Agentic behavior is encoded as a default operating mode rather than a dormant direction waiting to be activated

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

• Agentic behavior in LLMsconcept0.751
  Nine traits characterizing LLM-as-agent deployments; all nine are natural in both models
• Agentic methods incur context-switching latency from external execution.claim0.729
  Identifies a key limitation of agentic methods.
• "In active inference a policy is simply a sequence of choices for actions through time"quote0.729
  Definition of sequential policy in active inference, contrasting with state-action policies in RL.
• 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.claim0.723
  LLMs exhibit systematic errors that deterministic logic avoids.
• The assumption that the Assistant persona corresponds to a linear direction in activation space is likely flawed; some information may be represented nonlinearly or encoded in weights rather than activationsclaim0.723
  Limitation acknowledgment about the adequacy of the linear representation assumption
• Detecting dormant behavioral changes requires evaluating across all possible contexts, which is infeasible in practiceclaim0.719
  Practical limitation of current evaluation methods for pernicious divergence
• Agentic self-evaluation and self-steering may scale to broadly interpret and understand internal representations and SAE features.claim0.719
  Forward-looking claim about the potential of model introspection as an interpretability tool
• Behavior-Optimized Activation Path Recoverymethod0.719
  Method of optimizing activation-space interventions to produce behavioral paths along M_y, then measuring whether the resulting activation trajectories trace M_h curvature