Principle 01
Often described as Kidlin's Law
Problem Clarity
A clearly stated problem is already partly solved.
Writing a problem clearly forces assumptions, constraints, people, and outcomes into view before a solution takes over the conversation.
What it means
Most difficult problems arrive as symptoms: too many manual steps, inconsistent output, slow decisions, or a vague sense that AI should help. A useful problem statement converts that discomfort into something observable.
Clarity does not produce the complete answer. It removes several wrong answers. Once the affected person, current behaviour, constraint, and desired change are explicit, the solution space becomes smaller and more useful.
Why it matters for AI
AI amplifies the brief
A vague prompt or product brief produces polished ambiguity. Clear inputs give people and models a shared target.
Tools stop leading
Teams can evaluate automation, agents, or a simple process change against the problem instead of choosing technology first.
Success becomes testable
A specific problem statement makes it possible to define what better looks like before anything is built.
Try it on a real problem
Start with three questions.
- 01
Who experiences the problem, and during which exact moment or workflow?
- 02
What happens today, and what evidence shows that it is a problem?
- 03
What should change if the problem is solved—and what must remain unchanged?
Put it into practice
Replace the solution sentence
Instead of “we need an AI support bot,” write: “Support leads spend two hours each day answering repeat order-status questions because customers cannot see reliable updates.” The second sentence gives a team several solutions to test—and a way to judge them.
The wording is commonly circulated as “Kidlin's Law,” although its precise origin is uncertain. We use it as a practical problem-framing heuristic, not a scientific law.
Where this shows up