AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces the cliff token, a token at which the estimated probability of reaching the correct answer (success probability) drops beyond an adaptive threshold, and introduces a cliff taxonomy of deterministic, uncertain, and sampled-off cliffs, defined by greedy choice and token entropy.
Harbor Adapters are developed that port more than 80 benchmarks to evaluate arbitrary agents, and validated through rigorous code review and parity experiments, and Harbor-Index is introduced, a curated set of 82 difficult, diverse, and high-quality tasks spanning 29 benchmarks to support more reliable and comprehensiv...
It is found that models generally learn more reliably from rules than from examples alone, and additional examples on top of rules or simply scaling up the number of examples do not lead to consistent and significant gains.
PGMem is a heterogeneous persona-memory graph that connects event and persona nodes through typed provenance and evidence edges, keeping each persona signal traceable to the events that support or revise it.
It is shown that AI generation leaves a consistent ``stylometric footprint'': a small subset of features, primarily entropy and lexical diversity, consistently separates AI-generated text from human writing across 8 LLMs and 5 domains, while the remaining features depend heavily on the domain and generator.
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