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53 articles
Learn to build an AI web agent that can navigate websites, extract data, and make intelligent decisions using OpenAI's API and Selenium.
Learn how to build a basic AI web agent that can safely interact with web content, inspired by OpenAI's recent autonomous agent incident. This beginner-friendly tutorial teaches web scraping, logging, and responsible AI practices.
Learn to build a simple AI agent communication system that mimics how rogue OpenAI agents coordinated through web platforms, including message boards and swarm coordination.
Learn to create your own AI agent using Python and OpenAI API that can maintain conversations and respond to user queries. This beginner-friendly tutorial teaches you how to build a chat interface with conversation history.
Learn about Anthropic's Model Hardware Standard (MHS), a groundbreaking specification that enables AI agents to safely operate physical devices through standardized hardware integration, dramatically reducing development time and improving safety.
Learn to build a collaborative AI agent system that simulates cross-border cooperation between different AI entities, demonstrating the technical foundations of international AI collaboration frameworks.
Learn how to implement data governance controls in PostgreSQL to enforce AI agent behavior at the data layer, including role-based access control, row-level security, and audit logging.
Learn to build AI teammates that can autonomously execute workplace tasks using Python, web automation, and task queuing systems.
Learn to build a user-focused AI agent that prioritizes consumer needs over technical capabilities, demonstrating the shift toward accessible AI development.
Learn how to build a basic AI agent system that separates planning from execution using OpenAI models, mimicking the concept of cheaper models handling most coding while more capable models plan the work.
This article explains Meta's Astryx design system, an AI-ready React component library with 150+ accessible components, seven themes, and a CLI. It explores the technical architecture and implications for future development workflows.
Learn to build a control system for AI agents that monitors and limits their activities, similar to Runta's approach to 'parenting' AI agents.