Iterative Refinement for Multi-Stop Itinerary Building

Iterative refinement is the process of progressively improving an AI-generated itinerary through a series of follow-up prompts, each adding constraints, corrections, or new preferences to the previous output. Rather than expecting a perfect plan from a single prompt, travelers build toward their ideal trip through structured conversation turns.

This technique matters because complex multi-stop trips involve too many variables to resolve at once, and AI performs significantly better when problems are broken into sequential steps. By refining one leg, budget layer, or activity type at a time, travelers produce itineraries that are far more accurate and personally relevant than those generated in a single exchange.