Scaffolding is a technique for breaking a complex task into smaller, more manageable steps that the AI can reason through using intermediate prompts, models, or agents. Rather than asking a model to solve a hard problem in a single step, scaffolding structures the problem so the model works through it progressively.
Each step in a scaffolded process is simpler and more reliable than trying to handle everything at once. The overall output is more accurate, more traceable, and easier to debug when something goes wrong. Scaffolding is the bridge between what a model can reliably do in a single step and what a complex business task actually requires.
