Blog
In-depth articles on AI models, tools, and engineering practices.
Why Use Hooks? The Engineering Pattern That Keeps Showing Up Everywhere
Hooks appear in React, PyTorch, webhooks, and AI agents. Here's why this pattern keeps solving the same core problem across software engineering.
Claude Web Search Tool: Dynamic Filtering, Pricing, and Implementation Guide
How Claude's web search tool works, why dynamic filtering with Opus 4.6 cuts token costs, and how to implement it in your API calls today.
Superpowers: Teaching AI Coding Agents to Think Before They Type
Superpowers uses structured markdown skills to force AI coding agents like Claude Code and Cursor to plan before coding — 67K GitHub stars and growing.
/simplify: Claude Code's Answer to AI-Generated Technical Debt
How Claude Code's /simplify command uses multi-agent review to clean up AI-generated code across reuse, quality, and efficiency.
Claude Code Scheduled Tasks: Automate Recurring Prompts with /loop and Cron
How to use Claude Code's /loop command and cron scheduling tools to automate recurring prompts, poll deployments, and set reminders within a session.
Why You Should Run AI Coding Agents Locally Instead of Cloud-Only
Cloud agents like Claude Code and Codex are powerful, but running AI agents locally with open-weight models gives you privacy, speed, and zero usage limits.
Red Green Refactor: Why TDD Is the Best Way to Control AI Coding Agents
Red Green Refactor — a 20-year-old TDD practice — turns out to be the most effective way to get reliable, high-quality code from AI coding agents like Claude Code.
Claude Opus 4.6 1M Context Now Default for Claude Code on Max, Team, and Enterprise
Claude Opus 4.6 with 1M context window is now the default model for Claude Code users on Max, Team, and Enterprise plans — here's what changes.
OpenAI's Updated Model Spec: What Changes for AI Alignment and Developer Trust
OpenAI publishes an updated Model Spec defining how its models should behave — here's what changed and why it matters for developers and the AI industry.
OpenAI's Technical Lessons From Building Computer Access for Agents
OpenAI shares key engineering lessons from building computer access for agents: tighter execution loops, file system context, and secure network access.
OpenAI's Chain-of-Thought Controllability Eval: What It Measures and Why It Matters
OpenAI releases a Chain-of-Thought Controllability evaluation to measure how well reasoning models follow instructions within their thinking process.
Obsidian + Claude Code: Building a Second Brain That Actually Works
How pairing Obsidian's local markdown vault with Claude Code's file-aware agent creates a persistent, controllable context system that solves AI's biggest usability problem.