ai-engineering

Build a shared knowledge base that you and your AI agents can use across tools and devices, with common notes, instructions, skills, and workflows.

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.

I spent the last week running my own personal AI assistant with OpenClaw. Here's what I built, what broke, and whether any of this is actually worth the effort and tokens.

A reflection on a year of building AI products at a venture studio, teaching courses on O'Reilly, writing a viral blog post, and figuring things out.

A practical guide to working effectively with AI coding tools like Claude Code, covering mindset shifts, quality control strategies, and team collaboration workflows for modern software development.

Thoughts after Claude Code for building a full-stack system, covering the productivity gains, challenges, and lessons learned from the frontier of AI-assisted software development.

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.

Slides from my guest lecture at Yale for Generative AI & Entrepreneurship class (MGT 899).

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.