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Show HN: VOOG – Moog-style polyphonic synthesizer in Python with tkinter GUI

Body: I built a polyphonic synthesizer in Python with a tkinter GUI styled after the Moog Subsequent 37.<p><pre><code> Features: 3 oscillators, Moog ladder filter (24dB/oct), dual ADSR envelopes, LFO, glide, noise generator, 4 multitimbral channels, 19 presets, rotary knob GUI, virtual keyboard with mouse + QWERTY input, and MIDI support. No external GUI frameworks — just tkinter, numpy, and sounddevice.</code></pre>

Show HN: Microgpt is a GPT you can visualize in the browser

very much inspired by karpathy's microgpt of the same name. it's (by default) a 4000 param GPT/LLM/NN that learns to generate names. this is sorta an educational tool in that you can visualize the activations as they pass through the network, and click on things to get an explanation of them.

Show HN: Microgpt is a GPT you can visualize in the browser

very much inspired by karpathy's microgpt of the same name. it's (by default) a 4000 param GPT/LLM/NN that learns to generate names. this is sorta an educational tool in that you can visualize the activations as they pass through the network, and click on things to get an explanation of them.

Show HN: Knock-Knock.net – Visualizing the bots knocking on my server's door

Show HN: Knock-Knock.net – Visualizing the bots knocking on my server's door

Show HN: OpenWhisper – free, local, and private voice-to-text macOS app

I wanted a voice-to-text app but didn't trust any of the proprietary ones with my privacy.<p>So I decided to see if I could vibe code it with 0 macOS app & Swift experience.<p>It uses a local binary of whisper.cpp (a fast implementation of OpenAI's Whisper voice-to-text model in C++).<p>Github: <a href="https://github.com/richardwu/openwhisper" rel="nofollow">https://github.com/richardwu/openwhisper</a><p>I also decided to take this as an opportunity to compare 3 agentic coding harnesses:<p>Cursor w/ Opus 4.6: - Best one-shot UI by far - Didn't get permissioning correct - Had issues making the "Cancel recording" hotkey being turned on all the time<p>Claude Code w/ Opus 4.6: - Fewest turns to get main functionality right (recording, hotkeys, permissions) - Was able to get a decent UI with a few more turns<p>Codex App w/ Codex 5.3 Extra-High: - Worst one-shot UI - None of the functionality worked without multiple subsequent prompts

Show HN: Arcmark – macOS bookmark manager that attaches to browser as sidebar

Hey HN! I was a long-time Arc browser user and loved how its sidebar organized tabs and bookmarks into workspaces. I wanted to switch to other browsers without losing that workflow. So I built Arcmark, it's a macOS bookmark manager (Swift/AppKit) that floats as a sidebar attached to any browser window. It uses macOS accessibility API to follow the browser window around.<p>You get workspace-based links/bookmarks organization with nested folders, drag-and-drop reordering, and custom workspace colors. For the most part I tried replicating Arc's sidebar UX as close as possible.<p>1. Local-first: all data lives in a single JSON file ( ~/Library/Application Support/Arcmark/data.json). No accounts, no cloud sync.<p>2. Works with any browser: Chrome, Safari, Brave, Arc, etc. Or use it standalone as a bookmark manager with a regular window.<p>3. Import pinned tab and spaces from Arc: it parses Arc's StorableSidebar.json to recreate the exact workspace/folder structure.<p>4. Built with swift-bundler rather than Xcode.<p>There's a demo video in the README showing the sidebar attachment in action. The DMG is available on the releases page (macOS 13+), or you can build from source.<p>This is v0.1.0 so it's a very early version. Would appreciate any feedback or thoughts<p>GitHub: <a href="https://github.com/Geek-1001/arcmark" rel="nofollow">https://github.com/Geek-1001/arcmark</a>

Show HN: Arcmark – macOS bookmark manager that attaches to browser as sidebar

Hey HN! I was a long-time Arc browser user and loved how its sidebar organized tabs and bookmarks into workspaces. I wanted to switch to other browsers without losing that workflow. So I built Arcmark, it's a macOS bookmark manager (Swift/AppKit) that floats as a sidebar attached to any browser window. It uses macOS accessibility API to follow the browser window around.<p>You get workspace-based links/bookmarks organization with nested folders, drag-and-drop reordering, and custom workspace colors. For the most part I tried replicating Arc's sidebar UX as close as possible.<p>1. Local-first: all data lives in a single JSON file ( ~/Library/Application Support/Arcmark/data.json). No accounts, no cloud sync.<p>2. Works with any browser: Chrome, Safari, Brave, Arc, etc. Or use it standalone as a bookmark manager with a regular window.<p>3. Import pinned tab and spaces from Arc: it parses Arc's StorableSidebar.json to recreate the exact workspace/folder structure.<p>4. Built with swift-bundler rather than Xcode.<p>There's a demo video in the README showing the sidebar attachment in action. The DMG is available on the releases page (macOS 13+), or you can build from source.<p>This is v0.1.0 so it's a very early version. Would appreciate any feedback or thoughts<p>GitHub: <a href="https://github.com/Geek-1001/arcmark" rel="nofollow">https://github.com/Geek-1001/arcmark</a>

Show HN: Off Grid – Run AI text, image gen, vision offline on your phone

Your phone has a GPU more powerful than most 2018 laptops. Right now it sits idle while you pay monthly subscriptions to run AI on someone else's server, sending your conversations, your photos, your voice to companies whose privacy policy you've never read. Off Grid is an open-source app that puts that hardware to work. Text generation, image generation, vision AI, voice transcription — all running on your phone, all offline, nothing ever uploaded.<p>That means you can use AI on a flight with no wifi. In a country with internet censorship. In a hospital where cloud services are a compliance nightmare. Or just because you'd rather not have your journal entries sitting in someone's training data.<p>The tech: llama.cpp for text (15-30 tok/s, any GGUF model), Stable Diffusion for images (5-10s on Snapdragon NPU), Whisper for voice, SmolVLM/Qwen3-VL for vision. Hardware-accelerated on both Android (QNN, OpenCL) and iOS (Core ML, ANE, Metal).<p>MIT licensed. Android APK on GitHub Releases. Build from source for iOS.

Show HN: Off Grid – Run AI text, image gen, vision offline on your phone

Your phone has a GPU more powerful than most 2018 laptops. Right now it sits idle while you pay monthly subscriptions to run AI on someone else's server, sending your conversations, your photos, your voice to companies whose privacy policy you've never read. Off Grid is an open-source app that puts that hardware to work. Text generation, image generation, vision AI, voice transcription — all running on your phone, all offline, nothing ever uploaded.<p>That means you can use AI on a flight with no wifi. In a country with internet censorship. In a hospital where cloud services are a compliance nightmare. Or just because you'd rather not have your journal entries sitting in someone's training data.<p>The tech: llama.cpp for text (15-30 tok/s, any GGUF model), Stable Diffusion for images (5-10s on Snapdragon NPU), Whisper for voice, SmolVLM/Qwen3-VL for vision. Hardware-accelerated on both Android (QNN, OpenCL) and iOS (Core ML, ANE, Metal).<p>MIT licensed. Android APK on GitHub Releases. Build from source for iOS.

Show HN: SQL-tap – Real-time SQL traffic viewer for PostgreSQL and MySQL

sql-tap is a transparent proxy that captures SQL queries by parsing the PostgreSQL/MySQL wire protocol and displays them in a terminal UI. You can run EXPLAIN on any captured query. No application code changes needed — just change the port.

Show HN: SQL-tap – Real-time SQL traffic viewer for PostgreSQL and MySQL

sql-tap is a transparent proxy that captures SQL queries by parsing the PostgreSQL/MySQL wire protocol and displays them in a terminal UI. You can run EXPLAIN on any captured query. No application code changes needed — just change the port.

Show HN: Sameshi – a ~1200 Elo chess engine that fits within 2KB

I made a chess engine today, and made it fit within 2KB. I used a variant of MinMax called Negamax, with alpha beta pruning. For the board representation I have used a 120-cell "mailbox". I managed to squeeze in checkmate/stalemate in there, after trimming out some edge cases.<p>I am a great fan of demoscene (computer art subculture) since middle school, and hence it was a ritual i had to perform.<p>For estimating the Elo, I measured 240 automated games against Stockfish Elo levels (1320 to 1600) under fixed depth-5 and some constrained rules, using equal color distribution.<p>Then converted pooled win/draw/loss scores to Elo through some standard logistic formula with binomial 95% confidence interval.

Show HN: Sameshi – a ~1200 Elo chess engine that fits within 2KB

I made a chess engine today, and made it fit within 2KB. I used a variant of MinMax called Negamax, with alpha beta pruning. For the board representation I have used a 120-cell "mailbox". I managed to squeeze in checkmate/stalemate in there, after trimming out some edge cases.<p>I am a great fan of demoscene (computer art subculture) since middle school, and hence it was a ritual i had to perform.<p>For estimating the Elo, I measured 240 automated games against Stockfish Elo levels (1320 to 1600) under fixed depth-5 and some constrained rules, using equal color distribution.<p>Then converted pooled win/draw/loss scores to Elo through some standard logistic formula with binomial 95% confidence interval.

Show HN: I spent 3 years reverse-engineering a 40 yo stock market sim from 1986

Hello my name is Ben Ward for the past 3 years I have been remastering the financial game Wall Street Raider created by Michael Jenkins originally on DOS in 1986.<p>It has been a rough journey but I finally see the light at the end of the tunnel. I just recently redid the website and thought maybe the full story of how this project came to be would interest you all. Thank you for reading.

Show HN: I spent 3 years reverse-engineering a 40 yo stock market sim from 1986

Hello my name is Ben Ward for the past 3 years I have been remastering the financial game Wall Street Raider created by Michael Jenkins originally on DOS in 1986.<p>It has been a rough journey but I finally see the light at the end of the tunnel. I just recently redid the website and thought maybe the full story of how this project came to be would interest you all. Thank you for reading.

Show HN: Pgclaw – A "Clawdbot" in every row with 400 lines of Postgres SQL

Hi HN,<p>Been hacking on a simple way to run agents entirely inside of a Postgres database, "an agent per row".<p>Things you could build with this: * Your own agent orchestrator * A personal assistant with time travel * (more things I can't think of yet)<p>Not quite there yet but thought I'd share it in its current state.

Show HN: Sol LeWitt-style instruction-based drawings in the browser

Sol LeWitt was a conceptual artist who never touched his own walls.<p>He wrote instructions and other people executed them, the original prompt engineer!<p>I bookmarked a project called "Solving Sol" seven years ago and made a repo in 2018. Committed a README. Never pushed anything else.<p>Fast forward to 2026, I finally built it.<p><a href="https://intervolz.com/sollewitt/" rel="nofollow">https://intervolz.com/sollewitt/</a>

Show HN: Moltis – AI assistant with memory, tools, and self-extending skills

Hey HN. I'm Fabien, principal engineer, 25 years shipping production systems (Ruby, Swift, now Rust). I built Moltis because I wanted an AI assistant I could run myself, trust end to end, and make extensible in the Rust way using traits and the type system. It shares some ideas with OpenClaw (same memory approach, Pi-inspired self-extension) but is Rust-native from the ground up. The agent can create its own skills at runtime.<p>Moltis is one Rust binary, 150k lines, ~60MB, web UI included. No Node, no Python, no runtime deps. Multi-provider LLM routing (OpenAI, local GGUF/MLX, Hugging Face), sandboxed execution (Docker/Podman/Apple Containers), hybrid vector + full-text memory, MCP tool servers with auto-restart, and multi-channel (web, Telegram, API) with shared context. MIT licensed. No telemetry phoning home, but full observability built in (OpenTelemetry, Prometheus).<p>I've included 1-click deploys on DigitalOcean and Fly.io, but since a Docker image is provided you can easily run it on your own servers as well. I've written before about owning your content (<a href="https://pen.so/2020/11/07/own-your-content/" rel="nofollow">https://pen.so/2020/11/07/own-your-content/</a>) and owning your email (<a href="https://pen.so/2020/12/10/own-your-email/" rel="nofollow">https://pen.so/2020/12/10/own-your-email/</a>). Same logic here: if something touches your files, credentials, and daily workflow, you should be able to inspect it, audit it, and fork it if the project changes direction.<p>It's alpha. I use it daily and I'm shipping because it's useful, not because it's done.<p>Longer architecture deep-dive: <a href="https://pen.so/2026/02/12/moltis-a-personal-ai-assistant-built-in-rust/" rel="nofollow">https://pen.so/2026/02/12/moltis-a-personal-ai-assistant-bui...</a><p>Happy to discuss the Rust architecture, security model, or local LLM setup. Would love feedback.

Show HN: Moltis – AI assistant with memory, tools, and self-extending skills

Hey HN. I'm Fabien, principal engineer, 25 years shipping production systems (Ruby, Swift, now Rust). I built Moltis because I wanted an AI assistant I could run myself, trust end to end, and make extensible in the Rust way using traits and the type system. It shares some ideas with OpenClaw (same memory approach, Pi-inspired self-extension) but is Rust-native from the ground up. The agent can create its own skills at runtime.<p>Moltis is one Rust binary, 150k lines, ~60MB, web UI included. No Node, no Python, no runtime deps. Multi-provider LLM routing (OpenAI, local GGUF/MLX, Hugging Face), sandboxed execution (Docker/Podman/Apple Containers), hybrid vector + full-text memory, MCP tool servers with auto-restart, and multi-channel (web, Telegram, API) with shared context. MIT licensed. No telemetry phoning home, but full observability built in (OpenTelemetry, Prometheus).<p>I've included 1-click deploys on DigitalOcean and Fly.io, but since a Docker image is provided you can easily run it on your own servers as well. I've written before about owning your content (<a href="https://pen.so/2020/11/07/own-your-content/" rel="nofollow">https://pen.so/2020/11/07/own-your-content/</a>) and owning your email (<a href="https://pen.so/2020/12/10/own-your-email/" rel="nofollow">https://pen.so/2020/12/10/own-your-email/</a>). Same logic here: if something touches your files, credentials, and daily workflow, you should be able to inspect it, audit it, and fork it if the project changes direction.<p>It's alpha. I use it daily and I'm shipping because it's useful, not because it's done.<p>Longer architecture deep-dive: <a href="https://pen.so/2026/02/12/moltis-a-personal-ai-assistant-built-in-rust/" rel="nofollow">https://pen.so/2026/02/12/moltis-a-personal-ai-assistant-bui...</a><p>Happy to discuss the Rust architecture, security model, or local LLM setup. Would love feedback.