Systems | Development | Analytics | API | Testing

Ep 77 | The Rise of VibeOps: How AI Is Transforming Network Automation

For decades, network teams have been forced to choose between speed and stability. AI may finally be changing that equation. In this episode of The AI Forecast, Paul Muller sits down with John Capobianco, Head of AI and Developer Relations at Itential and author of “Automate Your Network,” to explore how AI is reshaping the future of network operations. Drawing on decades of experience in network engineering, John explains why network automation has struggled to gain traction and how AI, agents, and Model Context Protocol (MCP) could finally break the bottleneck.

How Thrive Learning Scaled 56K Users with Agentic Analytics

Live from Snowflake Summit '26, tech leaders from around the globe gathered to discover how the world’s most innovative companies are making AI real for business. But few sessions delivered as much raw, practical insight as the one presented by Frankie Woodhead, Chief Product & Technology Officer at Thrive Learning. Heading up a fast-growing, £20m ARR LearnTech business that serves over 500 global customers and 5 million users, Woodhead didn't give a standard product pitch.

Agentic Analytics in Finance: Lessons from Navan and EcoLab

Finance leaders are operating in one of the most demanding macro environments in recent memory. Interest rates are moving faster than most models anticipated, reshaping the cost of capital almost overnight. Supply chain fragility has also turned working capital management into a moving target, and geopolitical uncertainty is changing how you plan for the future. Yet for many finance functions, the analytics stack hasn't kept pace with that urgency.

Practical applications for NeoLoad MCP: 3 use cases

As AI-aided software development lifecycles pick up speed, performance teams are left with the familiar challenge of too much work, too few specialists, and results that take too long to analyze. Over the past year, Tricentis NeoLoad has shipped capabilities designed to address each of these problems directly. What started with Augmented Analysis accelerating root cause identification grew into a fully connected Model Context Protocol (MCP) architecture.

Building Confidence Across APIs and AI Agents with the Swagger Contract Testing Kiro Power

There is a specific kind of confidence that comes with deploying software. Not just “the tests passed” confidence, but the kind that comes from knowing the services your application depends on still behave the way you expect them to. Preserving that integrity becomes harder as systems grow, teams move faster, and AI agents become active participants in delivery workflows.