protologue

pro·to·logue noun

  1. In biological nomenclature, the original description published together with a new name, against which every later use of that name is checked.
  2. This site: the reference record for 101 prompting and large language model techniques, each with a short citable definition, its relations to other techniques, and the paper that introduced it.

Foundations

Core concepts of prompting — the parts of a prompt, how models consume it, and the basic zero-shot and few-shot paradigms.

Exemplars & In-Context Learning

How demonstrations inside a prompt are chosen, ordered, scaled, and calibrated, and what they actually teach the model.

Reasoning Elicitation

Techniques that get a model to produce intermediate reasoning, decompose problems, or explore multiple solution paths before answering.

Self-Critique & Verification

Techniques in which a model, or a set of models, checks, critiques, votes on, or revises outputs.

Retrieval & Tool Use

Grounding generation in external information and letting models call functions, search, and other tools.

Agents & Orchestration

Patterns for composing multiple model calls, tools, and memory into workflows and autonomous agents.

Prompt Optimization

Automatic and learned methods that search for, compress, or train better prompts.

Reasoning Models & Test-Time Compute

Models trained to reason at length, and methods that improve answers by spending more computation at inference time.

Security & Adversarial Prompting

Attacks that subvert a model's instructions and the defenses designed to resist them.

Failure Modes & Evaluation

Systematic ways prompted models go wrong, and the evaluations used to measure them.