Velxio, Arduino Emulator
5 by dmonterocrespo | 3 comments on Hacker News.
Monday, March 9, 2026
Sunday, March 8, 2026
New top story on Hacker News: Show HN: Skir – like Protocol Buffer but better
Show HN: Skir – like Protocol Buffer but better
13 by gepheum | 11 comments on Hacker News.
Why I built Skir: https://ift.tt/8vqKg6i... Quick start: npx skir init All the config lives in one YML file. Website: https://skir.build GitHub: https://ift.tt/GM8qU5C Would love feedback especially from teams running mixed-language stacks.
13 by gepheum | 11 comments on Hacker News.
Why I built Skir: https://ift.tt/8vqKg6i... Quick start: npx skir init All the config lives in one YML file. Website: https://skir.build GitHub: https://ift.tt/GM8qU5C Would love feedback especially from teams running mixed-language stacks.
Saturday, March 7, 2026
Friday, March 6, 2026
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Friday, February 27, 2026
New top story on Hacker News: Show HN: Unfudged – version every change between commits - local-first
Show HN: Unfudged – version every change between commits - local-first
12 by cyrusradfar | 10 comments on Hacker News.
I built unf after I pasted a prompt into the wrong agent terminal and it overwrote hours of hand-edits across a handful of files. Git couldn't help because I hadn't finished/committed my in progress work. I wanted something that recorded every save automatically so I could rewind to any point in time. I wanted to make it difficult for an agent to permanently screw anything up, even with an errant rm -rf unf is a background daemon that watches directories you choose (via CLI) and snapshots every text file on save. It stores file contents in an object store, tracks metadata in SQLite, and gives you a CLI to query and restore any version. The install includes a UI, as well to explore the history through time. The tool skips binaries and respects `.gitignore` if one exists. The interface borrows from git so it should feel familiar: unf log , unf diff , unf restore . I say "UN-EF" vs U.N.F, but that's for y'all to decide: I started by calling the project Unfucked and got unfucked.ai, which if you know me and the messes I get myself into, is a fitting purchase. The CLI command is `unf` and the Tauri desktop app is called "Unfudged". How it works: https://ift.tt/agvXmM2 (summary below) The daemon uses FSEvents on macOS and inotify on Linux. When a file changes, `unf` hashes the content with BLAKE3 and checks whether that hash already exists in the object store — if it does, it just records a new metadata entry pointing to the existing blob. If not, it writes the blob and records the entry. Each snapshot is a row in SQLite. Restores read the blob back from the object store and overwrite the file, after taking a safety snapshot of the current state first (so restoring is itself reversible). There are two processes. The core daemon does the real work of managing FSEvents/inotify subscriptions across multiple watched directories and writing snapshots. A sentinel watchdog supervises it, kept alive and aligned by launchd on macOS and systemd on Linux. If the daemon crashes, the sentinel respawns it and reconciles any drift between what you asked to watch and what's actually being watched. It was hard to build the second daemon because it felt like conceding that the core wasn't solid enough, but I didn't want to ship a tool that demanded perfection to deliver on the product promise, so the sentinel is the safety net. Fingers crossed, I haven’t seen it crash in over a week of personal usage on my Mac. But, I don't want to trigger "works for me" trauma. The part I like most: On the UI, I enjoy viewing files through time. You can select a time section and filter your projects on a histogram of activity. That has been invaluable in seeing what the agent was doing. On the CLI, the commands are composable. Everything outputs to stdout so you can pipe it into whatever you want. I use these regularly and AI agents are better with the tool than I am: # What did my config look like before we broke it? unf cat nginx.conf --at 1h | nginx -t -c /dev/stdin # Grep through a deleted file unf cat old-routes.rs --at 2d | grep "pub fn" # Count how many lines changed in the last 10 minutes unf diff --at 10m | grep '^[+-]' | wc -l # Feed the last hour of changes to an AI for review unf diff --at 1h | pbcopy # Compare two points in time with your own diff tool diff <(unf cat app.tsx --at 1h) <(unf cat app.tsx --at 5m) # Restore just the .rs files that changed in the last 5 minutes unf diff --at 5m --json | jq -r '.changes[].file' | grep '\.rs$' | xargs -I{} unf restore {} --at 5m # Watch for changes in real time watch -n5 'unf diff --at 30s' What was new for me: I came to Rust in Nov. 2025 honestly because of HN enthusiasm and some FOMO. No regrets. I enjoy the language enough that I'm now working on custom clippy lints to enforce functional programming practices. This project was also my first Apple-notarized DMG, my first Homebrew tap, and my second Tauri app (first one I've shared). Install & Usage: > brew install cyrusradfar/unf/unfudged Then unf watch in a directory. unf help covers the details (or ask your agent to coach).
12 by cyrusradfar | 10 comments on Hacker News.
I built unf after I pasted a prompt into the wrong agent terminal and it overwrote hours of hand-edits across a handful of files. Git couldn't help because I hadn't finished/committed my in progress work. I wanted something that recorded every save automatically so I could rewind to any point in time. I wanted to make it difficult for an agent to permanently screw anything up, even with an errant rm -rf unf is a background daemon that watches directories you choose (via CLI) and snapshots every text file on save. It stores file contents in an object store, tracks metadata in SQLite, and gives you a CLI to query and restore any version. The install includes a UI, as well to explore the history through time. The tool skips binaries and respects `.gitignore` if one exists. The interface borrows from git so it should feel familiar: unf log , unf diff , unf restore . I say "UN-EF" vs U.N.F, but that's for y'all to decide: I started by calling the project Unfucked and got unfucked.ai, which if you know me and the messes I get myself into, is a fitting purchase. The CLI command is `unf` and the Tauri desktop app is called "Unfudged". How it works: https://ift.tt/agvXmM2 (summary below) The daemon uses FSEvents on macOS and inotify on Linux. When a file changes, `unf` hashes the content with BLAKE3 and checks whether that hash already exists in the object store — if it does, it just records a new metadata entry pointing to the existing blob. If not, it writes the blob and records the entry. Each snapshot is a row in SQLite. Restores read the blob back from the object store and overwrite the file, after taking a safety snapshot of the current state first (so restoring is itself reversible). There are two processes. The core daemon does the real work of managing FSEvents/inotify subscriptions across multiple watched directories and writing snapshots. A sentinel watchdog supervises it, kept alive and aligned by launchd on macOS and systemd on Linux. If the daemon crashes, the sentinel respawns it and reconciles any drift between what you asked to watch and what's actually being watched. It was hard to build the second daemon because it felt like conceding that the core wasn't solid enough, but I didn't want to ship a tool that demanded perfection to deliver on the product promise, so the sentinel is the safety net. Fingers crossed, I haven’t seen it crash in over a week of personal usage on my Mac. But, I don't want to trigger "works for me" trauma. The part I like most: On the UI, I enjoy viewing files through time. You can select a time section and filter your projects on a histogram of activity. That has been invaluable in seeing what the agent was doing. On the CLI, the commands are composable. Everything outputs to stdout so you can pipe it into whatever you want. I use these regularly and AI agents are better with the tool than I am: # What did my config look like before we broke it? unf cat nginx.conf --at 1h | nginx -t -c /dev/stdin # Grep through a deleted file unf cat old-routes.rs --at 2d | grep "pub fn" # Count how many lines changed in the last 10 minutes unf diff --at 10m | grep '^[+-]' | wc -l # Feed the last hour of changes to an AI for review unf diff --at 1h | pbcopy # Compare two points in time with your own diff tool diff <(unf cat app.tsx --at 1h) <(unf cat app.tsx --at 5m) # Restore just the .rs files that changed in the last 5 minutes unf diff --at 5m --json | jq -r '.changes[].file' | grep '\.rs$' | xargs -I{} unf restore {} --at 5m # Watch for changes in real time watch -n5 'unf diff --at 30s' What was new for me: I came to Rust in Nov. 2025 honestly because of HN enthusiasm and some FOMO. No regrets. I enjoy the language enough that I'm now working on custom clippy lints to enforce functional programming practices. This project was also my first Apple-notarized DMG, my first Homebrew tap, and my second Tauri app (first one I've shared). Install & Usage: > brew install cyrusradfar/unf/unfudged Then unf watch in a directory. unf help covers the details (or ask your agent to coach).
Thursday, February 26, 2026
New top story on Hacker News: Show HN: Mission Control – Open-source task management for AI agents
Show HN: Mission Control – Open-source task management for AI agents
9 by meisnerd | 1 comments on Hacker News.
I've been delegating work to Claude Code for the past few months, and it's been genuinely transformative—but managing multiple agents doing different things became chaos. No tool existed for this workflow, so I built one. The Problem When you're working with AI agents (Claude Code, Cursor, Windsurf), you end up in a weird situation: - You have tasks scattered across your head, Slack, email, and the CLI - Agents need clear work items, context, and role-specific instructions - You have no visibility into what agents are actually doing - Failed tasks just... disappear. No retry, no notification - Each agent context-switches constantly because you're hand-feeding them work I was manually shepherding agents, copying task descriptions, restarting failed sessions, and losing track of what needed done next. It felt like hiring expensive contractors but managing them like a disorganized chaos experiment. The Solution Mission Control is a task management app purpose-built for delegating work to AI agents. It's got the expected stuff (Eisenhower matrix, kanban board, goal hierarchy) but built from the assumption that your collaborators are Claude, not humans. The killer feature is the autonomous daemon . It runs in the background, polls your task queue, spawns Claude Code sessions automatically, handles retries, manages concurrency, and respects your cron-scheduled work. One click: your entire work queue activates. The Architecture - Local-first : Everything lives in JSON files. No database, no cloud dependency, no vendor lock-in. - Token-optimized API : The task/decision payloads are ~50 tokens vs ~5,400 unfiltered. Matters when you're spawning agents repeatedly. - Rock-solid concurrency : Zod validation + async-mutex locking prevents corruption under concurrent writes. - 193 automated tests : This thing has to be reliable. It's doing unattended work. The app is Next.js 15 with 5 built-in agent roles (researcher, developer, marketer, business-analyst, plus you). You define reusable skills as markdown that get injected into agent prompts. Agents report back through an inbox + decisions queue. Why Release This? A few people have asked for access, and I think it's genuinely useful for anyone delegating to AI. It's MIT licensed, open source, and actively maintained. What's Next - Human collaboration (sharing tasks with real team members) - Integrations with GitHub issues and email inboxes - Better observability dashboard for daemon execution - Custom agent templates (currently hardcoded roles) If you're doing something similar—delegating serious work to AI—check it out and let me know what's broken. GitHub: https://ift.tt/wExlmPa
9 by meisnerd | 1 comments on Hacker News.
I've been delegating work to Claude Code for the past few months, and it's been genuinely transformative—but managing multiple agents doing different things became chaos. No tool existed for this workflow, so I built one. The Problem When you're working with AI agents (Claude Code, Cursor, Windsurf), you end up in a weird situation: - You have tasks scattered across your head, Slack, email, and the CLI - Agents need clear work items, context, and role-specific instructions - You have no visibility into what agents are actually doing - Failed tasks just... disappear. No retry, no notification - Each agent context-switches constantly because you're hand-feeding them work I was manually shepherding agents, copying task descriptions, restarting failed sessions, and losing track of what needed done next. It felt like hiring expensive contractors but managing them like a disorganized chaos experiment. The Solution Mission Control is a task management app purpose-built for delegating work to AI agents. It's got the expected stuff (Eisenhower matrix, kanban board, goal hierarchy) but built from the assumption that your collaborators are Claude, not humans. The killer feature is the autonomous daemon . It runs in the background, polls your task queue, spawns Claude Code sessions automatically, handles retries, manages concurrency, and respects your cron-scheduled work. One click: your entire work queue activates. The Architecture - Local-first : Everything lives in JSON files. No database, no cloud dependency, no vendor lock-in. - Token-optimized API : The task/decision payloads are ~50 tokens vs ~5,400 unfiltered. Matters when you're spawning agents repeatedly. - Rock-solid concurrency : Zod validation + async-mutex locking prevents corruption under concurrent writes. - 193 automated tests : This thing has to be reliable. It's doing unattended work. The app is Next.js 15 with 5 built-in agent roles (researcher, developer, marketer, business-analyst, plus you). You define reusable skills as markdown that get injected into agent prompts. Agents report back through an inbox + decisions queue. Why Release This? A few people have asked for access, and I think it's genuinely useful for anyone delegating to AI. It's MIT licensed, open source, and actively maintained. What's Next - Human collaboration (sharing tasks with real team members) - Integrations with GitHub issues and email inboxes - Better observability dashboard for daemon execution - Custom agent templates (currently hardcoded roles) If you're doing something similar—delegating serious work to AI—check it out and let me know what's broken. GitHub: https://ift.tt/wExlmPa
Wednesday, February 25, 2026
Tuesday, February 24, 2026
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New top story on Hacker News: Show HN: Moltis – AI assistant with memory, tools, and self-extending skills
Show HN: Moltis – AI assistant with memory, tools, and self-extending skills
6 by fabienpenso | 0 comments on Hacker News.
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. 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). 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 ( https://ift.tt/WEXu9lZ ) and owning your email ( https://ift.tt/vKjyGFt ). 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. It's alpha. I use it daily and I'm shipping because it's useful, not because it's done. Longer architecture deep-dive: https://ift.tt/KH1fLri... Happy to discuss the Rust architecture, security model, or local LLM setup. Would love feedback.
6 by fabienpenso | 0 comments on Hacker News.
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. 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). 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 ( https://ift.tt/WEXu9lZ ) and owning your email ( https://ift.tt/vKjyGFt ). 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. It's alpha. I use it daily and I'm shipping because it's useful, not because it's done. Longer architecture deep-dive: https://ift.tt/KH1fLri... Happy to discuss the Rust architecture, security model, or local LLM setup. Would love feedback.
Thursday, February 12, 2026
New top story on Hacker News: Show HN: Pgclaw – A "Clawdbot" in every row with 400 lines of Postgres SQL
Show HN: Pgclaw – A "Clawdbot" in every row with 400 lines of Postgres SQL
8 by calebhwin | 2 comments on Hacker News.
Hi HN, Been hacking on a simple way to run agents entirely inside of a Postgres database, "an agent per row". Things you could build with this: * Your own agent orchestrator * A personal assistant with time travel * (more things I can't think of yet) Not quite there yet but thought I'd share it in its current state.
8 by calebhwin | 2 comments on Hacker News.
Hi HN, Been hacking on a simple way to run agents entirely inside of a Postgres database, "an agent per row". Things you could build with this: * Your own agent orchestrator * A personal assistant with time travel * (more things I can't think of yet) Not quite there yet but thought I'd share it in its current state.
Wednesday, February 11, 2026
Tuesday, February 10, 2026
New top story on Hacker News: Show HN: HN Companion – web app that enhances the experience of reading HN
Show HN: HN Companion – web app that enhances the experience of reading HN
8 by georgeck | 2 comments on Hacker News.
HN is all about the rich discussions. We wanted to take the HN experience one step further - to bring the familiar keyboard-first navigation, find interesting viewpoints in the threads and get a gist of long threads so that we can decide which rabbit holes to explore. So we built HN Companion a year ago, and have been refining it ever since. Try it: https://ift.tt/V0Zwu92 or available as an extension for Firefox / Chrome: [0]. Most AI summarization strips the voices from conversations by flattening threads into a wall of text. This kills the joy of reading HN discussions. Instead, HN Companion works differently - it understands the thread hierarchy, the voting patterns and contrasting viewpoints - everything that makes HN interesting. Think of it like clustering related discussions across multiple hierarchies into a group and surfacing the comments that represent each cluster. It keeps the verbatim text with backlinks so that you never lose context and can continue the conversation from that point. Here is how the summarization works under the hood [1]. We first built this as an open source browser extension. But soon we learned that people hesitate to install it. So we built the same experience as a web app with all the features. This helped people see how it works, and use it on mobile too (in the browser or as PWA). This is now a playground to try new features before taking them to the browser extension. We did a Show HN a year ago [2] and we have added these features based on user feedback: * cached summaries - summaries are generated and cached on our servers. This improved the speed significantly. You still have the option to use your own API key or use local models through Ollama. * our system prompt is available in the Settings page of the extension. You can customize it as you wish. * sort the posts in the feed pages (/home, /show etc.) based on points, comments, time or the default sorting order. * We tried fine tuning an open weights model to summarize, but learned that with a good system prompt and user prompt, the frontier models deliver results of similar quality. So we didn’t use the fine-tuned model, but you can run them locally. The browser extension does not track any usage or analytics. The code is open source[3]. We want to continue to improve HN Companion, specifically add features like following an author, notes about an author, draft posts etc. See it in action for a post here https://ift.tt/pQ8XrVk We would love to get your feedback on what would make this more useful for your HN reading. [0] https://ift.tt/TvqNsnQ [1] https://ift.tt/YcTpms5 [2] https://ift.tt/Ag0cenu [3] https://ift.tt/ucq8fAa
8 by georgeck | 2 comments on Hacker News.
HN is all about the rich discussions. We wanted to take the HN experience one step further - to bring the familiar keyboard-first navigation, find interesting viewpoints in the threads and get a gist of long threads so that we can decide which rabbit holes to explore. So we built HN Companion a year ago, and have been refining it ever since. Try it: https://ift.tt/V0Zwu92 or available as an extension for Firefox / Chrome: [0]. Most AI summarization strips the voices from conversations by flattening threads into a wall of text. This kills the joy of reading HN discussions. Instead, HN Companion works differently - it understands the thread hierarchy, the voting patterns and contrasting viewpoints - everything that makes HN interesting. Think of it like clustering related discussions across multiple hierarchies into a group and surfacing the comments that represent each cluster. It keeps the verbatim text with backlinks so that you never lose context and can continue the conversation from that point. Here is how the summarization works under the hood [1]. We first built this as an open source browser extension. But soon we learned that people hesitate to install it. So we built the same experience as a web app with all the features. This helped people see how it works, and use it on mobile too (in the browser or as PWA). This is now a playground to try new features before taking them to the browser extension. We did a Show HN a year ago [2] and we have added these features based on user feedback: * cached summaries - summaries are generated and cached on our servers. This improved the speed significantly. You still have the option to use your own API key or use local models through Ollama. * our system prompt is available in the Settings page of the extension. You can customize it as you wish. * sort the posts in the feed pages (/home, /show etc.) based on points, comments, time or the default sorting order. * We tried fine tuning an open weights model to summarize, but learned that with a good system prompt and user prompt, the frontier models deliver results of similar quality. So we didn’t use the fine-tuned model, but you can run them locally. The browser extension does not track any usage or analytics. The code is open source[3]. We want to continue to improve HN Companion, specifically add features like following an author, notes about an author, draft posts etc. See it in action for a post here https://ift.tt/pQ8XrVk We would love to get your feedback on what would make this more useful for your HN reading. [0] https://ift.tt/TvqNsnQ [1] https://ift.tt/YcTpms5 [2] https://ift.tt/Ag0cenu [3] https://ift.tt/ucq8fAa
Monday, February 9, 2026
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Friday, February 6, 2026
New top story on Hacker News: Show HN: Daily-updated database of malicious browser extensions
Show HN: Daily-updated database of malicious browser extensions
7 by toborrm9 | 3 comments on Hacker News.
Hey HN, I built an automated system that tracks malicious Chrome/Edge extensions daily. The database updates automatically by monitoring chrome-stats for removed extensions and scanning security blogs. Currently tracking 1000+ known malicious extensions with extension IDs, names, and dates. I'm working on detection tools (GUI + CLI) to scan locally installed extensions against this database, but wanted to share the raw data first since maintained threat intelligence lists like this are hard to find. The automation runs 24/7 and pushes updates to GitHub. Free to use for research, integration into security tools, or whatever you need. Happy to answer questions about the scraping approach or data collection methods.
7 by toborrm9 | 3 comments on Hacker News.
Hey HN, I built an automated system that tracks malicious Chrome/Edge extensions daily. The database updates automatically by monitoring chrome-stats for removed extensions and scanning security blogs. Currently tracking 1000+ known malicious extensions with extension IDs, names, and dates. I'm working on detection tools (GUI + CLI) to scan locally installed extensions against this database, but wanted to share the raw data first since maintained threat intelligence lists like this are hard to find. The automation runs 24/7 and pushes updates to GitHub. Free to use for research, integration into security tools, or whatever you need. Happy to answer questions about the scraping approach or data collection methods.
Thursday, February 5, 2026
Wednesday, February 4, 2026
Tuesday, February 3, 2026
New top story on Hacker News: Show HN: PII-Shield – Log Sanitization Sidecar with JSON Integrity (Go, Entropy)
Show HN: PII-Shield – Log Sanitization Sidecar with JSON Integrity (Go, Entropy)
5 by aragoss | 0 comments on Hacker News.
What PII-Shield does: It's a K8s sidecar (or CLI tool) that pipes application logs, detects secrets using Shannon entropy (catching unknown keys like "sk-live-..." without predefined patterns), and redacts them deterministically using HMAC. Why deterministic? So that "pass123" always hashes to the same "[HIDDEN:a1b2c]", allowing QA/Devs to correlate errors without seeing the raw data. Key features: 1. JSON Integrity: It parses JSON, sanitizes values, and rebuilds it. It guarantees valid JSON output for your SIEM (ELK/Datadog). 2. Entropy Detection: Uses context-aware entropy analysis to catch high-randomness strings. 3. Fail-Open: Designed as a transparent pipe wrapper to preserve app uptime. The project is open-source (Apache 2.0). Repo: https://ift.tt/vUN1Tpt Docs: https://pii-shield.gitbook.io/docs/ I'd love your feedback on the entropy/threshold logic!
5 by aragoss | 0 comments on Hacker News.
What PII-Shield does: It's a K8s sidecar (or CLI tool) that pipes application logs, detects secrets using Shannon entropy (catching unknown keys like "sk-live-..." without predefined patterns), and redacts them deterministically using HMAC. Why deterministic? So that "pass123" always hashes to the same "[HIDDEN:a1b2c]", allowing QA/Devs to correlate errors without seeing the raw data. Key features: 1. JSON Integrity: It parses JSON, sanitizes values, and rebuilds it. It guarantees valid JSON output for your SIEM (ELK/Datadog). 2. Entropy Detection: Uses context-aware entropy analysis to catch high-randomness strings. 3. Fail-Open: Designed as a transparent pipe wrapper to preserve app uptime. The project is open-source (Apache 2.0). Repo: https://ift.tt/vUN1Tpt Docs: https://pii-shield.gitbook.io/docs/ I'd love your feedback on the entropy/threshold logic!
Monday, February 2, 2026
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Tuesday, January 27, 2026
New top story on Hacker News: A few random notes from Claude coding quite a bit last few weeks
A few random notes from Claude coding quite a bit last few weeks
51 by bigwheels | 65 comments on Hacker News.
https://ift.tt/TOFHSsx
51 by bigwheels | 65 comments on Hacker News.
https://ift.tt/TOFHSsx
Monday, January 26, 2026
Sunday, January 25, 2026
Saturday, January 24, 2026
New top story on Hacker News: Ask HN: Gmail spam filtering suddenly marking everything as spam?
Ask HN: Gmail spam filtering suddenly marking everything as spam?
27 by goopthink | 42 comments on Hacker News.
Almost all transactional emails are being marked as suspicious even when their SPF/DKIM records are fine and they’ve been whitelisted before. Did Google break something in gmail/spam filtering?
27 by goopthink | 42 comments on Hacker News.
Almost all transactional emails are being marked as suspicious even when their SPF/DKIM records are fine and they’ve been whitelisted before. Did Google break something in gmail/spam filtering?
Friday, January 23, 2026
New top story on Hacker News: Show HN: Teemux – Zero-config log multiplexer with built-in MCP server
Show HN: Teemux – Zero-config log multiplexer with built-in MCP server
4 by gajus | 0 comments on Hacker News.
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'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. There is one implementation detail that I geek out about: 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/remove nodes that share logs (a process that historically would have taken a central log aggregator). A super quick demo: npx teemux -- curl -N https://ift.tt/TWFcdtZ
4 by gajus | 0 comments on Hacker News.
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'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. There is one implementation detail that I geek out about: 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/remove nodes that share logs (a process that historically would have taken a central log aggregator). A super quick demo: npx teemux -- curl -N https://ift.tt/TWFcdtZ
Thursday, January 22, 2026
New top story on Hacker News: Show HN: Synesthesia, make noise music with a colorpicker
Show HN: Synesthesia, make noise music with a colorpicker
6 by tevans3 | 2 comments on Hacker News.
This is a (silly, little) app which lets you make noise music using a color picker as an instrument. When you click on a specific point in the color picker, a bit of JavaScript maps the binary representation of the clicked-on color's hex-code to a "chord" in the 24 tone-equal-temperament scale. That chord is then played back using a throttled audio generation method which was implemented via Tone.js. NOTE! Turn the volume way down before using the site. It is noise music. :)
6 by tevans3 | 2 comments on Hacker News.
This is a (silly, little) app which lets you make noise music using a color picker as an instrument. When you click on a specific point in the color picker, a bit of JavaScript maps the binary representation of the clicked-on color's hex-code to a "chord" in the 24 tone-equal-temperament scale. That chord is then played back using a throttled audio generation method which was implemented via Tone.js. NOTE! Turn the volume way down before using the site. It is noise music. :)
New top story on Hacker News: Show HN: Bible translated using LLMs from source Greek and Hebrew
Show HN: Bible translated using LLMs from source Greek and Hebrew
15 by epsteingpt | 15 comments on Hacker News.
Built an auditable AI (Bible) translation pipeline: Hebrew/Greek source packets -> verse JSON with notes rolling up to chapters, books, and testaments. Final texts compiled with metrics (TTR, n-grams). This is the first full-text example as far as I know (Gen Z bible doesn't count). There are hallucinations and issues, but the overall quality surprised me. LLMs have a lot of promise translating and rendering 'accessible' more ancient texts. The technology has a lot of benefit for the faithful, that I think is only beginning to be explored.
15 by epsteingpt | 15 comments on Hacker News.
Built an auditable AI (Bible) translation pipeline: Hebrew/Greek source packets -> verse JSON with notes rolling up to chapters, books, and testaments. Final texts compiled with metrics (TTR, n-grams). This is the first full-text example as far as I know (Gen Z bible doesn't count). There are hallucinations and issues, but the overall quality surprised me. LLMs have a lot of promise translating and rendering 'accessible' more ancient texts. The technology has a lot of benefit for the faithful, that I think is only beginning to be explored.
Wednesday, January 21, 2026
Tuesday, January 20, 2026
Monday, January 19, 2026
Sunday, January 18, 2026
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Friday, January 16, 2026
New top story on Hacker News: The Alignment Game
The Alignment Game
8 by dmvaldman | 0 comments on Hacker News.
https://docs.google.com/spreadsheets/d/1BYh9ZtEv4k7xoSXmtf1q...
8 by dmvaldman | 0 comments on Hacker News.
https://docs.google.com/spreadsheets/d/1BYh9ZtEv4k7xoSXmtf1q...
Thursday, January 15, 2026
Wednesday, January 14, 2026
Tuesday, January 13, 2026
Monday, January 12, 2026
New top story on Hacker News: Unauthenticated remote code execution in OpenCode
Unauthenticated remote code execution in OpenCode
24 by CyberShadow | 1 comments on Hacker News.
Previous versions of OpenCode started a server which allowed any website visited in a web browser to execute arbitrary commands on the local machine. Make sure you are using v1.1.10 or newer; see link for more details.
24 by CyberShadow | 1 comments on Hacker News.
Previous versions of OpenCode started a server which allowed any website visited in a web browser to execute arbitrary commands on the local machine. Make sure you are using v1.1.10 or newer; see link for more details.
Sunday, January 11, 2026
New top story on Hacker News: Ask HN: What Are You Working On? (January 2026)
Ask HN: What Are You Working On? (January 2026)
46 by david927 | 138 comments on Hacker News.
What are you working on? Any new ideas that you're thinking about?
46 by david927 | 138 comments on Hacker News.
What are you working on? Any new ideas that you're thinking about?
Saturday, January 10, 2026
Friday, January 9, 2026
New top story on Hacker News: Scientists discover oldest poison, on 60k-year-old arrows
Scientists discover oldest poison, on 60k-year-old arrows
5 by noleary | 0 comments on Hacker News.
https://ift.tt/cG2TdI9
5 by noleary | 0 comments on Hacker News.
https://ift.tt/cG2TdI9
Thursday, January 8, 2026
Wednesday, January 7, 2026
New top story on Hacker News: Polymarket refuses to pay bets that US would 'invade' Venezuela
Polymarket refuses to pay bets that US would 'invade' Venezuela
64 by petethomas | 28 comments on Hacker News.
https://ift.tt/ufiYLlV
64 by petethomas | 28 comments on Hacker News.
https://ift.tt/ufiYLlV
Tuesday, January 6, 2026
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Thursday, January 1, 2026
New top story on Hacker News: Show HN: Feature detection exploration in Lidar DEMs via differential decomp
Show HN: Feature detection exploration in Lidar DEMs via differential decomp
3 by DarkForestery | 0 comments on Hacker News.
I'm not a geospatial expert — I work in AI/ML. This started when I was exploring LiDAR data with agentic assitince and noticed that different signal decomposition methods revealed different terrain features. The core idea: if you systematically combine decomposition methods (Gaussian, bilateral, wavelet, morphological, etc.) with different upsampling techniques, each combination has characteristic "failure modes" that selectively preserve or eliminate certain features. The differences between outputs become feature-specific filters. The framework tests 25 decomposition × 19 upsampling methods across parameter ranges — about 40,000 combinations total. The visualization grid makes it easy to compare which methods work for what. Built in Cursor with Opus 4.5, NumPy, SciPy, scikit-image, PyWavelets, and OpenCV. Apache 2.0 licensed. I'd appreciate feedback from anyone who actually works with elevation data. What am I missing? What's obvious to practitioners that I wouldn't know?
3 by DarkForestery | 0 comments on Hacker News.
I'm not a geospatial expert — I work in AI/ML. This started when I was exploring LiDAR data with agentic assitince and noticed that different signal decomposition methods revealed different terrain features. The core idea: if you systematically combine decomposition methods (Gaussian, bilateral, wavelet, morphological, etc.) with different upsampling techniques, each combination has characteristic "failure modes" that selectively preserve or eliminate certain features. The differences between outputs become feature-specific filters. The framework tests 25 decomposition × 19 upsampling methods across parameter ranges — about 40,000 combinations total. The visualization grid makes it easy to compare which methods work for what. Built in Cursor with Opus 4.5, NumPy, SciPy, scikit-image, PyWavelets, and OpenCV. Apache 2.0 licensed. I'd appreciate feedback from anyone who actually works with elevation data. What am I missing? What's obvious to practitioners that I wouldn't know?
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