Core Concepts
Zone of Proximal Development (ZPD)
Originally a psychological concept by Vygotsky, ZPD in AI describes the boundary between what a model can do unaided and what it can accomplish with scaffolding—such as few-shot examples, chain-of-thought prompting, or tool use.
Understanding ZPD helps practitioners design better prompts and fine-tuning strategies by identifying exactly where a model needs additional guidance to perform reliably.
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Related Terms
Techniques & Methods
Few-Shot Learning
Model's ability to generalize from only a handful of labeled examples.
Techniques & Methods
Chain-of-Thought
A prompting and reasoning technique in which a language model is encouraged to produce step-by-step intermediate reasoning before its final answer — empirically improving accuracy on multi-step problems, especially math, logic, and code.
Techniques & Methods
Prompt Engineering
The discipline of designing input text — instructions, examples, constraints, and context — to reliably steer a language model toward accurate, well-formatted, and intent-aligned outputs without modifying model weights.