243 items indexed · AI tools, prompts, hooks & techniques
This is a toolkit for building advanced AI agents that run on 'edge networks', making them faster by being physically closer to users. These agents can search the web, access databases, and automatically hand off tasks to other specialized agents to solve complex problems.
This is a comprehensive guide for building professional AI agents that are ready for real-world use. It provides code-based tutorials to take an AI application from a simple prototype to a scalable, secure, and observable product.
This guide provides developers with concrete examples of how to build AI agents that are reliable enough for production use. It highlights specific open-source projects that focus on testing and handling unexpected scenarios, or 'edge cases', to ensure the AI doesn't break when faced with unusual user requests or data.
This project provides blueprints for building automated AI assistants to handle complex business tasks like customer onboarding or content creation. It demonstrates how multiple AI 'agents' can collaborate, offering a model for creating a specialized digital workforce.
For complex coding tasks, using two specialized AI assistants is more effective than one. This technique uses an AI like OpenAI Codex to rapidly generate the initial functional code, and then uses a different AI, like Claude Code, to review, refactor, and improve the code's quality for production use.
Google has released Gemini 3, a new AI model that can understand text, images, audio, and video simultaneously. It boasts a very large memory (2-million-token context window) and is 30% more efficient and 15% cheaper than competitors, making it a powerful new option for developers.
This document compares two distinct approaches to AI-powered coding assistants. The 'Cursor' style prioritizes speed and rapid edits for individual developers and prototypes, while the 'Windsurf' style focuses on deep, project-wide understanding for large-scale changes and enterprise team collaboration.
This document outlines two advanced methods for automating software development tasks. Claude Code excels at dynamic, context-aware problem solving like complex refactoring, while Codex CLI provides predictable, auditable automation through strict profiles, ideal for processes like CI/CD and deployments. Businesses can use a hybrid approach, assigning creative work to Claude and repetitive, high-stakes tasks to Codex for optimal efficiency and control.
OpenCLAW's latest update introduces a 'ContextEngine,' allowing developers to build more intelligent and customized AI agents for your business needs. It also improves reliability by automatically switching between AI providers like OpenAI and Anthropic if one fails, ensuring your AI tools remain consistently operational.
The OpenAI Codex CLI is a command-line tool that gives developers direct terminal access to powerful AI models for coding. Recent updates have made it more 'agentic,' allowing it to independently plan and execute complex tasks, understand image uploads like screenshots, and integrate directly with VS Code and GitHub to streamline workflows.
Anthropic has updated its AI coding assistant, Claude Code, with new capabilities in early 2026. The update adds skills for interacting with the Claude API and Microsoft Office, improves integration with other tools, and expands voice command support to more languages.
This guide walks business owners through a five-phase process for automating repetitive workflows using AI: auditing current tasks, preparing data, selecting tools, testing with human oversight, and scaling based on measured ROI. It uses an impact-feasibility matrix to prioritize which processes to automate first, reducing risk on early pilots. A real-world example (Leaf Home saving $120K) anchors the framework in tangible business outcomes.