Introduction to LangGraph: Build a Deep Research Agent — WalkSelf
4.7 (12) ⏱ 2h 54m 📚 29 lessons 🎧 Audio version

Introduction to LangGraph: Build a Deep Research Agent

Learn the fundamentals of Agentic AI by building a multi-agent planner-executor system to automate complex research tasks.

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About this course

As artificial intelligence evolves from answering simple queries to executing complex workflows, agentic AI is becoming an essential skill for modern developers. Understanding how to build autonomous systems that plan and execute tasks opens up entirely new possibilities for automation and data synthesis. In this text-based course, you will learn the foundational concepts of multi-agent systems and build your own deep research agent. Starting with basic terminology and core AI definitions, you will explore the planner-executor architecture and learn how to use LangGraph to orchestrate intelligent workflows that can autonomously gather, analyze, and summarize information. What you'll learn: - Understand the core terminology and concepts behind agentic AI and multi-agent systems. - Design a planner-executor architecture to break down complex research goals into manageable steps. - Apply LangGraph to orchestrate stateful, multi-actor applications and autonomous agents. - Integrate basic retrieval-augmented generation (RAG) patterns and vector databases for efficient data handling. - Practice prompt engineering techniques to guide agent reasoning and improve output reliability. - Build a complete, text-based deep research workflow that autonomously synthesizes information. The course flow begins with essential definitions and foundational AI concepts before moving into practical, step-by-step written exercises. You will progressively construct your agent's logic, learning how to manage state, structure workflows, and handle errors along the way. This foundational course is designed for beginners and developers new to AI agents; no prior experience with LangGraph or multi-agent orchestration is required. Start reading today to build your first autonomous research agent and expand your AI development skills.

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  • Short & focused
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Reviews (12)

Alexandros Kouris GR
★ 4 · July 30, 2026

Clear LangGraph intro, multi-agent parts move fast.

Sebastián Rodríguez MX Verified learner
★ 5 · July 23, 2026

Construir el agente planner-executor con LangGraph paso a paso me ayudó a entender por fin cómo se coordinan varios agentes en una sola tarea de investigación. El ejemplo final, donde el agente busca, sintetiza y refina su respuesta, quedó sorprendentemente sólido.

Hatice Şahin TR Verified learner
★ 5 · July 14, 2026

LangGraph ile planlayıcı-yürütücü yapısını sıfırdan kurmak, çok ajanlı sistemlerin nasıl çalıştığını sonunda anlamamı sağladı.

Alessandro Romano IT
★ 4 · July 13, 2026

Il modo in cui il corso spiega il flusso planner-executor con LangGraph è chiarissimo e passo dopo passo si arriva a un agente di ricerca funzionante. L'unica pecca è che la parte sui grafi ciclici avrebbe meritato qualche esempio in più.

Alejandro Valverde CR Verified learner
★ 5 · July 10, 2026

Por fin entendí cómo encadenar varios agentes para automatizar una investigación completa.

Trần Thị Quỳnh VN
★ 4 · June 29, 2026

Phần xây dựng agent lập kế hoạch và thực thi bằng LangGraph rất dễ hiểu, chỉ tiếc là đoạn về xử lý lỗi giữa các node hơi sơ sài.

Sofia Costa PT Verified learner
★ 5 · June 21, 2026

Explicação ótima do fluxo planner-executor.

박하은 KR Verified learner
★ 5 · June 19, 2026

LangGraph로 플래너-이그제큐터 구조를 처음부터 끝까지 만들어보는 과정이 정말 체계적이었습니다. 그동안 멀티 에이전트라는 개념이 막연했는데, 리서치 에이전트를 직접 조립하면서 각 노드가 어떤 역할을 하는지 명확하게 이해됐어요. 특히 상태 관리 부분을 그래프로 시각화해서 설명해준 덕분에 코드를 볼 때 헷갈리지 않았습니다. 마지막 프로젝트에서 제가 만든 에이전트가 스스로 검색하고 요약하는 걸 보고 꽤 뿌듯했습니다. 에이전트 오케스트레이션을 제대로 배우고 싶은 단계에서 딱 필요한 강의였어요.

Oliver Vidal CL Verified learner
★ 4 · June 19, 2026

Construir un agente de investigación con el patrón planificador-ejecutor me dejó las ideas mucho más claras, sobre todo cómo se reparten las tareas entre varios agentes. Me hubiera gustado un poco más de profundidad en el manejo de errores cuando un paso falla, pero aun así lo recomiendo sin dudar para entrar en LangGraph.

Léo Martin LU
★ 5 · June 16, 2026

La construction pas à pas de l'agent planner-executor avec LangGraph m'a enfin fait comprendre comment structurer un agent de recherche multi-étapes.

Léa Richard FR Verified learner
★ 5 · June 6, 2026

Le système planificateur-exécuteur est expliqué de façon limpide, j'ai monté mon premier agent de recherche sans galérer.

Paweł Grabowski PL Verified learner
★ 5 · May 28, 2026

Kurs bardzo dobrze tłumaczy architekturę planner-executor w LangGraph, krok po kroku, bez zbędnego lania wody. Zbudowałem własnego agenta do głębokich researchów i faktycznie działa lepiej niż wszystko, co pisałem wcześniej sam.

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