Monika Chauhan

AI agents break in production at the context, tool, and observability layers. Amit Naik, VP of AI at CData, explains what fixes it and what managed agents cost you.

HA clusters grow from 2 to 4 nodes as infrastructure expands. Trey Isaac of SIOS Technology explains why configuration drift and human error scale with cluster size.

SIA by Hexo Labs is the first open source self-improving AI agent. Kunal Bhatia explains how it topped MLE-Bench and beat Karpathy's auto-researcher without human input.

Trusted telemetry is non-negotiable for AI in production. Shahar Azulay of groundcover explains why velocity—not just reliability—is the new differentiator | TFiR

Production AI inference is a distributed, bursty, latency-sensitive workload. Centralized cloud architectures designed for training cannot serve it effectively.

How Akamai Cloud builds a modular Kubernetes platform using Crossplane, Argo CD, and Kyverno, and safely scopes AI agents with read-only cluster access. With Corey McGalliard, Akamai Cloud.

AI agents hallucinate when they lack internal data. Michel Tricot, Founder and CEO of Airbyte, explains why data infrastructure is the missing layer in production agent deployments.

Single-cloud SQL Server DR fails when the provider does. Dave Bermingham of SIOS Technology explains multi-cloud HADR architecture, RTO/RPO trade-offs, and top implementation mistakes.

AI agents running unchecked cost more and create more risk than most teams realize. Robert Brennan, CEO of OpenHands, explains how an agent control plane solves it.

AI agents access your OS and production systems with no unified governance. Miska Kaipiainen of Mirantis explains why current tools fall short and what real control requires.