Explores the critical but underdeveloped components of Agent-to-Agent (A2A) protocols: dynamic discovery, naming, and resolution for scalable AI agent ecosystems.
A developer documents how AI agents built a complete shopping cart feature for an e-commerce app, from requirements to code, without manual programming.
A tutorial on building a multi-agent AI system with specialized agents using IBM's Watsonx Orchestrate platform and Docker.
Peekaboo 2.0 is a fast macOS screenshot tool for AI agents, now available as a CLI to avoid MCP context bloat and enable on-demand use.
A guide to adding long-term memory to a Gemini 2.5 chatbot using the Mem0 library and vector databases for personalized AI interactions.
A tutorial on building an AI agent with Watsonx.ai and integrating it using the Model Context Protocol (MCP) Gateway for seamless tool communication.
Explains why Context Engineering, not just prompt crafting, is the key skill for building effective AI agents and systems.
A guide to building configurable, collaborative AI agents using the OpenAI Agents SDK, covering agent factories, tool registries, and collaboration patterns.
Explores the trade-offs between single-agent and multi-agent AI systems, discussing their characteristics, pros, and cons for different tasks.
AI agents' autonomous and probabilistic nature forces stricter security and authorization models, breaking traditional microservice assumptions.
Explores building AI Agents as streaming SQL queries using platforms like Apache Flink for improved consistency, scalability, and developer experience.
Explores building AI Agents as streaming SQL queries using platforms like Apache Flink for improved consistency, scalability, and developer experience.
Explores the challenges of delegating authority to AI agents due to fragmented user identities and ungoverned authorization systems in enterprises.
llm.codes converts JavaScript-heavy Apple and other developer docs into clean Markdown that AI agents can read, solving a key problem for AI-assisted coding.
An overview of Generative AI and an introduction to building AI agents using Python and the LangGraph library.
Introduces Peekaboo MCP, a macOS tool that enables AI agents to capture screenshots and perform visual question answering using local or cloud vision models.
Introducing hinbox, an AI-powered tool for extracting and organizing entities from historical documents to build structured research databases.
Explores common design patterns for building AI agents and workflows, discussing when to use them and how to implement core concepts.
Explains how Sampling and Prompts in the Model Context Protocol (MCP) enable smarter, safer, and more controlled AI agent workflows.
Explains how Tools in the Model Context Protocol (MCP) enable LLMs to execute actions like running commands or calling APIs, moving beyond just reading data.
