Finding the edges of what you know means deliberately looking for the point where your understanding stops being reliable — the cases where your concept produces wrong predictions, the questions you cannot answer, the applications where the rule fails. This is the diagnostic that reveals where genuine learning is still needed. This concept covers boundary testing as a self-assessment practice in structured learning.
Boundary testing is a self-assessment technique where you actively probe the limits of your understanding by asking questions at progressively higher difficulty, abstraction, or novelty — deliberately pushing until you find where your knowledge breaks down. Knowing exactly where your understanding ends is far more valuable than vague confidence that you 'kind of get it.'
AI is an ideal boundary-testing partner because it can generate an infinite variety of edge cases, counterexamples, and increasingly difficult questions without repeating itself — turning a fuzzy sense of partial understanding into a precise map of what you actually know versus what you've only seen before.
After studying the French Revolution, prompt ChatGPT: 'Start asking me questions about this topic from easy to increasingly difficult and obscure. When I answer, probe whether I truly understand or am just pattern-matching. Keep going until I clearly can't answer accurately — then tell me exactly where my knowledge boundary is and what I should study next.'
Peri can explain this concept, give practical examples, help you decide whether it applies to your situation, or recommend a journey if appropriate.
Explore related journeys or tell Peri what you're working through.