually going on behind the scenes.<p>A few highlights:<p>- Performs ARP, ICMP, mDNS, and DNS scans to discover every device on your subnet, showing IP, MAC, vendor, and open ports.<p>- Continuously monitors selected hosts (“live ping”) to visualize latency spikes, missed pings, and reconnects.<p>- Detects VLANs on trunk or hybrid ports, exposing when your Mac is sitting on a tagged interface.<p>- Captures just the important live traffic — DHCP events, ARP broadcasts, 802.1X authentication, LLDP&#x2F;CDP neighbor data, ICMP packets, and off-subnet chatter — to give you a real-time pulse of your network.<p>- Decodes mDNS traffic into human-readable form (that one took months of deep dives, but the output is finally clear and useful).<p>- Built my own custom vendor-logo database: I wrote a tool that links MAC OUIs with their companies, fetches each vendor’s favicon, and stores them locally so scan results feel alive and recognizable.<p>Under the hood it’s written in Swift. It uses low-level BSD sockets for ping and ARP, plus Apple’s Network framework for interface enumeration. The rest relies on familiar command-line tools. It’s fast.<p>I’d love feedback from anyone who builds or uses network diagnostic tools:<p>- Does this fill a gap you’ve run into on macOS?<p>- Any ideas for improving scan speed or how traffic events are visualized?<p>- What else would you like to see?<p>Details and screenshots: https:&#x2F;&#x2F;pingstalker.com<p>Happy to answer any technical questions about the implementation, Swift APIs, or macOS permission model.

[Other] The Paranoid Guide to Running Copilot CLI in a Secure Docker Sandbox