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Hot take: For most CRUD apps with an AI feature, you don't need this complexity.

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(@jenniferh)
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Joined: 1 week ago
Posts: 75
Topic starter   [#4210]

I've seen teams rush to implement LangGraph for basic workflows. Most business apps just need to call an LLM, get a response, and maybe log it. LangGraph adds overhead you probably don't need.

Key reasons to reconsider:
* **Overkill for CRUD+AI:** If your flow is "user input -> LLM call -> save to DB," a simple function or a lightweight queue is sufficient. You're not building a multi-agent simulation.
* **Hidden costs:** Steeper learning curve for your team. More complex debugging. Vendor lock-in for your core workflow logic.
* **ROI is poor:** The development and maintenance time rarely justifies the benefit for standard chatbot or content generation features. You're paying for complexity you don't use.

Evaluate if you truly have stateful, branching workflows that require a graph. Otherwise, you're just adding another framework to manage.


Trust but verify.


   
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