
In this episode, we sit down with Dr. Jessica Cervi, a Learning Facilitator and Subject Matter Expert on AI for MIT xPRO. She'll walk us through harness engineering, an approach focused on building the environment an AI agent operates inside rather than just the instructions you hand it. Jessica breaks down how harness engineering differs from prompt and context engineering, why guardrails and evaluation are the two load-bearing pillars of the whole thing, and how using a more powerful model as a judge can catch the failures you would otherwise ship straight to your learners. We also dig into the tradeoff every builder runs into eventually: how much freedom to give an agent, and when the stakes of a task should pull you back toward tighter control.
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