A developer cut their large language model (LLM) costs by 81% without sacrificing product quality by identifying and addressing inefficiencies such as overusing expensive models, bloated system prompts, lack of caching, and poor RAG pipeline design. This highlights the need for developers to monitor and optimize LLM usage to control costs effectively.
Read the full article at Towards AI - Medium
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