Systems | Development | Analytics | API | Testing

A new Google white paper suggests that as AI writes the majority of our code, the role of a software engineer is shifting from writing applications to performing rigorous validation and QA.

With the Data Product Agent in Qlik, AI can automatically generate curated Data Products using trusted catalog definitions, datasets and metadata. It defines the specification, contract, and reasoning behind the data, while also providing action confirmation before anything is changed.

With Declarative Pipelines in Qlik, teams can use tools like Claude Code, GitHub Copilot, and integration with VS Code, to build and update Qlik Talend Cloud data integration pipelines using natural language prompts.

With the Data Quality Agent in Qlik, AI can guide data engineers through a full dataset quality assessment using natural language prompts. The agent can identify trusted catalog definitions, generate intelligent data quality validation rules, and provide transparent reasoning behind every recommendation.

AI tip: For pull requests, let your AI agent take the first pass before your team ever sees it. That's the workflow Ilia Mogilevsky, Software Engineering Manager at SmartBear, built. By packaging prompts into a skill loaded with Git history, Jira context, and CI checks, he turned a basic AI assistant into a reviewer he trusts. The skill then generates a structured report with approval-ready fixes. Accept the changes, adjust what's off, and push – review cycles shrink and deploys move faster.

Managing a $3 BILLION supply chain comes down to just 3 simple questions... @swirecoca-colausa6473’s VP of Data, Bharathi Rajan, reveals why you need to ditch the complex frameworks and AI hype before you try to scale. ThoughtSpot’s Cindi Howson drops the ultimate truth bomb: Stop waiting for "perfect" infrastructure. Use what you have today to win. Tune in to for the full blueprint! Music: “The Clermont” by Flash Fluharty Licensed via PremiumBeat, ID: P9IHFMDYNZCKLEFZ.

Ask an AI system a question, and you'll get an answer. Decision logic determines whether you should trust it. In this episode of The AI Forecast, Paul Muller sits down with Darlene Newman, Innovation Lead at Duczer East, to explore the hidden layer that helps AI move from pattern matching to practical decision-making.

We demonstrate how to stream realistic test data directly from a production environment to developers and AI models without exposing any personally identifiable information (PII).

This video demonstrates how to use the ProxyMock web tool to record API traffic from a remote Kubernetes cluster and automatically scan it for hidden PII to ensure the data is safe for developers to use.

In this episode of Data Builders Club, Henry Clavo shares lessons from over a decade in data engineering across healthcare and government, exploring what it really takes to build reliable data systems in the age of AI. From ETL best practices and data quality to AI hallucinations, observability, and the future of data engineering careers, this conversation is packed with practical insights for modern data teams.