Intent Engineering

Intent engineering goes beyond crafting good prompts: it ensures the AI interprets user goals correctly and produces outputs that match business needs. Practitioners design prompts, workflows, and feedback loops so the AI understands intent (what the user wants) rather than just following literal instructions. When to use intent engineering: Build customer-facing AI that must handle ambiguous requests, design agentic workflows that chain multiple steps toward a goal, or align AI outputs with specific business KPIs. Common mistakes: Assuming the model will infer intent from vague prompts, neglecting to validate outputs against actual user satisfaction, or designing for edge cases while missing the most common intents.