Running projects for AI features

The text discusses the process of running projects for AI heavy features. It highlights an experimental approach, starting with a proof of concept, early dogfooding, prompt refinement, and establishing a feedback loop to improve the feature. The author emphasizes the importance of understanding the capabilities of LLMs like OpenAI's GPTs and adjusting approaches accordingly. They also mention the need to know when to stop refining prompts and focus on customer feedback for continuous improvement.

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