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A guide to sandboxing AI agents: why an autonomous agent needs its own disposable computer, and the isolation tech underneath.

Why the industry is shifting from handcrafted agentic workflows to agents operating inside harnesses, what that looks like in practice, and the trade-offs involved.

A complete overview of Model Context Protocol (MCP) and how it solves the M×N integration problem in AI development by creating a standardized interface between AI applications and external tools.

A tutorial on building an advanced agentic RAG workflow that combines query routing, document grading, and query rewriting using LangGraph to create a robust, self-correcting retrieval system.

A coding tutorial on building an agentic RAG workflow with a query router using LangGraph, enabling the system to intelligently choose between Wikipedia and web search retrievers based on query type.

Some thoughts on product defensibility for AI applications from my experience in the startup world.

A comprehensive introduction to agentic RAG, common design patterns, as well as a few example pipelines.

Announcing my first video course with O'Reilly—Building AI Agents with LangGraph! This course dives deep into AI agent design, action-taking, and multi-agent architectures using Python and OpenAI.

A brief look at the components of multi-agent frameworks and the current cutting edge options.

A deep dive into the process building a corrective RAG workflow using langgraph to handle scenarios where the documents retrieved from a vector database in a traditional RAG workflow are not relevant to answer a question.

This blog post guides you through the process of deploying StableLM models on AWS Sagemaker Endpoints, including creating a custom inference script and setting up the endpoint.