About this Gridexpand for full context
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.
All Posts in This Grid
10 articles · newest first
AI in IT Operations: A Reality Check
What actually works, what's vendor theater, and where I think the genuine leverage lives over the next two years.
LLM-Powered Runbooks: Where They Work
LLMs augment runbooks well, but only after you've stopped treating them as answer engines. The pattern that works.
Prompt Injection: The OWASP of AI
Prompt injection is the SQL injection of 2026. Most teams haven't even mapped their attack surface yet.
RAG for Internal Documentation
RAG over internal docs is the most boring, most useful enterprise AI pattern. What it takes to get it right.
AI Tier-1 SOC Triage: Six-Month Results
After six months of LLM-assisted tier-1 triage, here's what I'd tell other IT leaders.
Model Selection for Enterprise IT
The LLM you pick for enterprise IT isn't the one on the ChatGPT homepage. Framework for selection.
Data Leakage in AI Workflows
Every AI workflow is a new data egress vector. Most orgs don't think about it until the lawyers find out.
The Economics of GenAI in the Enterprise
The ROI on GenAI isn't where the vendor deck says it is. Real economic patterns.
Shadow AI: What IT Doesn't Know
If you haven't counted Shadow AI usage, it's higher than you think. What to do about it (before reflexively banning).
Agentic AI: Hype vs. Production Reality
Agentic AI is real but fragile. What works, what breaks, and why your first deployment should be narrow.
Evaluating AI Vendors: The Practitioner's Checklist
Every AI vendor deck looks the same. The ten questions that separate real from fake.