A. creating a new database schema

B. integrating a new API

C. reducing manual code documentation

D. identifying flaws and improving design

A. to orchestrate interactions with servers

B. to act as an LLM for inferencing

C. to act as a tool or service provider

D. to provide resources for task execution

A. defining a persona

B. stating the purpose

C. using few-shot

D. describing the situation

A. It provides instructions for desired action.

B. It reduces the total token usage.

C. It provides a pattern to emulate.

D. It guides the tone and vocabulary.

A. insecure supply chain

B. direct injection

C. data poisoning

D. model drifting

A. chain-of-thought

B. metaprompting

C. zero-shot prompting

D. few-shot prompting

A. large language models

B. generative adversarial networks

C. diffusion models

D. variational autoencoders

A. by switching to an algorithm that reduces the character-to-token ratio

B. by increasing the context window size to reduce the total number of API calls

C. by automatically switching to a lower-cost model as the conversation history grows

D. by capping the cumulative number of input tokens sent with each new prompt