Make your constraints explicit before solving
Write out every assumption and rule you are treating as fixed — most problem-solvers carry invisible constraints they never surface.
Key takeaways
- What it is: Write out every assumption and rule you are treating as fixed — most problem-solvers carry invisible constraints they never surface.
- Why it works: Implicit constraints operate automatically; they shape the solution search without ever being consciously examined. Making them explicit moves them from procedural to declarative memory, where they can be evaluated and challenged. Research on representational change shows that insight is often triggered not by adding new information but by recognizing that an assumed constraint is not actually required by the problem.
- Evidence: Backed by observational / correlational evidence.
- Avoid: Listing only practical constraints (time, money) and missing the deeper representational ones: what counts as a valid solution, who is allowed to be involved, what domain the solution must come from.
Why it works
Implicit constraints operate automatically; they shape the solution search without ever being consciously examined. Making them explicit moves them from procedural to declarative memory, where they can be evaluated and challenged. Research on representational change shows that insight is often triggered not by adding new information but by recognizing that an assumed constraint is not actually required by the problem.
How to do it
- 1Write your problem statement at the top of a page.
- 2For 5 minutes, list every rule, assumption, boundary, and "it must be this way" you are taking for granted.
- 3For each, write: "Is this constraint stated explicitly in the problem, or am I assuming it?"
- 4Circle every assumed constraint — those are your first candidates for relaxation.
What the evidence says
ObservationalRepresentational change theory (Ohlsson, 1992) and Knoblich et al.’s (1999) experimental work on matchstick algebra problems showed that the difficulty of insight problems correlates with the tightness of the constraints subjects imposed on their representations.
Honest caveat: Most experimental evidence uses controlled insight puzzles (matchsticks, remote associates); how much the effect size transfers to open-ended real-world problems is not precisely established.
- — Knoblich et al. (1999), constraint relaxation and chunk decomposition in insight problem solving, Journal of Experimental Psychology: Learning, Memory, and Cognition
- — Ohlsson (1992), Information-processing explanations of insight and related phenomena
Common mistake
Listing only practical constraints (time, money) and missing the deeper representational ones: what counts as a valid solution, who is allowed to be involved, what domain the solution must come from.
IX Coach walks you through a systematic constraint audit at the start of a stuck problem, surfacing the assumptions that are narrowing your search before you invest effort in solutions.
Practice this with IX Coach →