Systems | Development | Analytics | API | Testing

AI agents are transforming enterprise AI, governance frameworks, and business decision-making. In this episode, we explore agentic AI systems, decision intelligence, and brand brains — AI systems designed to produce brand-specific, production-grade content that differentiates businesses. Join @wpp's Daniel Hulme & podcast host Cindi Howson for this insightful discussion. If you're a Chief Data Officer, Chief AI Officer, or enterprise leader, this conversation explains how to deploy AI agents safely, govern them effectively, and automate complex decisions while augmenting human creativity.

Welcome to Part One in this series covering AI Enterprise Security with ClearML. How do you secure an AI platform, ensure compliance, and still give your teams the access they need to move fast? ClearML builds security, compliance, and cost control into every layer of the platform — the guardrails are invisible to your AI/ML teams, but not absent. In this video, I introduce the six layers of the ClearML Enterprise security stack: Identity & Access, Configuration Governance, Automation Security, Compute & Data Access Governance, Model Serving, and Audit & Compliance.

In this session of MLOps Live, Joseph Perkins, Product Manager at Vizro by QuantumBlack, and Gilad Shaham, Director of Product Management, Iguazio (A McKinsey Company) discuss how modern AI teams are moving beyond heavy engineering to deliver production-ready, business-visible AI systems using open-source frameworks like MLRun and Vizro. In this session, you’ll learn how: The session includes a live demo of a gen AI application, showing how MLRun and Vizro work together to deliver both operational control and business visibility in production.

Qlik Data Products for Analytics is how you turn raw data into something people can actually trust and reuse. It’s built right into Qlik Cloud Analytics and is designed for analytics teams, data producers, and even AI initiatives. Instead of everyone rebuilding datasets over and over, teams can publish curated, governed, analytics-ready data products that include business context, quality checks, and our patented Qlik Trust Score. People discover them in a marketplace, plug them straight into dashboards, apps, or AI workflows, and move fast with confidence. The big value? Less duplication, lower cost, faster app development, and insights you can actually trust.

In this episode, Drew Oetzel sits down with Ryan Anguiano, Staff Architect at @WhatIfMediaGroup to discuss their massive migration of from legacy EC2 instances to using the @Strimzi operator. Ryan shares deep technical insights into how they optimized their data streaming architecture, including their use of EKS, EBS storage striping, and why the 12-Factor App methodology was the key to migrating over 100 services in just a few months.

Read more: https://www.speedscale.com/blog/how-to-migrate-oracle-java-to-openjdk-with-traffic-replay/

95% of AI pilots are failing. Here's why the other 5% are winning. While most organizations scramble to retrofit compliance into their AI implementations, leading finance teams are building it in from the start—and gaining a major competitive edge. Three insights that caught my attention: → Vendor solutions succeed at 2x the rate of internal builds (67% vs 33%)—your team's expertise matters more than you think.

Calling Katalon a hybrid testing platform means it brings manual, automated, and AI-generated testing together in one unified system. Katalon is built to help teams design, run, manage, and report on all three types of tests side by side, giving clear visibility into coverage, quality, and release readiness without forcing teams to choose just one testing approach — Alex Martins, VP of Strategy at Katalon.

In this episode, *Dr. Sanjiva Weerawarana* and *Asanka Abeysinghe* demystify what “agents” really are and why architects should care. They walk through core concepts and terminology—agents, agent loops, prompts, context, memory, RAG, tools, MCP, and skills—and discuss how agents observe, act, and evaluate. The conversation compares agents to traditional systems, explores where agents fit in modern architectures (including solo agents, agent-to-agent patterns, and multi-agent setups), and looks at orchestration challenges.