Explores the evolution from simple, stateless AI agents (Agent 1.0) to advanced, deep agents (Agent 2.0) capable of complex, multi-step tasks.
Explores the concept of AI Agents, defining them and examining their role in the AI ecosystem, with references to LangChain and Anthropic.
Microsoft's new open-source Agent Framework combines AutoGen and Semantic Kernel for building intelligent, multi-agent AI applications.
A guide to building a basic AI agent framework that uses AI for planning and orchestrates reusable, atomic functions to interpret natural language requests.
A developer shares practical website optimization tips, including updating HTTP links, using AI agents, and cleaning up config files.
Introduces agent-rules, an open-source CLI tool that standardizes security and coding rules across AI coding assistants like GitHub Copilot and Cursor.
A guide to building an AI-powered system using the Mastra AI framework to automate and streamline the evaluation of conference Call for Papers (CFP) submissions.
Explains the concept of AI subagents, specialized agents for specific tasks, and their architecture using an orchestrator model.
Explores designing a multi-agent AI system by creating autonomous agents that play the word game Taboo, focusing on agent communication and orchestration.
Explores the role of Large Language Models (LLMs) in AI, covering major model families, providers, and concepts like hallucinations.
A proposed security evaluation framework for Model Context Protocol (MCP) servers, focusing on configuration and implementation risks for developers.
Analyzes AI's impact on software engineering, covering developer evolution, skill gaps, productivity myths, and the future of the profession.
A developer's personal reflection on the addictive nature of AI agentic engineering, the loss of work-life balance, and the industry-wide trend of extreme work hours in the AI space.
Explores how zero-trust environments like defense and finance can securely adopt AI using local-first agents and semi-autonomous workflows.
Part 2 of a guide on using Docker Compose to enhance the reliability and portability of AI agents, focusing on Dockerfile and compose.yaml.
A tutorial on using Docker Compose to create reproducible, containerized runtime environments for AI agents, focusing on a weather query example.
Explores key traits of AI-native products designed for efficient consumption by AI agents, focusing on context optimization and tool execution.
Explores implementing a 'human-in-the-loop' tool for AI agents using Python async and DSPy, enabling agents to ask users clarifying questions.
A developer's guide to building an 'AI in a Box' solution using Azure Foundry, Azure Functions, and Static Web Apps, grounded in a personal project.
A developer details building a modular, agentic Personal AI Infrastructure (PAI) system named Kai, focusing on the 'why' behind AI development.
