🛠️ All DevTools

[Other] Show HN: Dwm.tmux – a dwm-inspired window manager for tmux Hey, HN! With all recent agentic workflows being primarily terminal- and tmux-based, I wanted to share a little project I created about decade ago.<p>I&#x27;ve continued to use this as my primary terminal &quot;window manager&quot; and wanted to share in case others might find it useful.<p>I would love to hear about other&#x27;s terminal-based workflows and any other tools you may use with similar functionality.

[Other] Winapp, the Windows App Development CLI

[Other] Show HN: 83 browser-use trajectories, visualized Hey all, Justin here. I previously built Phind, the AI search engine for developers.<p>One of the biggest problems we had there was figuring out what went wrong with bad searches. We had tons of searches per day, but less than 1% of users gave any explicit feedback. So we were either manually digging through searches or making general system improvements and hoping they helped.<p>This problem gets harder with agents. Traces are longer and more complex. It takes more effort to review them, so I&#x27;m building a tool that lets you analyze LLM outputs directly to help developers of LLM apps and agents understand where things are breaking and why.<p>I&#x27;ve put together a demo using browser-use agent traces (gpt-5): <a href="https:&#x2F;&#x2F;trails-red.vercel.app&#x2F;viewer" rel="nofollow">https:&#x2F;&#x2F;trails-red.vercel.app&#x2F;viewer</a><p>It&#x27;s early, but I have lots of ideas - live querying of past failures for currently-running agents, preference models to expand sparse signal data.<p>Would love feedback on the demo. Also if you&#x27;re building agents and have 10k+ traces per day that you&#x27;re not looking at but would like to, I&#x27;d love to talk.

[Other] Avoiding duplicate objects in Django querysets

[CLI Tool] Show HN: Teemux – Zero-config log multiplexer with built-in MCP server I started to use AI agents for coding and quickly ran into a frustrating limitation – there is no easy way to share my development environment logs with AI agents. So that&#x27;s what is Teemux. A simple CLI program that aggregates logs, makes them available to you as a developer (in a pretty UI), and makes them available to your AI coding agents using MCP.<p>There is one implementation detail that I geek out about:<p>It is zero config and has built-in leader nomination for running the web server and MCP server. When you start one `teemux` instance, it starts web server, .. when you start second and third instances, they join the first server and start merging logs. If you were to kill the first instance, a new leader is nominated. This design allows to seamless add&#x2F;remove nodes that share logs (a process that historically would have taken a central log aggregator).<p>A super quick demo:<p>npx teemux -- curl -N <a href="https:&#x2F;&#x2F;teemux.com&#x2F;random-logs" rel="nofollow">https:&#x2F;&#x2F;teemux.com&#x2F;random-logs</a>

[Other] Build & manage your developer portfolio without code Foliaro is a modern, open-source developer portfolio built with Next.js, TypeScript, and TailwindCSS. Unlike traditional portfolios that require code edits and redeploys, Foliaro includes a built-in admin panel to manage projects, skills, and personal details live from the UI. With keyboard shortcuts, secret access, JSON import/export, a first-time setup wizard, and smooth animations, it works like a lightweight CMS for developers.

[IDE/Editor] AI Agent Cluster Command Center for Developers AI Agent Cluster Command Center — A desktop application for managing multiple AI coding assistants simultaneously. - EdmondVirelle/Neural-Hive

[Other] Show HN: C/C++ Cheatsheet – a modern, practical reference for C and C++ Hi HN,<p>I’m the creator of C&#x2F;C++ Cheatsheet — a modern, practical reference for both C and C++ developers. It includes concise snippet-style explanations of core language features, advanced topics like coroutines and constexpr, system programming sections, debugging tools, and useful project setups. You can explore it online at <a href="https:&#x2F;&#x2F;cppcheatsheet.com&#x2F;" rel="nofollow">https:&#x2F;&#x2F;cppcheatsheet.com&#x2F;</a>.<p>I built this to help both beginners and experienced engineers quickly find clear examples and explanations without digging through fragmented blogs or outdated docs. It’s open source, regularly maintained, and contributions are welcome on GitHub.<p>If you’ve ever wanted a lightweight, example-focused guide to: - Modern C++ (templates, lambdas, concepts) - C fundamentals and memory handling - System programming - Debugging &amp; profiling …this site aims to be that resource.<p>Any feedback is welcome. Thank you.

[Other] Vargai/SDK – JSX for AI video, declarative programming language for Claude Code

[CLI Tool] Show HN: CLI for working with Apple Core ML models

[Other] 🎥 Make videos programmatically with React

[Other] Free, fast developer tools — no sign‑ups, no tracking. onlinedev.tools is a privacy‑first collection of developer utilities that run entirely in your browser. Format JSON, decode JWTs, generate UUIDs, test regex, convert colors, and more — all without sending data to a server. We built it to be fast, simple, and safe, so you can use it for quick tasks without worrying about privacy or setup. It’s free, no sign‑ups, and optimized for developers who just want tools that work.

[Other] Show HN: High speed graphics rendering research with tinygrad/tinyJIT I saw a tweet that tinygrad is so good that you could make a graphics library that wraps tg. So I’ve been hacking on a gtinygrad, and honestly it convinced me it could be used for legit research.<p>The JIT + tensor model ends up being a really nice way to express light transport all in simple python, so I reimplemented some new research papers from SIGGRAPH like REstir PG and SZ and it just works. instead of complicated cpp its just a 200 LOC of python.

[IDE/Editor] Show HN: Sweep, Open-weights 1.5B model for next-edit autocomplete Hey HN, we trained and open-sourced a 1.5B model that predicts your next edits, similar to Cursor. You can download the weights here (<a href="https:&#x2F;&#x2F;huggingface.co&#x2F;sweepai&#x2F;sweep-next-edit-1.5b" rel="nofollow">https:&#x2F;&#x2F;huggingface.co&#x2F;sweepai&#x2F;sweep-next-edit-1.5b</a>) or try it in our JetBrains plugin (<a href="https:&#x2F;&#x2F;plugins.jetbrains.com&#x2F;plugin&#x2F;26860-sweep-ai-autocomplete--coding-agent" rel="nofollow">https:&#x2F;&#x2F;plugins.jetbrains.com&#x2F;plugin&#x2F;26860-sweep-ai-autocomp...</a>).<p>Next-edit autocomplete differs from standard autocomplete by using your recent edits as context when predicting completions. The model is small enough to run locally while outperforming models 4x its size on both speed and accuracy.<p>We tested against Mercury (Inception), Zeta (Zed), and Instinct (Continue) across five benchmarks: next-edit above&#x2F;below cursor, tab-to-jump for distant changes, standard FIM, and noisiness. We found exact-match accuracy correlates best with real usability because code is fairly precise and the solution space is small.<p>Prompt format turned out to matter more than we expected. We ran a genetic algorithm over 30+ diff formats and found simple `original`&#x2F;`updated` blocks beat unified diffs. The verbose format is just easier for smaller models to understand.<p>Training was SFT on ~100k examples from permissively-licensed repos (4hrs on 8xH100), then RL for 2000 steps with tree-sitter parse checking and size regularization. The RL step fixes edge cases SFT can’t like, generating code that doesn’t parse or overly verbose outputs.<p>We&#x27;re open-sourcing the weights so the community can build fast, privacy-preserving autocomplete for any editor. If you&#x27;re building for VSCode, Neovim, or something else, we&#x27;d love to see what you make with it!

[CLI Tool] Show HN: Retain – A unified knowledge base for all your AI coding conversations Hey HN! I built Retain as the evolution of claude-reflect (github.com&#x2F;BayramAnnakov&#x2F;claude-reflect).<p>The original problem: I use Claude Code&#x2F;Codex daily for coding, plus claude.ai and ChatGPT occasionally. Every conversation contains decisions, corrections, and patterns I forget existed weeks later. I kept re-explaining the same preferences.<p>claude-reflect was a CLI tool that extracted learnings from Claude Code sessions. Retain takes this further with a native macOS app that:<p>- Aggregates conversations from Claude Code, claude.ai, ChatGPT, and Codex CLI - Instant full-text search across thousands of conversations (SQLite + FTS5)<p>It&#x27;s local-first - all data stays in a local SQLite database. No servers, no telemetry. Web sync uses your browser cookies to fetch conversations directly.

[Other] Show HN: What I learned building a local-only password manager (PassForgePro) Show HN: What I learned building a local-only password manager (PassForgePro)<p>Hi HN,<p>I built PassForgePro as a learning project to better understand password manager design, local-first security, and common cryptographic pitfalls.<p>The goal was not to replace mature tools like Bitwarden or KeePass, but to explore:<p>* how a local-only, zero-knowledge style design can work * key derivation with PBKDF2 and encrypted SQLite vaults (AES-256-GCM) * handling sensitive data in memory and clipboard cleanup * defining a realistic threat model and its limitations<p>This project is experimental and unaudited. I’m sharing it mainly to get feedback on the architecture, crypto choices, and overall approach, and to discuss what I got wrong or could improve (audits, reproducible builds, testing, etc.).<p>I’d really appreciate feedback, especially from people with security or cryptography experience.<p>Repo: <a href="https:&#x2F;&#x2F;github.com&#x2F;can-deliktas&#x2F;PassForgePro" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;can-deliktas&#x2F;PassForgePro</a> Docs &#x2F; demo: <a href="https:&#x2F;&#x2F;can-deliktas.github.io&#x2F;PassForgePro" rel="nofollow">https:&#x2F;&#x2F;can-deliktas.github.io&#x2F;PassForgePro</a>

[Other] Open source server code for the BitCraft MMORPG

[Other] PicoPCMCIA – a PCMCIA development board for retro-computing enthusiasts

[Database] Show HN: S2-lite, an open source Stream Store S2 was on HN for our intro blog post a year ago (<a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=42480105">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=42480105</a>). S2 started out as a serverless API — think S3, but for streams.<p>The idea of streams as a cloud storage primitive resonated with a lot of folks, but not having an open source option was a sticking point for adoption – especially from projects that were themselves open source! So we decided to build it: <a href="https:&#x2F;&#x2F;github.com&#x2F;s2-streamstore&#x2F;s2" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;s2-streamstore&#x2F;s2</a><p>s2-lite is MIT-licensed, written in Rust, and uses SlateDB (<a href="https:&#x2F;&#x2F;slatedb.io" rel="nofollow">https:&#x2F;&#x2F;slatedb.io</a>) as its storage engine. SlateDB is an embedded LSM-style key-value database on top of object storage, which made it a great match for delivering the same durability guarantees as s2.dev.<p>You can specify a bucket and path to run against an object store like AWS S3 — or skip to run entirely in-memory. (This also makes it a great emulator for dev&#x2F;test environments).<p>Why not just open up the backend of our cloud service? s2.dev has a decoupled architecture with multiple components running in Kubernetes, including our own K8S operator – we made tradeoffs that optimize for operation of a thoroughly multi-tenant cloud infra SaaS. With s2-lite, our goal was to ship something dead simple to operate. There is a lot of shared code between the two that now lives in the OSS repo.<p>A few features remain (notably deletion of resources and records), but s2-lite is substantially ready. Try the Quickstart in the README to stream Star Wars using the s2 CLI!<p>The key difference between S2 vs a Kafka or Redis Streams: supporting tons of durable streams. I have blogged about the landscape in the context of agent sessions (<a href="https:&#x2F;&#x2F;s2.dev&#x2F;blog&#x2F;agent-sessions#landscape">https:&#x2F;&#x2F;s2.dev&#x2F;blog&#x2F;agent-sessions#landscape</a>). Kafka and NATS Jetstream treat streams as provisioned resources, and the protocols&#x2F;implementations are oriented around such assumptions. Redis Streams and NATS allow for larger numbers of streams, but without proper durability.<p>The cloud service is completely elastic, but you can also get pretty far with lite despite it being a single-node binary that needs to be scaled vertically. Streams in lite are &quot;just keys&quot; in SlateDB, and cloud object storage is bottomless – although of course there is metadata overhead.<p>One thing I am excited to improve in s2-lite is pipelining of writes for performance (already supported behind a knob, but needs upstream interface changes for safety). It&#x27;s a technique we use extensively in s2.dev. Essentially when you are dealing with high latencies like S3, you want to keep data flowing throughout the pipe between client and storage, rather than go lock-step where you first wait for an acknowledgment and then issue another write. This is why S2 has a session protocol over HTTP&#x2F;2, in addition to stateless REST.<p>You can test throughput&#x2F;latency for lite yourself using the `s2 bench` CLI command. The main factors are: your network quality to the storage bucket region, the latency characteristics of the remote store, SlateDB&#x27;s flush interval (`SL8_FLUSH_INTERVAL=..ms`), and whether pipelining is enabled (`S2LITE_PIPELINE=true` to taste the future).<p>I&#x27;ll be here to get thoughts and feedback, and answer any questions!

[API/SDK] Show HN: SpeechOS – Wispr Flow-inspired voice input for any web app Hi Hacker News! I’m David Huie. I’m launching SpeechOS, a drop-in voice input SDK for web apps.<p>I was inspired by Wispr Flow and wanted the same workflow inside business apps (CRMs, docs, forms, support tools), not just a standalone tool. It’s saved me a massive amount of time vs typing.<p>How it works: add a couple lines of JS plus an API key, and SpeechOS shows a small mic widget on every text field.<p>Live demo: <a href="https:&#x2F;&#x2F;www.speechos.ai&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.speechos.ai&#x2F;</a><p>(Click a text box and the mic widget appears; click the gear icon to see settings, custom vocabulary, and snippet configuration.)<p>Users can:<p>- Dictate: speak naturally, real-time voice to polished text (punctuation, no filler&#x2F;typos)<p>- Edit: say “make it shorter”, “fix grammar”, “translate...”<p>- Command: define Siri-style app actions (for example, “submit form”, “mark complete”), and we match intent to your commands<p>It also supports:<p>- Custom vocabulary: domain terms and names (product names, acronyms, jargon) so they transcribe correctly<p>- Text snippets: saved reusable blocks of text you can insert by voice (for example, “my signature”, “disclaimer”, “my address”)<p>Why: text entry speed and accuracy still matter for productivity tools. A large-scale text entry dataset with 37,370 participants showed an average typing speed of 36.2 WPM and ~2.3% uncorrected errors. In speech research, speech recognition was about 3× faster than keyboard input and had ~20.4% lower error rate for English text entry. (<a href="https:&#x2F;&#x2F;hci.stanford.edu&#x2F;research&#x2F;speech&#x2F;" rel="nofollow">https:&#x2F;&#x2F;hci.stanford.edu&#x2F;research&#x2F;speech&#x2F;</a>)<p>SpeechOS is currently in beta and free for now. Sign up at <a href="https:&#x2F;&#x2F;app.speechos.ai&#x2F;accounts&#x2F;signup&#x2F;" rel="nofollow">https:&#x2F;&#x2F;app.speechos.ai&#x2F;accounts&#x2F;signup&#x2F;</a> and enter this HN-only beta code: HN-JFc74cVC (please don’t share outside HN).<p>Links:<p>SDK repo: <a href="https:&#x2F;&#x2F;github.com&#x2F;speechos-org&#x2F;speechos-client" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;speechos-org&#x2F;speechos-client</a><p>Demo: <a href="https:&#x2F;&#x2F;www.speechos.ai&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.speechos.ai&#x2F;</a><p>Signup (code: HN-JFc74cVC): <a href="https:&#x2F;&#x2F;app.speechos.ai&#x2F;accounts&#x2F;signup&#x2F;" rel="nofollow">https:&#x2F;&#x2F;app.speechos.ai&#x2F;accounts&#x2F;signup&#x2F;</a><p>I’d love feedback on:<p>1) Where this is most valuable in your stack (notes? docs? CRM entry? support macros?)<p>2) What you’d want from voice commands&#x2F;snippets configuration<p>3) What would make you comfortable shipping this (privacy&#x2F;security, latency, pricing)<p>If you’re building anything in voice AI&#x2F;dictation, I’d be happy to swap notes (david@speechos.ai).