Systems | Development | Analytics | API | Testing

Fivetran + dbt Labs CEO George Fraser and Fivetran + dbt Labs President Tristan Handy sit down with Andreessen Horowitz general partner Martin Casado, one of the leading investors in software and AI infrastructure, to talk about Open Data Infrastructure in the AI era. Martin and his team have invested in dbt, Fivetran, Tabular, Cursor, OpenRouter, and many other companies.

Learn how to analyze a 30-second local load test using AI and Proxymock to track latency and P99 metrics effortlessly.

Operationalizing Code Optimization to Improve Cost, Performance, and Reliability of Your Cloud and AI Workloads While infrastructure optimizations like rightsizing and auto-suspending idle resources are standard practice, they cannot solve the cost and performance issues caused by inefficient code. Unoptimized workloads and AI functions waste compute resources, lead to missed SLAs, and significantly inflate cloud spend.

SAP projects are planned and tracked inside SAP Cloud ALM. Here's how Tricentis NeoLoad brings performance testing into that same project hub. In this demo, Tricentis shows how SAP teams create, run, and analyze NeoLoad performance tests from SAP Cloud ALM, so they catch performance problems long before go-live. Highlights.

SAP transformation projects are planned and tracked inside SAP Cloud ALM. Here's how SAP Enterprise Performance Testing by Tricentis, or EPT, brings performance testing into that same hub. In this demo, Tricentis walks through creating, running, and analyzing an EPT performance test without leaving SAP Cloud ALM, so performance problems surface long before go-live. Highlights.

Most people assume the model does everything in an agent. It doesn't. Sudais (Growth Strategist) sits down with Humza Khatri (Software Architect), to go inside the engine room: the custom-built agent harness that runs ARIA and Astera's other agents. CHAPTERS.

Explore powerful new features designed to help you balance rapid innovation with enterprise-grade control.

Even well-designed algorithms can fail and end up hurting the people they're meant to help. In this episode, Dr. Ben Green, Assistant Professor of Information and Public Policy at the University of Michigan, explains what keeps data from being used for good, why AI regulation can't be left to AI companies, and what organizations risk losing when they hand too much of their thinking to AI. In this clip from podcast, he shares why it is the companies that are building AI tools that need to be held responsible vs. putting agency on the tools.

In this episode of Discovering the Architecture Middle Path, Asanka is joined by Selvaratnam Uthaiyashankar (Shankar), WSO2's Chief Product Officer, to explore the architecture of product design. The conversation looks at the principles behind product decisions, the tradeoffs that shape those choices, and how architecture, developer experience, deployment models, and different user needs influence product design. They also discuss how product principles evolve as customer expectations and technologies such as AI and agentic systems continue to change.

Watch this video to see how see how SmartBear BearQ keeps bug reports and test results in sync with Jira, Linear, and Azure DevOps at AI speed and scale, with no manual copy-pasting. BearQ’s agentic QA system connects to the tools your team already relies on, so its three built-in agents can pull in context and push results right where your team lives.