Premature Closure
The LLM commits to a confident answer before processing all constraints, characteristic of constraint-heavy tasks where it fills in plausible answers fast and gets cross-constraint interactions wrong.
Problem
The model commits early to per-clue / per-step answers that are individually plausible but jointly incoherent. By the time later constraints are processed the commitment is already made. Reviewing the trace shows the model knew the constraints but didn't gate generation on them. Result: confident wrong answers, not 'I don't know' wrong answers.
Solution
Pair with: large-reasoning-model-paradigm (route to LRM), strategic-preparation-phase (force constraint enumeration before generation), generate-and-test-strategy (separate generate from verify). Detect premature-closure-prone tasks by load (constraint-heavy, multi-step, math).
When to use
- Never. Cite when reviewing tasks routed to fast LLMs that should be routed to LRMs.
- Always pair detection with one of the three resolution patterns.
- Surface as a known failure mode in agent design docs.
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