Generative AI with JavaScript & TypeScript: A Practical Developer's Guide to LLMs, Prompt Engineering, RAG, AI Agents, Tool Calling, LangChain, LangGraph, MCP, and Production AI Applications - Softcover

Pandey, Garima

9798194609130: Generative AI with JavaScript & TypeScript: A Practical Developer's Guide to LLMs, Prompt Engineering, RAG, AI Agents, Tool Calling, LangChain, LangGraph, MCP, and Production AI Applications

Softcover

ISBN 13: 9798194609130

Publisher: Independently published, 2026

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Unlock the Power of Generative AI Using Your Existing JavaScript & TypeScript Skills!

If you are a JavaScript or TypeScript developer, you don't need to learn Python or machine learning mathematics to build modern AI applications. Generative AI with JavaScript & TypeScript delivers a clear, pragmatic engineering roadmap for software developers who want to move past simple API demos and build production-ready AI features.

Authored by experienced software developer Garima Pandey, this book guides you step-by-step through building 10 real-world projects—from streaming API clients and Zod-validated structured outputs to vector database RAG pipelines, stateful LangGraph agent workflows, and Model Context Protocol (MCP) tool integrations.

What You Will Learn:

LLM Fundamentals: Tokenization, context windows, sampling parameters (temperature, top_p), and message roles.
Type-Safe AI Applications: Building resilient Node.js & TypeScript integrations with Zod schemas and retry handlers.
Prompt & Context Engineering: Grounding AI responses, decomposing prompts, and defending against prompt injection.
Real-Time Streaming & Memory: Server-Sent Events (SSE) chatbots, sliding window sessions, and database-backed persistent user memory.
Tool Calling: Giving AI models the ability to execute application functions and external APIs safely.
Retrieval-Augmented Generation (RAG): Building vector search pipelines with Pinecone, parent-child chunking, hybrid search, and re-ranking.
AI Agents & Workflows: ReAct agent loops, LangChain.js, and stateful cyclic graphs with LangGraph.js and human-in-the-loop approvals.
Model Context Protocol (MCP): Interoperating with standardized MCP tool servers using @modelcontextprotocol/sdk.
Production Engineering: Golden dataset evaluations, LangSmith telemetry, token cost optimization, and OWASP AI Security guardrails.