Reference
Prompt Engineering Glossary
Every term you need, with working example prompts and practical notes on when each technique earns its keep.
14 terms in Techniques
Chain-of-Thought (CoT)
Prompting the model to produce intermediate reasoning steps before its final answer, improving accuracy on multi-step problems.
TechniquesFew-Shot Prompting
Including 1-5 worked examples of the desired input/output pattern in the prompt so the model can infer the task format and style.
TechniquesIn-Context Learning (ICL)
The capability of a pretrained LLM to learn a task at inference time from examples provided in the prompt -- no weight updates, no fine-tuning.
TechniquesMeta-Prompting
Using a language model to write or improve prompts that another model (or the same one) will execute -- treating prompt engineering itself as a prompt engineering task.
TechniquesNegative Prompting
Explicitly stating what the model should NOT do, NOT include, or NOT sound like -- in addition to (or instead of) describing the desired output.
TechniquesPrompt Chaining
Splitting a complex task into a sequence of smaller prompts where each step's output feeds the next -- versus asking one mega-prompt to do everything.
TechniquesPrompt Decomposition
Identifying the sub-problems inside a single prompt and addressing each explicitly -- in one prompt -- rather than asking the model to figure out the structure itself.
TechniquesRole Prompting
Assigning the model a concrete professional role (e.g. "senior security engineer", "copy editor") to shape its framing, vocabulary, and priorities -- distinct from broader persona prompting.
TechniquesSelf-Consistency
Generating N independent answers to the same prompt (with temperature > 0) and picking the majority answer -- trading compute for reliability.
TechniquesStep-Back Prompting
Before answering a specific question, asking the model to derive the general principle or high-level abstraction that the question falls under -- then using that principle to answer.
TechniquesStructured Output
Constraining a model to produce JSON, XML, or other machine-parseable output conforming to a schema -- so downstream code can consume it reliably.
TechniquesSystem Prompt
The high-priority, typically hidden instruction that sets a model's persona, rules, and constraints for an entire conversation.
TechniquesTree of Thoughts (ToT)
A prompting strategy where the model explores multiple reasoning branches, evaluates each, and selects (or combines) the best -- versus linear chain-of-thought which commits to one path.
TechniquesZero-Shot Prompting
Asking a model to perform a task with no examples of the expected output -- relying entirely on the instruction and the model's pretrained knowledge.