Writing AI Tools

A step-by-step guide for turning a spare Mac into an always-on machine Claude Code can control over SSH or from the Claude app.

An article about using GitHub Agentic Workflows to scale documentation QA with a tiered AI setup, combining deterministic checks with LLM-assisted reviews, centralized workflows, and MCP-backed knowledge.

A long-form essay about why AI coding software factories break down, with discussion of harness engineering, benchmark limits, and safer ways to use coding agents.

A web app that generates product or project ideas by pairing familiar tools with an added agent layer. The page frames it as an idea generator for “copy idea” style prompts, with a simple call to action to pull the lever for a new departure.

A detailed tutorial that explains what agent tools are and walks through a basic set of implementation patterns for an AI agent in Python, including bash, file, search, edit, and web fetch tools.

A short policy file for the ripgrep project that explains how contributors may use AI tools while contributing, and sets rules for issues, pull requests, and comments.

A lightweight Hacker News view that filters out AI-related stories and shows a cleaner front page feed.

A playful benchmark dashboard that ranks LLMs based on one person's 10-question scoring process.

A small web app for taking a break from AI and recording a short session away from LLMs.

An educational article explaining world models, latent states, dynamics learning, and planning for agents, with examples from gridworld, Dreamer, and MuZero.

AImpostor is an Electron-based ChatGPT wrapper for macOS that mimics Claude’s visual style and color scheme. The repo includes an install script for placing the app in ~/Applications and a screenshot asset.

An independent white paper proposing a local-deployment path for frontier AI weights, with a PDF, generator script, and a detailed README outlining the argument, sections, and contribution process.

A GitHub-hosted guidelines file for AI coding assistants used in Stanford CS336. It tells assistants how to help students with debugging, explanations, and feedback while avoiding direct solutions or code generation.

An article on applying pace-layer thinking to AI-assisted software development. It explains where generative AI fits well in fast-changing layers, where it is risky in slower layers, and how architecture should separate the two.

A retrospective essay about using LLMs to build and debug a programming language, including memory safety, runtime testing, and tool-assisted code health.

A developer blog post about how GenAI has changed the author’s coding workflow, including Claude, Maestro, Kilo.AI, git worktrees, voice prompting, and custom skills.

A GitHub-hosted research note about an agent-driven engineering workflow, comparing merged PR volume across Kungfu, Google AX, and OpenAI references.

An article about an AI agent jail post on Show HN and the wave of LLM-generated sales pitches it attracted, with examples of the outreach and the author’s responses.