Sangam Mukherjee

    Production AI Agents with JavaScript: LangChain & LangGraph

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    AI Agents · Online Course

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    Aspiring and seasoned JavaScript and TypeScript developers looking to transition into the cutting-edge field of artificial intelligence will find this comprehensive course by Sangam Mukherjee indispensable. The curriculum is specifically designed to bypass the Python-centric bias of AI development, offering a complete, production-grade pathway using LangChain.js and LangGraph.js. Throughout the course, learners explore how to architect stateful, multi-agent workflows that can reason, invoke external tools, and collaborate to solve complex business problems. By focusing on modern web standards, Zod schema validation, and JSON-first patterns, this training ensures that the agents you build are deterministic, reliable, and easy to debug. You will dive deep into building real-world applications, such as document-based chat systems utilizing Retrieval-Augmented Generation (RAG) and robust code-driven agents. Additionally, the course places heavy emphasis on the operational lifecycle, guiding you through monitoring, debugging, and tracing agentic pipelines using LangSmith and LangGraph Cloud. Integrated seamlessly with Next.js frontends, this course bridges the gap between raw AI models and user-facing SaaS platforms, making it the perfect choice for frontend and full-stack engineers seeking to build production-ready AI agent architectures.

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    Sangam Mukherjee

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    Sangam Mukherjee is a passionate software engineer and technical educator dedicated to empowering the global JavaScript community to build advanced AI-driven applications. Recognizing that while much of the artificial intelligence ecosystem has historically focused on Python, a massive contingent of web developers using JavaScript and TypeScript are eager to build sophisticated AI agents. Sangam bridges this gap by creating highly practical, production-focused educational content. His teaching methodology focuses heavily on hands-on project building, moving away from theoretical slides and directly into system design, state management, and orchestration. Through his deep-dive courses, Sangam guides developers through the complexities of frameworks like…Show more

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    Program Overview

    Online Course

    Learning format

    AI Agents

    Subcategory

    $39.99 (list $9.99)

    Price

    Price may change · updated within 1–2 weeks

    English

    Course language

    What You'll Learn

    • Architect stateful, multi-agent systems using LangGraph.js to manage complex business logic and agent collaboration in TypeScript.
    • Implement reliable tool calling and structured data extraction utilizing Zod schemas and JSON-first patterns for deterministic model outputs.
    • Build and optimize advanced Retrieval-Augmented Generation (RAG) pipelines for chatting with documents and custom knowledge bases.
    • Integrate AI agents with Next.js web applications to deliver real-time, interactive, and responsive user experiences.
    • Monitor, trace, and debug agentic workflows in real-time using LangSmith to identify latency bottlenecks and prompt inaccuracies.
    • Deploy production-ready agent services to the cloud using LangGraph Cloud and manage state persistence effectively.

    Best For

    • JavaScript and TypeScript developers who want to build AI agents without switching to Python.
    • Full-stack engineers looking to integrate sophisticated AI workflows into Next.js applications.
    • Developers interested in mastering stateful, multi-agent architectures for enterprise-grade automation.
    • Professionals seeking a structured approach to debugging and monitoring AI pipelines via LangSmith.

    Not For

    • Complete beginners to programming who lack a foundational understanding of JavaScript or TypeScript.
    • Developers looking for a course strictly focused on Python-based AI development or data science libraries.
    • Individuals seeking basic prompt engineering tips rather than advanced agentic workflow architecture.
    • Learners who require non-technical, high-level theory without hands-on coding or implementation practice.

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