How to handle long context windows vs. retrieval strategies?

Is RAG Dead?

Not yet. While context windows are growing (Gemini 1.5 Pro has 1M+), stuffing everything into context has downsides.

Trade-offs

• Cost: Long contexts are expensive to process every time.
• Latency: Time-to-first-token increases with context length.
• Accuracy: Models can struggle to find details buried in the middle of massive contexts ("Lost in the Middle").

Further reading

• Vector Databases & Embeddings
• GraphRAG & Advanced RAG Techniques
• Flagship LLMs in 2025