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July 31, 2026 at 04:38 PM

[Testing] Show HN: FizzBee – Formal Model based autonomous testing GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;fizzbee-io&#x2F;fizzbee-mbt-examples" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;fizzbee-io&#x2F;fizzbee-mbt-examples</a> Quick Start: <a href="https:&#x2F;&#x2F;fizzbee.io&#x2F;testing&#x2F;tutorials&#x2F;quick-start&#x2F;" rel="nofollow">https:&#x2F;&#x2F;fizzbee.io&#x2F;testing&#x2F;tutorials&#x2F;quick-start&#x2F;</a><p>Most developers agree testing is important. At the same time, most developers don’t enjoy writing tests. With AI generating code faster than ever, testing is becoming even more crucial. But even AI-generated tests need review and maintenance, which makes them another burden.<p>I&#x27;m introducing another form of autonomous testing - &quot;model-based testing&quot;. Instead of writing test cases, you describe expected behavior in a Python-like specification language.<p>The FizzBee model can be: - Verified exhaustively for design bugs (like formal methods). - Mapped to your actual system, automatically generating the tests.<p>This gives you:<p>- No hand-crafted test cases - Automatic testing of concurrent as well as sequential behavior - No cascading test rewrites when behavior changes - No cluttering the SUT with tracing code<p>With FizzBee, you get both design validation (like in formal methods) and automatic test generation, saving time and effort.<p>Currently, only Go is supported. Java and Rust are next and would love to hear which language you’d want supported next.<p>I’d love your feedback!

Found: October 07, 2025 ID: 1754

[API/SDK] Show HN: Mix – Open-source multimodal agents SDK Why we built it: • Claude Code: great for coding, but no video&#x2F;audio support, localhost only • OpenAI SDK: single-model, no native multimedia tools • Both: no integrated DevTools for debugging agent reasoning<p>So, we built Mix as an alternative for multimodal applications. • Native video&#x2F;audio&#x2F;PDF analysis tools (via Gemini for vision, Claude for reasoning) • Multi-model routing instead of single-provider lock-in • One-command Supabase setup for cloud deployment (vs localhost-only) • HTTP architecture that enables visual DevTools alongside agent workflows • Go backend: 50-80% lower memory footprint than Node.js—efficient for concurrent agent sessions. Python and typescript clients are available<p>Example use cases in the demo video: portfolio analyzer that reads Excel and generates charts, YouTube search agent that finds and edits video clips.<p>GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;recreate-run&#x2F;mix" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;recreate-run&#x2F;mix</a> Demo video: <a href="https:&#x2F;&#x2F;youtu.be&#x2F;IwgKt68wQSc" rel="nofollow">https:&#x2F;&#x2F;youtu.be&#x2F;IwgKt68wQSc</a><p>Would appreciate feedback, especially from folks building multimodal agents.

Found: October 07, 2025 ID: 1760

[Other] Stress test for parallel disk i/o using git and pnpm

Found: October 07, 2025 ID: 1753

[Other] A lightweight, powerful framework for multi-agent workflows

Found: October 07, 2025 ID: 1749

trycua/cua

GitHub Trending

[DevOps] Open-source infrastructure for Computer-Use Agents. Sandboxes, SDKs, and benchmarks to train and evaluate AI agents that can control full desktops (macOS, Linux, Windows).

Found: October 07, 2025 ID: 1748

[Other] Show HN: 1-Bit Pixel Art Font Editor I like making small fonts for Arduino and ESP32 projects with those little SSD1306 OLED screens. So I made this browser-based tool to help design pixel art fonts for use in those embedded projects.<p>It has a preview area that updates when you save your character. It can support fixed-width and variable-width fonts. And when you&#x27;re done you can export the font in a few different formats.<p>It comes with a bunch of example fonts built-in. Also it&#x27;s fully client-side code so you can save the webpage to use it offline.<p>If you want some inspiration for fonts, I made a bunch of really small fonts a few years ago: <a href="https:&#x2F;&#x2F;www.moonbench.xyz&#x2F;projects&#x2F;tiny-pixel-art-fonts&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.moonbench.xyz&#x2F;projects&#x2F;tiny-pixel-art-fonts&#x2F;</a>

Found: October 07, 2025 ID: 1761

[CLI Tool] Show HN: NewsGoat – A terminal-based RSS reader written in Go

Found: October 07, 2025 ID: 1755

Orchestra

Product Hunt

[Other] A chat-centric workspace for builders and modern teams Orchestra makes workflow simple for teams who build products and rely on communication. With messaging at its core, and a task tracker and AI agents natively built in, work contexts are aligned and teams are connected.

Found: October 07, 2025 ID: 1745

[Other] Ai app builder to build & finish web apps with human support From idea to shipped front-end: clean React + Tailwind code you own. Edit visually, prompt changes, one-click publish on managed cloud,export anytime. No lock-in. More features next release - create full stack applications & full code export (incl backend)

Found: October 07, 2025 ID: 1746

PromptCompose

Product Hunt

[Other] The command center for your AI prompts. Manage, version, and A/B test your AI prompts — just like code. PromptCompose helps teams build reusable templates, inject variables, and deploy optimized prompt versions instantly.

Found: October 07, 2025 ID: 1747

[API/SDK] New addition to the API catalog ApyHub’s Temporary, Disposable Emails API lets developers create secure, custom-lifespan inboxes with spam filtering. Perfect for testing, sign-ups, and privacy-first workflows.

Found: October 07, 2025 ID: 1751

[Other] Pdoc – Generate API documentation for Python projects

Found: October 07, 2025 ID: 1744

[Other] Show HN: Stochastic Gradient in Hilbert Spaces I wrote a free, proof-complete monograph on stochastic gradient methods in infinite-dimensional Hilbert spaces. It starts from the functional-analysis foundations (Riesz, Radon–Nikodym), gives five equivalent definitions of stochastic gradients, proves existence&#x2F;uniqueness of the dynamics, connects the continuum limit to gradient-flow PDEs, and derives explicit convergence rates under multiple assumption sets (convex, strongly convex, PL&#x2F;KL, heavy-tailed noise, proximal). It also covers special cases (Gaussian&#x2F;RKHS), extends to Hilbert manifolds&#x2F;Banach spaces, analyzes discretizations (stability&#x2F;consistency), and includes four applications (QM ground states, elasticity, optimal control, inverse problems) with pseudocode and explicit constants. Open problems at the end invite feedback. PDF is free to redistribute if cited.<p>Happy to answer questions on assumptions that are actually needed in infinite-D, how the spectral picture influences rates, and what breaks outside Hilbert structure. If you want a quick start, skim the convergence summary and the applications sections.

Found: October 06, 2025 ID: 1766

[Other] Show HN: ElevenLabs UI shadcn/UI components for audio Hey hn, I put together a collection of audio and agent components for Next.js built on top of ShadCN.<p>Hope you find this useful &amp; let me know if there’s ant feedback a (GitHub repo will be open sourced tomorrow am)

Found: October 06, 2025 ID: 1742

[Testing] Automated code reviews via mutation testing

Found: October 06, 2025 ID: 1828

[Other] CodeMender: an AI agent for code security

Found: October 06, 2025 ID: 1741

Apps SDK

Hacker News (score: 121)

[Other] Apps SDK

Found: October 06, 2025 ID: 1736

[Other] Show HN: Tangled – Git collaboration built on AT Protocol

Found: October 06, 2025 ID: 1743

[Other] Show HN: A Digital Twin of my coffee roaster that runs in the browser I built this website to host a data-driven model of my coffee sample roaster.<p>I realized after 20 or so batches on the machine that while the controls are intuitive (heat, fan, and drum speeds), the physics can be unintuitive. I wanted to use my historical roast data to create and tune a model that I could use to do roast planning, control, and to help me build my own intuition for roasting. This website lets you interact with my roaster in a virtual, risk-free setting!<p>The models are custom Machine Learning modules that honor roaster physics and bean physics (this is not GPT&#x2F;transformer-based). Buncha math.<p>The models are trained on about a dozen real roasts. The default bean model is an Ethiopian Guji bean.<p>My next steps are to add other roasters and the ability to practice control&#x2F;reference tracking.

Found: October 06, 2025 ID: 1841

[Other] OpenZL: An open source format-aware compression framework <a href="https:&#x2F;&#x2F;github.com&#x2F;facebook&#x2F;openzl" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;facebook&#x2F;openzl</a><p><a href="https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2510.03203" rel="nofollow">https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2510.03203</a><p><a href="https:&#x2F;&#x2F;openzl.org&#x2F;" rel="nofollow">https:&#x2F;&#x2F;openzl.org&#x2F;</a>

Found: October 06, 2025 ID: 1737
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