Real meal planning isn't about finding recipes—it's about satisfying dozens of competing constraints simultaneously: budget, allergies, available ingredients, cooking skills, time, and equipment. Treating planning as constraint satisfaction makes it explicit which limits matter most when tradeoffs are necessary.
Constraint satisfaction is a problem-solving approach where AI must find solutions that simultaneously meet multiple conditions, such as a meal plan that is gluten-free, nut-free, under 500 calories, and uses only ingredients you already own.
Understanding this concept helps you write better prompts because the more clearly you define each constraint upfront, the more accurately AI can generate meal plans that actually work for your household. Vague constraints produce vague results, while precise constraints produce precise, usable plans.
Peri can explain this concept, give practical examples, help you decide whether it applies to your situation, or recommend a journey if appropriate.
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