System Prompts vs. Fine-Tuning: Are We Building Solutions for Problems That Don't Exist?

Is all the infrastructure around fine-tuning actually solving real problems, or are we chasing solutions looking for problems? In this episode, Corn and Herman dive deep into Daniel's question about system prompting versus fine-tuning in AI systems. They explore how system prompts actually work, why they're surprisingly effective, and whether the massive investment in fine-tuning platforms matches the real-world demand. Plus, they discuss how new tools like the Model Context Protocol might be changing the game entirely—and whether most companies even need to fine-tune at all.