Broad prompt
Explain gravity.
What Is an LLM?
The prompt steers. The model predicts.
LLM stands for Large Language Model. At its core, an LLM is a prediction engine trained on large amounts of text. It learns statistical patterns: - how sentences are structured - how concepts relate - how explanations are commonly written - how instructions are usually followed When you provide a prompt, the model predicts a useful continuation of the text. It does not think like a person. It does not understand concepts the way humans do. Instead, it generates outputs based on learned language patterns. That is why prompts matter so much. Clear prompts create stronger behavioral guidance. Vague prompts leave more room for variation.
Prompt guidance matters
Guided prompt
Explain gravity to a 10-year-old in 2 short sentences.
The guided prompt produces more focused output because it reduces the range of what the prediction engine can plausibly generate.
LLMs generate outputs by predicting useful continuations based on patterns learned from text.
Practice
Run the prompt and observe the output. Then look at the LLM node settings — notice the model name and the temperature setting. Edit the prompt and run again. The model stays the same, but the output changes because the prompt changed.