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The article discusses the concept of coding agents, which involves writing programs that can write other programs. It explores the potential benefits and challenges of this approach, including the ability to automate software development and the need to ensure safety and security.

The article discusses the rapid growth of commercial genetic testing and the concerns raised about the lack of understanding and regulation in this industry. It highlights the need for more oversight and education to ensure consumers are making informed decisions about their genetic information and its potential implications.

The article discusses the potential environmental impact of commercial space travel, highlighting concerns about greenhouse gas emissions, resource consumption, and the long-term effects on the Earth's atmosphere and climate.

The article discusses the RSS Librarian, a Python-based tool that allows users to manage their RSS feeds efficiently. It provides features like feed organization, article archiving, and full-text search to help users stay on top of their news and content consumption.

The article discusses 9 observations made by the author while using AI agents, including their potential to enhance human creativity, the need for careful oversight, and the importance of understanding their limitations and biases.

This article explores the benefits of cultivating a sense of joy and curiosity in life, highlighting how these qualities can foster personal growth, enhance relationships, and lead to a more fulfilling existence.

This article explores the impact of syntax on code readability and maintainability, highlighting the importance of writing clear and concise code that follows established programming conventions.

The article explains how to use Git to manage and version control files, including techniques for tracking changes, merging branches, and resolving conflicts. It provides a comprehensive overview of Git's file management capabilities for developers.

The article explores the retrieval of Opus 46, a lost symphony composed by a renowned classical musician. It details the efforts of researchers to locate and analyze the missing work, shedding light on the challenges and significance of uncovering lost musical masterpieces.

I completely vibe coded this digital Zen garden to have something to do for the 2 minute breaks that happen when you wait for your AI agent. 10k+ lines JS, 5k+ lines CSS and 0 idea how it really works besides main account login logic and stripe integration. Switched from Claude Code to Codex to Gemini and back to Codex which I feel is the most capable cli coding agent right now. Can do 5+ mins of work without going off rails consistently. This project was made just over 2 weeks and I certainly am feeling the AGI when working with SOTA coding tools

I have a bit of phone anxiety, and have a ton of dread around making phone calls to restaurants, banks, doctors, and so on and on.

I thought: AI could do this with a web form turned into a prompt.

Stack started out simple -> using 11labs for voice + claude + twillio, but it actually got rather complex (even though I tried vibe coding most).

First off, finding the phone numbers quickly is hard. This is done by scraping the web with some basic duckduckgo search and structure with openai calls.

Second, collecting the right information. I’m still struggling a bit with this but the architecture is that: A) user puts in call objective and business name B) if keywords are detected spin up one of the default form categories C) if not, get structured json from gpt-4o-mini and turn into react form

The cost of making a single call spun out of control, but luckily sonnet can handle a lot of the calls and I’m ok paying for twillio.

Ended up taking months to build my week-long project because of course.

It’s still WIP so feel free to email me: galcohavy@ucla.edu with any ideas or issues u ran into. \

Claude Code asks for permission before running tools (Bash, Write, Edit, etc.). If you're not at your terminal, it just waits. This tool hooks into Claude Code's PermissionRequest hook and sends each prompt as a push notification to your phone via ntfy.sh. Tap Approve or Deny, and Claude continues.

Setup:

  npm install -g claude-remote-approver
  claude-remote-approver setup

How it works: The hook POSTs the permission request to an ntfy topic, then subscribes to a response topic via SSE. When you tap a button on your phone, ntfy delivers the response back. The hook writes {"behavior":"allow"} or {"behavior":"deny"} to stdout and exits.

The topic name is generated with crypto.randomBytes(16) (128 bits), config file is 0600, and unanswered requests auto-deny after 120 seconds.

If you don't want requests going through the public ntfy.sh server, you can self-host ntfy and point the config at your own instance.

Github: https://github.com/yuuichieguchi/claude-remote-approver

npm: https://www.npmjs.com/package/claude-remote-approver

The article discusses the Ghostty style, a unique and personalized web design approach that emphasizes the integration of ghost buttons and typography to create visually appealing and user-friendly websites.

This paper proposes a novel deep learning-based approach for solving partial differential equations, which outperforms traditional numerical methods in accuracy and computational efficiency. The authors demonstrate the effectiveness of their method on a range of benchmark problems, highlighting its potential for widespread applications in science and engineering.

Finnish is morphologically complex — vowel harmony, six grammatical cases, free word order. AI models get it wrong in the same predictable ways every time.

  I built this after noticing that AI-generated Finnish triggers immediate pattern recognition in native speakers: overly formal register,
  SVO word order (Finnish allows much more variation), missing discourse particles (-han/-hän, -pa/-pä), and excessive nominalization.

  Before:
  "Tämä on erittäin merkittävä kehitysaskel, joka tulee vaikuttamaan laajasti alan tulevaisuuteen. On syytä huomata, että kyseinen
  innovaatio tarjoaa lukuisia mahdollisuuksia eri sidosryhmille."

  After:
  "Iso juttu alalle. En ole varma mihin tämä lopulta johtaa, mutta hyötyjiä on – varsinkin ne jotka ovat odottaneet tällaista jo vuosia."

  Finnish Humanizer is a pattern library — 26 identified patterns — packaged as a Claude Code skill and distributed for 15 platforms
  (Cursor, Copilot, Windsurf, ChatGPT custom instructions, etc.). It's not an additional model call. It's a checklist of linguistic tells
  you can apply mechanically.

  Patterns are grounded in Finnish linguistics research (Kotus — the Research Institute for the Languages of Finland).

  Would especially value feedback from Finnish speakers on pattern coverage and any false positives.

The article explores the author's appreciation for the Vi text editor, highlighting its versatility, power, and continued relevance in the modern software development landscape. It emphasizes Vi's enduring appeal due to its efficiency, customizability, and the deep connection it fosters between users and their tools.

The article describes the Chatterjee-Xi test, a statistical test used to determine if a dataset follows a specific distribution. The test is implemented in the SciPy library and can be used to assess the goodness of fit for a variety of probability distributions.

This article explores the engineering behind the animated ASCII banner displayed in the GitHub Copilot CLI. It delves into the technical details of generating and rendering the banner, including the use of ANSI escape codes and various optimization techniques to ensure smooth performance.

The article discusses the discovery of a new species of giant rhino, Paraceratherium, which was one of the largest land mammals that ever existed. It provides insights into the evolution and geographic distribution of these prehistoric giants.

I built an open-source bot that turns Trello cards into working code using Claude Code.

Drop a task card in a list → Sergio picks it up, explores your codebase, and posts an implementation plan as a comment. Add feedback, move the card back, and iterate. When you're happy, move it to the Development list → Sergio creates a worktree, writes the code, runs tests, and opens a draft PR on GitHub.

It's a tool that can be used by teams of devs and product managers to cover the knowledge gaps between non technical and technical planning.

All triggered by dragging cards. It's basically Claude Code running as an autonomous teammate on a $5/month VM, orchestrated through Trello. The two-user sandbox architecture keeps the AI isolated from secrets and credentials (similar to OpenClaw's approach to secure agentic coding).

The roadmap includes pluggable engine support (OpenCode, Codex) and MCP servers for reading Google Docs, Figma, and Notion directly from cards.

I built Paragent because I kept context-switching between features.

The idea: describe what you want in plain English, and an agent branches off, writes the code, and opens a PR. You can run 10 at once — each on its own branch.

How it works: - Connect your repo via GitHub App (minimal permissions: contents + PRs) - Describe a feature ("Add Stripe checkout to the pricing page") - Agent plans, writes, runs your verification, opens a PR - You review on GitHub like any other PR

You bring your own API keys (OpenAI, Anthropic, Gemini). We orchestrate but never store your code or prompts.

Free tier: 1 repo, 2 concurrent agents. Would love feedback from anyone who's tried Cursor/Copilot and wants something that works in parallel.

Hey HN,

  I'm shipping my first open-source project and I'm pretty nervous about it.

Why I built this: I was building AI agents and kept running into the same problem – they forget everything. Every conversation starts from zero. I wanted something that could: - Auto-extract facts from conversations (not just store raw text) - Handle "user moved from SF to NYC" without keeping both as true - Search by meaning, not just keywords - Version everything (who said what, when)

  Tech stack:
  - TypeScript + Hono (fast, edge-ready)
  - Convex (real-time DB + vector search)
  - Gemini (embeddings + extraction)

  What it does:
  # Store memory
  curl -X POST /v1/content -d '{"content": "User loves hiking, lives in SF"}'

  # Recall naturally
  curl -X POST /v1/recall -d '{"query": "outdoor hobbies"}'
  # Returns: "User loves hiking" with assembled context

  It handles the boring stuff – chunking, embeddings, deduplication, contradiction detection, versioning – so you can focus on your actual product.

  Links:
  - GitHub: https://github.com/akhilponnada/aethene
  - API Docs: OpenAPI spec in repo

Thanks for reading.

I've been using OpenClaw (AI assistant framework) for a while and loved it, so I wanted to roll it out to my whole team. The problem: getting non-engineers set up is painful, and sharing API keys across a team is a security headache.

So I built ClawHuddle — a self-hosted platform that lets you provision and manage OpenClaw instances for your team from a single dashboard.

What it does:

- One-click provisioning — Admin invites a user, they get their own isolated OpenClaw instance (each runs in its own Docker container)

- Managed skills — Admin curates and pre-installs skills for the team, so everyone gets vetted tooling out of the box

- Centralized API keys — No need for every team member to have their own keys. Also supports Claude Code CLI token login

- Channel setup — Quickly connect messaging channels (Telegram supported now; Discord and LINE planned)

Each instance is fully isolated — conversations, files, and configs never leak between users.

Stack: Next.js 16, Fastify, SQLite, Docker, Traefik. Monorepo with Turborepo.

There's a live demo at https://clawhuddle.com/ (may have some rough edges, actively fixing bugs).

Open source: https://github.com/allen-hsu/clawhuddle

Hope this is useful if you're trying to bring OpenClaw to a team setting.

Your AI agent is burning 6x more tokens than it needs to just to browse the web. We built OpenBrowser MCP to fix that. Most browser MCPs give the LLM dozens of tools: click, scroll, type, extract, navigate. Each call dumps the entire page accessibility tree into the context window. One Wikipedia page? 124K+ tokens. Every. Single. Call. OpenBrowser works differently. It exposes one tool. Your agent writes Python code, and OpenBrowser executes it in a persistent runtime with full browser access. The agent controls what comes back. No bloated page dumps. No wasted tokens. Just the data your agent actually asked for. The result? We benchmarked it against Playwright MCP (Microsoft) and Chrome DevTools MCP (Google) across 6 real-world tasks: - 3.2x fewer tokens than Playwright MCP - 6x fewer tokens than Chrome DevTools MCP - 144x smaller response payloads - 100% task success rate across all benchmarks One tool. Full browser control. A fraction of the cost. It works with any MCP-compatible client: - Cursor - VS Code - Claude Code (marketplace plugin with MCP + Skills) - Codex and OpenCode (community plugins) - n8n, Cline, Roo Code, and more Install the plugins here: https://github.com/billy-enrizky/openbrowser-ai/tree/main/pl... It connects to any LLM provider: Claude, GPT 5.2, Gemini, DeepSeek, Groq, Ollama, and more. Fully open source under MIT license. OpenBrowser MCP is the foundation for something bigger. We are building a cloud-hosted, general-purpose agentic platform where any AI agent can browse, interact with, and extract data from the web without managing infrastructure. The full platform is coming soon. Join the waitlist at openbrowser.me to get free early access. See the Demo: https://youtu.be/ov1rSYd42hE?si=pB6QgtQfm-CX1CEa See the full benchmark methodology: https://docs.openbrowser.me/comparison See the benchmark code: https://github.com/billy-enrizky/openbrowser-ai/tree/main/be... Browse the source: https://github.com/billy-enrizky/openbrowser-ai LinkedIn Post: https://www.linkedin.com/posts/enrizky-brillian_opensource-a... #OpenSource #AI #MCP #BrowserAutomation #AIAgents #DevTools #LLM #GeneralPurposeAI #AgenticAI

Rename.world is a platform that allows users to easily rename their internet domain names, providing a seamless process for updating their online presence and branding.

A large US company threatened legal action against an individual for releasing a free, open-source software project that was similar to the company's proprietary product. The article discusses the legal and ethical implications of this situation.