Lessons Learned Building LLM Apps
2025-01-21
This post summarizes lessons learned from building applications using Large Language Models (LLMs). LLMs excel at transforming large amounts of text into concise summaries; they struggle with generating more text than input or relying on their pre-trained data for complex reasoning. Effective LLM applications should provide the LLM with all necessary information, letting the LLM perform text condensation. The author advises against using LLMs for tasks requiring human expertise (e.g., medical diagnosis) and emphasizes that LLMs should augment, not replace, human workers. Avoid using LLMs for tasks that can be done with regular code.