Weak-tier model deficits are not in task understanding but in protocol-level and procedural execution: they identify the right skill but cannot operate under it

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• Weak-tier models often fail to invoke relevant harness artifacts during task-solving, with Qwen3-32B showing a 25% load rate against ~96% for strong modelsclaim0.807
  Diagnosis of first failure mode explaining low harness-benefit for weak-tier models
• Even when the harness is loaded, weak-tier models fail to adhere to it due to weak instruction-following over long-horizon tasks, drifting more than four times more steeply than strong modelsclaim0.796
  Diagnosis of second failure mode explaining low harness-benefit for weak-tier models
• weak-tier models gain little, traced to two failure modes: failing to activate relevant harness artifacts and failing to follow them faithfully once activatedquote0.794
  Verbatim summary of weak-tier harness-benefit failure diagnosis from conclusion
• Cost-efficient models lack not individual skills but their reliable integration under competitive pressure.claim0.767
  Interpretation that the tested LLMs have the necessary subskills but cannot coordinate them in the adversarial game.
• Some failures may reflect prompt design rather than model limitations, but the underlying issue is one of reasoning rather than instruction-following.claim0.763
  Acknowledges the confound of not explicitly instructing models to track wealth, yet points to reasoning gaps given code agents avoid errors without prompts.
• Performance-optimized hierarchical models predict neural responses in higher visual cortex (Yamins et al., 2014)concept0.751
  Demonstrated CNN representations predict neurons in visual cortex; background motivation for neural-network-brain correspondence.
• Hypothesis 1 (Threshold Behavior): There exists a task-dependent threshold Sc such that performance exhibits sharp changes as S crosses Sc, with value and transition width depending on model, layer, and poolinghypothesis0.750
  Core testable hypothesis of UCCT about the nature of performance transitions under anchoring
• Models that are competent all represent data in a similar way; all strong models are alike, each weak model is weak in its own wayclaim0.749
  Author's interpretation of the VTAB alignment results echoing Tolstoy