What is Few-Shot Prompting?
Showing the model two or more input-output examples inside the prompt so it imitates the pattern. Examples beat paragraphs of instruction for format, tone, and edge-case handling in builder and support tasks.
Related terms
System Prompt
The persistent instruction block prepended to every request that sets role, rules, and output format. It outranks user text in well-built stacks, which is why builders version it like code, not copy.
Chain of Thought
Asking the model to reason step by step before giving the final answer, which raises accuracy on math, planning, and debugging. Keep the reasoning in thinking tokens and return only the conclusion to users.
Evals
Repeatable tests that score model behavior on fixed cases before and after prompt or model changes. Without evals every tweak is a guess; with them, regressions in tone, accuracy, or format get caught early.
Temperature
Sampling randomness for generation: low values make output focused and repeatable, high values make it varied and surprising. BYOB chat configs default near 0.5 while tool calls use 0.3 for steadier structured actions.
Thinking Budget
The token allowance reserved for internal model reasoning before answering. Larger budgets suit hard multi-step problems; BYOB prices thinking tokens separately so runaway reasoning shows up in metering.
Structured Output
Forcing model replies into a machine-readable shape such as JSON with fixed fields. Required wherever AI output feeds code, databases, or UI components, since free text breaks parsers the moment formatting drifts.