Step-by-step tutorials to master AI tools effectively.
24 ARTICLES
24 ARTICLES IN HOW-TO
Discover the incredible story of Mohammed Ismail, who used Google Gemini and Google Maps to find a childhood friend after 31 years. Learn how personal AI utility is transforming the way we search for people and locations across decades.
Discover the shift from conversational chatbots to headless AI agents. This guide explores how to leverage Codex for programmable automation and advanced developer tools to streamline your workflows.
Industry leaders like Andrew Ng are defining structured workflows for coding agents—moving beyond rapid, experimental 'vibe-coding' toward rigorous planning, execution, and monitoring to prevent technical debt.
Learn how to build a robust Hybrid AI architecture by combining local LLMs for data privacy with cloud models for complex reasoning. This guide explores cost optimization and scaling strategies for modern enterprises.
Move beyond basic prompting to master advanced context engineering. This guide explores the five core components of functional AI agents, from LLM reasoning engines to system instruction playbooks.
Learn how to build and secure complex multi-agent systems using LangGraph and Codex subagents. This tutorial covers essential security protocols and human-in-the-loop workflows for modern agentic AI applications.
Basic RAG systems often struggle with complex enterprise documents. This guide explains how to use rerankers and knowledge graphs to improve retrieval accuracy for legal and financial professionals.
Discover how agentic AI features in Google Maps can automate your travel planning and daily tasks. This guide shows you how to book hotels and find events using simple natural language commands.
Stop relying on 'vibes' for AI development. Learn how Eval-Driven Development serves as the new PRD, ensuring your AI products are reliable, safe, and ready for production-scale deployment.
Transform your static developer portfolio into a dynamic, queryable asset using the Model Context Protocol (MCP). This guide shows you how to connect your projects to AI assistants like Claude Desktop, allowing recruiters and agents to interact with your work in real-time.
AI hallucinations and stale data can damage enterprise reputation. This guide explores how the Agentic Context Layer solves systemic drift, providing a framework for real-time data consistency and reliable AI performance.
Streamline your Google Workspace workflows by integrating the Model Context Protocol (MCP). This guide covers setting up OAuth credentials and configuring the mcp-gee-sweet server to enable secure AI-driven automation.