When to Choose LangGraph: Precision Engineering

While LangChain is for speed, LangGraph is for Reliability. If you are building an agent that will manage money, update production databases, or handle sensitive customer data, you need the control that only a graph specialized for cycles can provide.

1. Complex State Requirements

If your agent needs to track more than just messages (e.g., a "Shopping Cart," a "Compliance Flag," or a "Recursion Counter"), LangGraph is the only logical choice.

• You can define a custom TypedDict for your state.
• Nodes can modify parts of that state without losing the rest.

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2. High-Stakes Reliability

In LangGraph, you define the "Walls" of the maze. The agent can think for itself, but it cannot jump over the walls.

• Example: You can force an agent to always go through a Security node before the Final Answer node. This is impossible to guarantee in a standard LangChain executor.

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3. Human-in-the-Loop (HITL)

If your app needs a "Review" step—where a human pauses the agent, edits a draft, and clicks "Resume"—LangGraph's persistence layer is built specifically for this. It is the "Gold Standard" for semi-autonomous systems.

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4. Visualizing the "Controlled Path"

graph TD
    Start --> NodeA[Tool Execution]
    NodeA --> NodeB[Safety Validator]
    NodeB --> Router{Secure?}
    Router -- No --> NodeA
    Router -- Yes --> NodeC[Human Approval]
    NodeC --> Final[Final State Persistence]

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5. Use Case Checklist for LangGraph

Should you use LangGraph? Yes, if:

• You have complex business logic (branching, looping).
• You need Human-in-the-Loop checkpoints.
• You are building for Production Use in an enterprise.
• Reliability is more important than development speed.

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Key Takeaways

• LangGraph is for Control and Predictability.
• It is the best framework for Long-running sessions (persistence).
• Its Explicit state management makes debugging infinitely easier.
• It is the mandatory choice for mission-critical agentic applications.