Your AI Feature Shipped. Now, Will Users Trust It?
The question product and engineering teams ask before shipping an AI feature is usually simple: does it work? Is the model accurate enough? Are the outputs reasonable?
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Agentic AI Just Rewrote the Data Engineer's Job Description. Here's What IT Leaders Need to Know.
Gartner predicts that 70% of today's data engineering tasks will be fully automated by 2030. I put that number to Tim Garrod, Qlik's Head of Product Management for data integration and quality, on a recent Qlik Insider session, and his answer is the one every CIO, CDO, and VP of IT should sit with: automation doesn't make the data engineer obsolete, it makes the good ones ten times more valuable. AI amplifies skilled judgment. It doesn't replace it.
New MCP tools for Declarative Pipelines
Qlik's MCP server just got three new lookup tools built for data engineering. They connect directly to your Qlik Cloud tenant, so coding agents can pull the real project values a pipeline needs instead of working from an empty template, find spaces and data connections by name, and browse the tables and views available on a connection, just by asking in natural language. That means easier declarative pipeline creation, with real tenant context built right into your prompt for faster, more accurate iteration.
AI Chatbots: Transforming Performance Testing
Until recently, performance testing workflows meant complex scripting, manual maintenance, and slow feedback. Now, the adoption of AI chatbots in QA and DevOps is prompting a fundamental shift. Teams using AI-driven testing tools are seeing significant reductions in test cycle times and improvements in defect detection. These are not incremental improvements, but shifts that are redefining benchmarks for speed and coverage.
How to Operationalize AI Pilots: Roche's Agentic Analytics
If there's one thing that stuck with me from Yannick Misteli's session at the Agentic Analytics Playbook event in London, it's this: most AI pilots don't stall because of technology or budget. They stall because nobody answered the "day after" questions. I had the opportunity to sit down with Yannick Mistelli, Head of Engineering at Roche, the global pharma company with 100,000+ employees and heavy regulation across 25+ countries.
Myth v Fact | Shipping software with AI
Think you know the rules of shipping software with AI? Myth or fact? Test your instincts and see what it takes to maintain application integrity at the speed of AI.
[AgentSpot Showcase Series] Winny - GTM Intelligence Agent
Meet Winny, a GTM Intelligence agent built with AgentSpot and ThoughtSpot. See how teams can get faster answers to questions about conversion and pipeline velocity by simply asking questions in AgentSpot or Slack, with verified data pulled directly from ThoughtSpot. What is AgentSpot? AgentSpot is multiplayer AI for your business. Anyone can build, share, and collaborate with AI agents connected to your company’s data, context, and tools.
How AI changed performance engineering (2 years later)
We thought the lemon had no more juice. AI proved us wrong.
The 3 Things Companies With AI ROI Have in Common
Most companies are investing in AI. Very few are seeing it reflected in their financial results. The gap comes down to three foundational decisions. In this clip from The Data & AI Chief, Raman Tallamraju from Vanguard breaks down what the companies seeing measurable AI benefits have in common.
Centerprise AI: Add New Banking Systems Without Custom Integration Projects
Your next banking initiative shouldn't wait on another custom integration. Keep your core banking system and connect everything around it with Centerprise AI. Describe the pipeline you need, and it generates the connections, mappings, transformations, and data quality checks across APIs, databases, legacy systems, and more.