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Methodological module

TRIZ contradiction resolution

The constraints conflict, so we are looking for a way to resolve rather than split the difference.

When it helps
Use it when improving one important property appears to damage another: speed versus quality, reach versus privacy, simplicity versus control.
Origin
TRIZ · contradiction resolution and ideal final result

What this module does

TRIZ treats a contradiction as useful design information. Instead of accepting a compromise, you describe what must improve and what becomes worse, then look for a change that separates or removes the conflict.

How to use it

  1. Name the desired improvement.
  2. Name what gets worse when you pursue it.
  3. Write the contradiction in one sentence.
  4. Describe the ideal final result without explaining how.
  5. Separate the conflict in time, space, conditions, or responsibility.
  6. Turn the strongest move into a small experiment.

Practical example

Situation

A support team wants faster replies without lowering answer quality.

Result

Instead of averaging both goals, it separates work by conditions: instant structured acknowledgement, then a specialist answer only for cases that need judgment.

Limitations

  1. This is a compact contradiction exercise, not the full ARIZ process.
  2. It needs a concrete conflict; vague aspirations produce slogans.
  3. Some constraints are real and require an explicit trade-off after alternatives are explored.

Standalone template

Copy these prompts and work through them without Selecton.

I want to improve: …

But then this gets worse: …

Contradiction: we need … and …

Ideal final result: … without …

Separation moves: time / space / condition / role

Smallest test: …

How it fits into Selecton

The app keeps a reliable five-stage baseline and now adds an adaptive-methods-v1 layer: typed method cards can be selected automatically or received as an explicit lens from a method page. Full non-linear routing and effectiveness measurement remain under evaluation.

Auto, adaptation, and combinations

The intended Auto mode selects one primary method for the next useful move, based on the state of the decision. A route may use different modules in sequence—for example GROW to clarify a goal, weighted criteria to compare options, then a pre-mortem to test the plan. They are not blended into an opaque prompt: every transition should remain explainable and reversible to the baseline route.