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Security Operations Centers (SOCs) are high-stress, time-critical environments in which analysts manage multiple concurrent tasks and depend heavily on both technical expertise and effective communication. This paper examines the integration of Large Language Model (LLM) technologies into an operational SOC using an anthropological, fieldwork-based approach. Over a six-month period, two computer science graduate researchers were embedded within a corporate SOC, guided by an internal advocate, to observe workflows and assess organizational responses to emerging technologies. We began with an initial demonstration of an LLM-based incident response tool, followed by sustained participant observation and fieldwork within the incident response and vulnerability management teams. Drawing on these insights, we co-developed and deployed an LLM-based SOC companion platform supporting root cause analysis, query construction, and asset discovery. Continued in-situ observation was used to evaluate its impact on analyst practices. Our findings show that anthropological and sociotechnical approaches, coupled with practitioner co-creation, can enable the nondisruptive introduction of LLM companion tools by closely aligning development with existing SOC workflows. 

Our expanding understanding of the brain at the level of neurons and synapses, and the level of cognitive phenomena such as language, leaves a formidable gap between these two scales. Here we introduce a computational system which promises to bridge this gap: the Assembly Calculus. It encompasses operations on assemblies of neurons, such as project, associate, and merge, which appear to be implicated in cognitive phenomena, and can be shown, analytically as well as through simulations, to be plausibly realizable at the level of neurons and synapses. We demonstrate the reach of this system by proposing a brain architecture for syntactic processing in the production of language, compatible with recent experimental results.