Thread
The "It Depends" Problem
Same instruction, opposite results. Specificity is the lever. Context redirects, not informs. The measurement itself was wrong.
Answered Constraints produce opposite effects depending on task type: a large effect on convergent tasks, harmful on exploratory ones. Negation alone is null; specificity provides the destination. The strongest specificity effect, once cited at 2.34, was three confounds stacked; honest magnitude is g=1.34.
Open Where exactly is the boundary between convergent and exploratory tasks? Domain experts can't distinguish specific from generic output on quality. Specificity changes form, not substance.
Why AI Defaults to Generic
Every prompt technique is one move: make the default path expensive enough that the model leaves it. Specificity is the largest measured version.
Same Technique, Opposite Results
The structured approach that produced precision on convergent problems actively harmed exploratory ones.
Why 'Don't Be Generic' Doesn't Work
Telling a model 'don't be generic' does nothing on its own; giving it specific anchors does. The gain is verifiability, not quality.
More Context Barely Helps
Adding information to an already-thorough prompt produced near zero improvement. Three constraint sentences changed everything.
The Most-Cited Finding Was Wrong
The most-cited effect across 90+ experiments was three effects stacked. Honest magnitude: 40% smaller.