The Real AI Decision Driver Isn’t the Model — Rob Hirschfeld of RackN | TFiR
Rob Hirschfeld of RackN argues that the real AI decision driver isn't model quality — it's the ...
AI Infrastructure
Artificial intelligence and machine learning discussions with industry leaders and practitioners. Covering AI infrastructure, large language models, GenAI adoption, MLOps, vector databases, AI security, and enterprise AI strategy from executives building real-world AI systems.
Enterprise AI Is Failing in Production — Empromptu AI Is Fixing the Foundation | TFiR
Empromptu AI CEO Shanea Leven breaks down why enterprise AI deployments fail in production and how the ...
Agentic AI Meets Bare Metal: How RackN Is Building the Infrastructure Layer for Enterprise AI Agents | Rob Hirschfeld | TFiR
Rob Hirschfeld, CEO of RackN, explains how 10 years of bare metal automation expertise is being built ...
Self-Host AI or Use OpenAI? Rob Hirschfeld of RackN Has a Clear Answer | TFiR
RackN CEO Rob Hirschfeld makes the case that hybrid AI is the inevitable destination for every enterprise ...
Vibe Hunting Is the Future of Threat Detection — Aqsa Taylor of Exaforce Explains Why
Exaforce Chief Security Evangelist Aqsa Taylor breaks down vibe hunting, explaining how AI-native SOC platforms enable ...
HA’s Patching Blind Spot Is Killing Uptime: Dave Bermingham, SIOS Technology | TFiR
Most HA architectures are built for unexpected failures, not planned maintenance. Dave Bermingham of SIOS Technology explains ...
Why Is the Vector API in Its 11th Iteration and When Will Project Valhalla Finally Unlock It | TFiR
The Vector API remains in its 11th incubation iteration because it deliberately waits for Project Valhalla's ...
AI Infrastructure Self-Inflicted Wounds: Why Enterprise Pilots Stall | Rob Hirschfeld, RackN | TFiR
Rob Hirschfeld, CEO of RackN, identifies the repeating failure patterns in enterprise AI infrastructure — siloed teams, ...
Why AI Infrastructure Needs OpenSearch to Prevent Hallucinations at Scale | Bianca Lewis, OpenSearch | TFiR
AI agents generate hundreds of thousands of queries per second—traditional vector search can't keep up. Bianca ...
Traditional Observability Wasn’t Built for AI Failures | Shahar Azulay, groundcover | TFiR
AI systems fail differently than traditional applications—no error codes, just subtle drift and hallucinations that sampling will ...