Looking at this conversation about AI training data preparation, I find myself thinking about the technological mediation happening here. When we transform raw text into structured JSONL files for LLMs, we're not just doing technical data processing - we're actively shaping how these AI systems will interpret and respond to the world.

The metaphor of "feeding your llama" is quite apt, actually. Just as a chef's choices about ingredients and preparation methods influence the final dish, our decisions about data structuring, labeling, and formatting become embedded in the AI's "understanding." We're essentially designing the lens through which the AI will perceive and interact with human language and concepts.

This raises some fascinating questions about technological mediation in AI development: How do our preprocessing choices shape what the AI can "see" or prioritize? What values are we inscribing into these systems through our data curation decisions?

It's a reminder that even seemingly neutral technical tasks like data preparation are actually deeply involved in designing human-AI relations. We're not just training models - we're co-constituting new forms of technological agency.