Module 08 LangChain and LangGraph - akash-coded/aws-bedrock-agentcore-strands GitHub Wiki

๐Ÿฆœ Module 08 ยท LangChain and LangGraph

The other ecosystem โ€” and an honest side-by-side with Strands.

Module 08 of 16 ยท track Build ยท Estimated time: 7โ€“8 hours ยท Prerequisites: Module 05. Module 06 recommended.

LangChain is the framework you will meet in most existing codebases. This module builds it up from first principles โ€” why it exists, what it actually does โ€” then puts it directly against Strands so you can choose with evidence rather than allegiance.

Open the module on GitHub โ†—: the slides, notebooks, exercises and solutions are there. This page is the reading order, with the tutorial and the workbench alongside.

Read first, on the site

The lesson that frames this module is How AI-DLC, BMAD, Spec Kit and Scrum Fit One Lifecycle (7 min): why the framework changes and the lifecycle does not.

What you will be able to do

  • Explain what LangChain abstracts and why chains exist at all
  • Build chains, tools, memory and structured output in LangChain
  • Model a stateful workflow as a LangGraph graph
  • Compare LangChain and Strands on the same task and justify a choice

Concepts in this module

Portable GenAI concepts AWS-specific surface
Chains and composition langchain-aws
Runnables Bedrock as a LangChain provider
Structured output LangGraph on Bedrock
Graph state machines
Middleware

Portable concepts transfer to any stack. The AWS column is where this module touches the cloud โ€” see docs/concepts/portability-matrix.md.

Run it in this order

# Step What it is
1 ๐Ÿ“– slides/LangChain-from-Zero.pptx LangChain from zero
2 ๐Ÿ’ป notebooks/01_why_langchain_context_and_history.ipynb Why LangChain โ€” context and history
3 ๐Ÿ’ป notebooks/02_essentials_how_langchain_works.ipynb How LangChain actually works
4 โœ๏ธ exercises/exercise_1_foundations.md Exercise 1 โ€” foundations
5 ๐Ÿ’ป notebooks/03_basic_langchain.ipynb Basic LangChain
6 โœ๏ธ exercises/exercise_2_tools.md Exercise 2 โ€” tools
7 ๐Ÿ’ป notebooks/04_intermediate_langchain.ipynb Intermediate
8 โœ๏ธ exercises/exercise_3_memory_and_structured_output.md Exercise 3 โ€” memory and structured output
9 ๐Ÿ’ป notebooks/05_advanced_langchain.ipynb Advanced
10 โœ๏ธ exercises/exercise_4_middleware_and_graphs.md Exercise 4 โ€” middleware and graphs
11 ๐Ÿ’ป notebooks/PierPoint_LangGraph_Chains_to_Swarms.ipynb LangGraph: chains to swarms
12 ๐Ÿ’ป notebooks/06_langchain_vs_strands_side_by_side.ipynb LangChain vs Strands, side by side
13 โœ๏ธ exercises/exercise_5_multiagent_capstone.md Exercise 5 โ€” multi-agent capstone

๐Ÿ“– read   ๐Ÿ’ป run   โœ๏ธ practise   ๐Ÿ“Š workbook   ๐Ÿ”– reference

Worked solutions live in solutions/. Attempt every exercise closed-book first โ€” the solutions are written to be read after you have a wrong answer to compare against.

Common mistakes

  • Cargo-culting chains. If a function would do, use a function.
  • LangGraph state that grows without bound โ€” checkpointing is not free.

When it breaks

Every error anyone has hit in this course is in the Error Index, by the exact string. Model access and region problems are in Model and Region Notes. If it is a question rather than an error, check the answered ones first, then ask in Q&A.

Field guide for this module

Frameworks

Quick reference

Recipes and procedures


โ† Module 07 ยท Multi-Agent Patterns with Strands ยท All modules ยท Module 09 ยท LLM Memory Mechanics โ†’

โœ๏ธ This page is generated from modules/08-langchain-and-langgraph/README.md. To change it, edit the module README: an edit made here is replaced at the next sync.

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