TOON: “JSON for AI” (is it any good?)

Summary

The transcript explores JSON prompting, a technique for improving language model interactions by using structured data formats like JSON and Tune to potentially enhance instruction following and reduce token count. The discussion centers on comparing different data formats (paragraph, YAML, JSON, Tune) and their token efficiency when communicating with AI models, revealing surprising insights about how these formats are processed. The key takeaway is that while JSON prompting seems promising, it may not always result in the expected token reduction, and alternative approaches like Tune are emerging to address these challenges in AI model communication.