RAG Framework Selection: LangChain, LlamaIndex, Custom

RAG frameworks help early; production maturity often calls for custom or hybrid approaches.

What AI does well here

• Use frameworks for prototyping and learning RAG patterns
• Evaluate framework escape hatches before committing in production
• Build custom abstractions where framework abstractions don't fit
• Maintain familiarity with both frameworks and underlying primitives

What AI cannot do

• Get framework benefits without framework constraints
• Predict perfectly when migration will be needed
• Avoid the operational burden either way

Practice this safely

Use a small project example from your own work. The useful move is to compare the AI's draft against your goal, sources, and constraints before you trust it.

1. 1Ask AI to explain RAG frameworks in plain language, then underline anything that sounds uncertain or too broad.
2. 2Give it one detail from "RAG Framework Selection: LangChain, LlamaIndex, Custom" and ask for two possible next steps plus one reason each step might be wrong.
3. 3Check LangChain against a trusted source, teacher, adult, expert, or original document before you use it.