Prompt Engineering
Designing and iterating on prompts to get reliable output — closer to spec-writing than to magic words.
Prompt engineering is the practice of stating the task, audience, format, and constraints precisely enough that a model can succeed. The reliable levers are specificity, examples, explicit output format, and giving the model the context it lacks. Most ’the model can’t do this’ problems turn out to be underspecified prompts.
In practice: Adding two example outputs cuts format errors more than any adjective ever will.
Where this comes up
- 20 Best AI Tools for Accounting & Finance in 2026: Review and Comparison of Pros & Cons, Key Features and Pricing
- AI Course for Fitness Coaches: Elevate Your Coaching Skills
- AI Course for Virtual Assistants: Enhance Your Skills and Efficiency
- AI Courses for Beginners in 2026: Start Learning With No Experience
- AI Learning Apps with Daily Reminders: Your Guide to Effective Learning
- AI for Customer Success in 2026: Training, Workflows, Prompts, and What Teams Should Automate Carefully