Avoid asking factual questions
The LLM is not a database of facts. Historical events, dates, places are not stored as exact references. LLMs generate their response based on statistical probabilities derived from patterns.
The more widely documented something is, the better the LLM knows it
The LLM's training is roughly proportional to the representation of the information on the Internet. An LLM is more reliable and detailed when discussing common knowledge.
Precise questions using relevant jargon with context yields useful output
Poorly worded questions that do not use domain-specific terminology are less likely to produce clear answers.
Do not trust citations
The LLM does not have citations hard-coded into the network. Citations are most likely to be hallucinations
Decompose complex tasks and questions into a sequence of iterative prompts
There is a limited amount of "thinking" by the LLM per prompt, so simpler tasks are more likely to produce relevant answers.
Structure your question to produce a page or less of output
Producing a 200 page book from a single prompt devolves into hallucinations after a few pages. Shorter answers are more likely to remain lucid, so phrase your question in a way that can be answered with a small amount of text.
LLMs default to the average
While LLM output can be creative (in unexpected ways), seeking exceptional insight yields the mundane
Simplify your question to a one-shot prompt
Iterative questions are more likely to yield hallucinations
Delegation to an intern who doesn't learn
This can be confusing, as the LLM occasionally knows more than you do.
