Systems | Development | Analytics | API | Testing

AI didn't remove the release bottleneck, it moved it downstream. Code volume exploded, verification didn't. The old QA model isn't broken, it's outgrown: 80% of engineering teams have already traced a production incident to AI-generated code. AURA is Sauce Labs' answer, the only full-lifecycle release assurance platform built to close the gap. It continuously verifies every release against business intent, authoring, running, and regenerating tests in an autonomous learning loop, with humans in control.

Every tech leader is talking about agentic development and the promise of dramatically speeding up software delivery. But as organizations begin scaling AI-generated code, many are running into the same challenge: their test data processes can't keep up.

The challenge for most data teams isn’t a lack of ideas—it’s the time it takes to turn those ideas into something usable. In this session, Steffen Bischoff, Chief Architect Data at Qlik, follows a single dataset from a core system through its entire journey to becoming a governed data product. You’ll see pipelines created by describing intent instead of writing code, versioned in Git, then curated, quality-checked, and documented with the help of specialized agents. From there, the data product is made available to the AI tool of your choice through the Qlik MCP Server.

Learn more: speedscale.com.

Now that AI coding tools have put development capabilities into more hands, prototypes are becoming business-critical applications almost overnight. Shanea Leven sees an opportunity for a new generation of builders, provided the infrastructure around their applications keeps pace. Shanea explains how organizations can give developers and new technical employees room to build while maintaining the standards required for enterprise software..

Fully managed Confluent Cloud for Apache Flink combines Flink SQL for data engineers with programmatic capabilities like the Table API, User-Defined Functions (UDFs), and Process Table Functions (PTFs) for developers. You can build mission-critical use cases with programmatic capabilities while using familiar dbt- and SQL-based workflows.

Perform robust real-time forecasting on your Kafka data streams using IBM Granite Time Series models TTM, FlowState, PatchTST-FM right in Flink. Get started easily with zero-config, model flexibility, and lower cost in fully managed Confluent Cloud.

What's new in Q3'26: Real-time anomaly detection and forecasting with IBM Granite Time Series models and Google TimesFM model, upserts for Real-Time Context Engine to maintain fresh context for AI, and lightning queries to instantly serve the current state of the business for operational apps, analytics, and more.