What this Grid covers
AIGrid is about applied AI in IT and security operations, written from the perspective of someone who has to run the systems afterward. LLM augmentation of analyst workflows, AIOps for noise reduction, SOAR playbooks, anomaly detection, and the narrower but more useful class of machine-learning features embedded in the tools we already use.
The editorial angle is skeptical in the useful sense: AI has real leverage in triage, summarization, correlation, and code generation, but the vendor pitch routinely overstates autonomy and understates the operational cost of keeping these systems honest. Posts here try to name the specific places AI earns its keep — and the specific places it creates new categories of risk and toil.
Expect reality checks, use-case write-ups, notes on model selection for ops work, prompt-engineering lessons from production, and occasional pushback against the "AI-first SOC" narrative when it deserves it.