How AI Systems Work – Practical Foundations for Modern Learners
Lesson 3: Constraints, Rules, and Logic
Lesson Objectives
By the end of this lesson, students should be able to:
- Explain the difference between a hard constraint and a preference.
- Recognize how rules can improve or limit AI output.
- Use constraints to improve a prompt or decision process.
Lesson Content
A constraint is a limit the system must respect. A hard constraint is non-negotiable. A soft constraint is a preference. For example, "the meeting cannot happen before 10 AM" is hard. "Earlier in the day is better" is soft.
Rules and constraints are useful because they prevent nonsense answers. They also make tradeoffs visible. If a student asks AI to create a three-hour plan for a ten-hour task, the AI may compress too much unless the student states what must be preserved.
Logic is the habit of making statements clear enough to test. A statement like "this customer qualifies for the discount" should be tied to conditions. If the conditions are unclear, the answer becomes guesswork.
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