Tutorial Series

A 7-part developer's guide to LangGraph — from the core building blocks (State, Nodes, Edges, reducers) through tool-using agents, multi-agent architectures, human-in-the-loop patterns, and production persistence, finishing with a full business playbook covering operations, cost, hallucination mitigation, security, and a final decision framework for when LangGraph is — and isn't — the right choice.

A comprehensive 18-part developer's guide to building, testing, and shipping production AI agents with Google Agent Development Kit (ADK) 2.0 and Gemini — covering graph workflow runtimes, multi-agent coordination, Task API delegation, Human-in-the-Loop gates, token economics, evaluation suites, MCP integrations, multi-provider model routing, pre-flight token budgeting, cross-provider TCO comparison, and self-hosted native deployment.

A comprehensive 13-part developer's guide to mastering LLM application architecture with the Gemini API — covering API fundamentals, multi-turn state, sampling controls, evaluations, structured prompting, function calling, guaranteed JSON schemas, extraction pipelines, autonomous agentic loops, resilient error conventions, production toolsets, multi-agent coordination, and end-to-end customer support agents.

A comprehensive 6-part developer's guide to building production-grade deep agents using LangChain — featuring planning, persistent tool-calling harnesses, subagent delegation, context engineering, SQLite checkpointers, and domain-specific customization.

A comprehensive 4-part series on architecting, building, scaling, and governing autonomous AI agents in production using frameworks like LangGraph.