# Sajal Sharma > Internet home of Sajal Sharma — AI engineer and O'Reilly instructor specializing in agentic AI systems, LLMs, and machine learning. This site publishes long-form writing on agentic AI systems, LLMs, RAG, and machine learning engineering. Content is free to read and cite with attribution. ## Blog Posts - [Sandboxing an AI Agent](https://sajalsharma.com/posts/sandboxing-an-ai-agent/): A guide to sandboxing AI agents: why an autonomous agent needs its own disposable computer, and the isolation tech underneath. - [Agents Have Outgrown Workflows](https://sajalsharma.com/posts/agentic-workflows-to-agent-harnesses/): 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 Week with OpenClaw as My Personal Assistant](https://sajalsharma.com/posts/openclaw-experiments/): 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. - [2025: Career in Review](https://sajalsharma.com/posts/2025-career-in-review/): 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. - [Working Effectively with AI Coding Tools like Claude Code](https://sajalsharma.com/posts/effective-ai-coding/): 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. - [Adventures with Claude Code: Reflections on Building a Full-Stack System with AI Assisted Coding](https://sajalsharma.com/posts/adventures-claude-code/): 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. - [Understanding MCP: How the Model Context Protocol Solves AI's Integration Problem](https://sajalsharma.com/posts/understanding-mcp/): 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. - [Agentic RAG Series - Part 3: Building a Comprehensive Agentic RAG Workflow: Query Routing, Document Grading, and Query Rewriting](https://sajalsharma.com/posts/comprehensive-agentic-rag/): 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. - [Agentic RAG Series - Part 2: Building an Agentic RAG Workflow with Query Router Using LangGraph](https://sajalsharma.com/posts/agentic-rag-query-router-langgraph/): 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. - [What's the Moat? Product Defensibility for AI Applications](https://sajalsharma.com/posts/product-defensibility-ai-applications/): Some thoughts on product defensibility for AI applications from my experience in the startup world. - [Agentic RAG Series - Part 1: An Introduction to Agentic RAG](https://sajalsharma.com/posts/introduction-to-agentic-rag/): A comprehensive introduction to agentic RAG, common design patterns, as well as a few example pipelines. - [Guest Lecture at Yale: February 2025 - Agentic Systems with LangGraph](https://sajalsharma.com/posts/yale-guest-lecture-february-2025-ai-agents-langgraph/): Slides from my guest lecture at Yale for Generative AI & Entrepreneurship class (MGT 899). - [Building AI Agents with LangGraph: My First O'Reilly Course!](https://sajalsharma.com/posts/building-ai-agents-langgraph-oreilly/): 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. - [An Overview of Multi Agent Frameworks: Autogen, CrewAI and LangGraph](https://sajalsharma.com/posts/overview-multi-agent-frameworks/): A brief look at the components of multi-agent frameworks and the current cutting edge options. - [Building a Corrective RAG workflow with LangGraph](https://sajalsharma.com/posts/corrective-rag-langgraph/): 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. - [Deploy StableLM models on AWS Sagemaker Endpoints](https://sajalsharma.com/posts/deploy-stablelm-models-aws-sagemaker/): 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. - [Building an Image Classifier Really Fast Using Fastai](https://sajalsharma.com/posts/building-image-classifier-fastai/): In this post, I demonstrate how to quickly build an image classifier using the fastai library, a powerful tool for practical deep learning. The project involves classifying images of fruit as either rotten or fresh. - [Coding K-Means Clustering using Python and NumPy](https://sajalsharma.com/posts/coding-kmeans-clustering-python-numpy/): This post details the process of coding the K-Means Clustering algorithm from scratch using Python and NumPy. It's a great exercise for understanding the mechanics of this fundamental machine learning algorithm. ## Pages - [About](https://sajalsharma.com/about): About Sajal Sharma — background, experience, and work. - [Blog](https://sajalsharma.com/posts): All blog posts. - [Full content](https://sajalsharma.com/llms-full.txt): Every post's full text as markdown.