Here’s a brief technical video covering two important concepts for making LLM API calls more reliable.

The first concept, a “Call-To-Truth,”, helps ensure the LLM understands that it should provide factual, reality-based responses. Without this, the model might generate incorrect or fictional information. This is prompt engineering.

The second concept is grounding the model in time by providing the current date. This becomes necessary when you want the LLM to respond accurately to recent events or time-sensitive topics.

In this video, I demonstrate both concepts with practical examples, and show how using the “Call-To-Truth” and providing the current date can improve response accuracy when making LLM API calls.