{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/379a3c6f9a2140cd8c5c8569ee7908e1\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/379a3c6f9a2140cd8c5c8569ee7908e1-56a7a663e8908d46.gif","duration":304.935,"title":"1 - LLM Fundamentals","description":"Today, I delve into the world of Code.ai use cases and how to leverage Kodi for effective prompting and context selection strategies. We aim to help users grasp the nuances of these strategies and their adaptability based on the task at hand. Join me as we explore large language model fundamentals, Kodi context retrieval, and a framework for categorizing tasks. Action: Understand and apply these strategies in your projects."}