Conditional logic already suffices where LLMs still fail, as code agents avoid systematic failures

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Code agents operate on structured data with exact arithmetic, while LLMs must parse natural-language observations and track state across turns; some failures may partly reflect numerical parsing or working-memory limitationsclaim0.823
  discussion of potential confounds
• Two heuristic code agents outperform most tested LLMs, and behavioural traces surface recurring LLM failure modes including overbidding, self-bidding, bankrupt TC initiation, and weak opponent-state adaptation.quote0.821
  Abstract sentence summarising performance and failures.
• LLMs implicitly learn a distribution of 'consistent reasoning paths', and inconsistent reasoning forms statistical outliers with low probability under this distribution.hypothesis0.797
  Theoretical hypothesis about the mechanism underlying LLM error detection and reflection.
• Some failures may reflect prompt design rather than model limitations, though code agents avoid errors without promptsclaim0.786
  noted as a possible confound
• Temporal logic is too weak to express many important properties of programs.claim0.783
  Criticism of temporal logic as a verification tool.
• Where does reliable, goal-directed behavior come from in LLMs if it is not explicitly programmed?question0.775
  Opening motivating question that UCCT attempts to answer through semantic anchoring
• Behavioural traces surface recurring LLM failure modes including overbidding, self-bidding, bankrupt TC initiation, and weak opponent-state adaptation that never appear in code agents.claim0.766
  LLMs exhibit systematic errors that deterministic logic avoids.
• Two heuristic code agents outperform most tested LLMsclaim0.766
  author assertion that deterministic heuristics surpass many LLMs