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The idea is simple: pipe your command through logifai, and Claude Code can search your logs directly.

npm run dev 2>&1 | logifai Hit an error → just ask Claude "what went wrong?" It captures everything into structured NDJSON, has a Web UI with live streaming, auto-redacts secrets, and includes a Claude Code Skill so Claude can search your logs without you ever copy-pasting terminal output.

It also has a Log Reference feature — select lines in the Web UI, click "Copy Ref", paste a compact logifai:// URI into Claude instead of hundreds of log lines. Keeps your context window clean.

It solves what I found to be the biggest pain point: the manual copy-paste shuttle between terminal and Claude Code.

Feedback and contributions welcome!

https://github.com/tomoyaf/logifai

Comments URL: https://news.ycombinator.com/item?id=46942233

Points: 1

# Comments: 0

Article URL: https://github.com/superS007/localllmjournal

Comments URL: https://news.ycombinator.com/item?id=46942206

Points: 2

# Comments: 0

Article URL: https://techcrunch.com/2026/02/07/india-has-changed-its-startup-rules-for-deep-tech/

Comments URL: https://news.ycombinator.com/item?id=46942179

Points: 2

# Comments: 1

Postman has quietly removed free multi-user collaboration and limited the free plan to a single user.

This hits small teams, students, and open-source contributors the hardest which is ironic since those users helped make Postman the default in the first place.

We decided not to pay and switched tools instead. Ended up with Apidog, which covers API design, testing, and docs together and still supports team workflows.

Interested to hear how others are reacting paying, migrating, or rolling their own setup?

Comments URL: https://news.ycombinator.com/item?id=46942116

Points: 1

# Comments: 0

Article URL: https://aecmag.com/features/the-rise-of-the-11-remote-workstation/

Comments URL: https://news.ycombinator.com/item?id=46942110

Points: 1

# Comments: 0

URL: https://github.com/twwch/next-chat-skills

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Text (paste into the "text" field):

Hi HN,

I built an open-source AI assistant that can autonomously discover, install, and execute Skills to actually complete tasks for you.

The Problem:

Most AI chatbots today are stuck in "read-only" mode. They can tell you how to do something, but they can't do it. Want to convert a PPTX to PDF? The AI will explain how, but you still have to run the commands yourself.

The Solution:

Next-Chat-Skills is a self-hosted AI assistant with a plugin system called Skills. When you ask the AI to do something it can't handle natively, it:

1. Searches for a relevant Skill (like an app store for AI capabilities) 2. Installs it automatically (npx skills add ...) 3. Executes the Skill's scripts (Python, Node.js, Shell) 4. Streams real-time output back to you in a terminal UI 5. Recovers from errors by installing missing dependencies and retrying

For example:

User: "Summarize this YouTube video for me" AI: -> Searches for a video-summarizer Skill -> Installs it (yt-dlp + Whisper) -> Downloads the video, transcribes audio -> Returns a structured summary No manual setup. No copy-pasting commands. The AI handles the entire workflow.

What is a Skill?

A Skill is just a folder with a SKILL.md descriptor and some scripts:

~/.agents/skills/video-summarizer/ ├── SKILL.md # Metadata + description ├── scripts/ │ ├── download.py # Download video │ ├── transcribe.py # Whisper transcription │ └── summarize.js # Generate summary └── rules/ # Usage guidelines for the AI Anyone can create and share Skills. The AI reads the SKILL.md to understand when and how to invoke each script. It's composable — the more Skills you add, the more capable your assistant becomes.

Key Features:

- Autonomous Skill discovery & installation — AI finds and installs what it needs - Real-time script execution — streams terminal output via SSE, supports Python/Node.js/Shell - File generation & download — scripts can generate files (PPTX, PDF, images) that users can download directly from chat - Multi-file upload & parsing — supports images, PDF, DOCX, XLSX, PPTX - Dual database — SQLite (zero-config) or PostgreSQL (production) - Optional auth — Google OAuth or fingerprint-based, works without login too - Docker-ready — pre-built image with Python, FFmpeg, LibreOffice, and popular Skills pre-installed - Works with any OpenAI-compatible API — GPT-4o, Claude (via proxy), local models, etc.

Tech Stack: Next.js 16, React 19, TypeScript, Vercel AI SDK, Tailwind CSS 4, shadcn/ui, Drizzle ORM (SQLite / PostgreSQL), Docker (Node.js 20 + Python 3)

Quick Start:

# Docker (fastest) docker run -p 3000:3000 \ -e OPENAI_API_KEY=sk-xxx \ -e OPENAI_BASE_URL=https://api.openai.com/v1 \ twwch/next-chat-skills:latest # Or from source git clone https://github.com/twwch/next-chat-skills cd next-chat-skills npm install && npm run dev Why I Built This:

I got tired of AI assistants that stop at "here's a code snippet." I wanted an AI that could actually run the code, handle failures, install dependencies, and deliver the final result — like having a junior developer who can use any Skill you point them at.

The Skills system makes this extensible without modifying the core app. Anyone can package a workflow as a Skill and share it.

What's Next:

- Skill marketplace / registry for community sharing - Multi-step workflow chaining (Skill A output -> Skill B input) - Better sandboxing for script execution - MCP (Model Context Protocol) integration

I'd love to hear your feedback. What Skills would you want to see? What's missing?

GitHub: https://github.com/twwch/next-chat-skills License: Apache 2.0

Comments URL: https://news.ycombinator.com/item?id=46942091

Points: 1

# Comments: 0

I moved my IoT compiler to test something from an AI vibe coding standpoint. The result is SETC a compiler and permit system and a free book that documents what I learned along the way.

The book starts with the problem, AI agents are writing and executing code with minimal oversight. Databases deleted, drives wiped, dozens of CVEs across every major AI coding tool. Usage is up, trust is down.

Then it walks through one approach, Ed25519 signed permits, Secure Enclave integration, M of N team approval, capability gated runtimes, and an ECDH killswitch. It stirs ideas about what the future may look like but doesn't necessarily have to but stirs the idea of what the gates might be then.

Would appreciate feedback from anyone working on similar problems & your approach.

Book: https://book.se.tc page: https://se.tc Docker: docker pull humanatsetc/setc:book-edition

Comments URL: https://news.ycombinator.com/item?id=46942086

Points: 1

# Comments: 0

Article URL: https://glovable.dev

Comments URL: https://news.ycombinator.com/item?id=46942079

Points: 1

# Comments: 0

Article URL: https://safeoid.com/

Comments URL: https://news.ycombinator.com/item?id=46942047

Points: 1

# Comments: 1

Article URL: http://www.jona.ca/2026/02/comic-code-reviews-part-2.html

Comments URL: https://news.ycombinator.com/item?id=46942017

Points: 1

# Comments: 1

I built a bootable Linux distribution that treats AI as a system primitive – like CPU or memory. Designed for security-conscious environments where data cannot leave the network.

The problem: Most AI requires cloud APIs, which means your data leaves your control. For banks, healthcare, defense, and regulated industries – that's a non-starter.

The solution: EdgeAI-OS runs everything locally. No cloud calls. No API keys. No telemetry. Boot the ISO, use AI. Your data never leaves the machine.

Security features: - 100% offline operation – air-gap friendly, zero network dependencies - No external API calls – all inference runs locally on CPU - Command risk assessment – every command classified as Safe/Moderate/Dangerous - Dangerous pattern blocking – prevents rm -rf /, curl|bash, fork bombs, etc. - Open source & auditable – MIT licensed, inspect every line of code - No data exfiltration – nothing phones home, ever

What's in the ISO: - Local LLMs (TinyLlama 1.1B + SmolLM 135M) – runs on CPU, no GPU needed - ai-sh: natural language shell where 80% of queries resolve instantly via templates - Multi-tier routing: simple queries → fast model, complex → larger model

Example ai-sh session: what time is it? [template] date ← instant, no LLM

files larger than 1gb [template] find . -size +1G ← instant, no LLM

rm -rf / [DANGEROUS] Blocked ← security check

configure nginx as reverse proxy [ai-generated] ... ← uses local LLM (~1-2s)

Target use cases: - Air-gapped enterprise environments (banks, healthcare, government) - Defense & classified networks - Edge devices with no internet connectivity - Privacy-conscious developers - Compliance-heavy industries (HIPAA, GDPR, SOC2)

Built with Rust, based on Debian. 4GB RAM recommended.

GitHub: https://github.com/neuralweaves/edgeai-os ISO Download: https://github.com/neuralweaves/edgeai-os/releases (1.2GB)

Would love feedback, especially from anyone working in secure/regulated environments. What features would make this enterprise-ready for you?

Comments URL: https://news.ycombinator.com/item?id=46942012

Points: 1

# Comments: 0

Starting from Seti@home, to bitcoin,.. now running AI Slop commands on my pc with full admin rights.. maybe openai can run workloads on my pc and send me some money for doing their work?

Comments URL: https://news.ycombinator.com/item?id=46942009

Points: 1

# Comments: 0

npx agentseed init

AGENTS.md (https://agents.md) is a standard file used by AI coding agents to understand a repo (stack, commands, conventions).

Agentseed generates it directly from the codebase using static analysis. Optional LLM augmentation is supported by bringing your own API key.

Extracts languages, frameworks, dependencies, build/test commands, directory structure, and monorepo boundaries.

Comments URL: https://news.ycombinator.com/item?id=46941990

Points: 1

# Comments: 0

Article URL: https://www.ft.com/content/d503afd5-1012-40f0-8f9d-620dcb39a9a2

Comments URL: https://news.ycombinator.com/item?id=46941988

Points: 2

# Comments: 0

Article URL: http://saturnine.cc/klint/

Comments URL: https://news.ycombinator.com/item?id=46941972

Points: 1

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Article URL: https://substack.com/@beccaselah/p-181168438

Comments URL: https://news.ycombinator.com/item?id=46941966

Points: 2

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Article URL: https://americanbusinesshistory.org/americas-most-valuable-companies-1995-2023/

Comments URL: https://news.ycombinator.com/item?id=46941942

Points: 2

# Comments: 0

Article URL: https://gainsec.com/2025/10/08/setting-up-your-own-4g-lte-network-150-for-your-embedded-system-iot-hacking-lab-via-open5gs-cbrs-enodeb-on-ubuntu-24-04/

Comments URL: https://news.ycombinator.com/item?id=46941885

Points: 2

# Comments: 1

Article URL: https://surfingcomplexity.blog/2026/02/08/nobody-knows-how-the-whole-system-works/

Comments URL: https://news.ycombinator.com/item?id=46941882

Points: 4

# Comments: 0

Article URL: https://zazolabs.com/odirect-the-problem-that-grew-up/

Comments URL: https://news.ycombinator.com/item?id=46941868

Points: 1

# Comments: 0