Systems | Development | Analytics | API | Testing

Stop AI Hallucinations at the Source | Simba Intelligence

AI isn't failing because the models are weak. It's failing because the data beneath them is broken. 88% of AI pilots never make it to production. 74% of companies haven't seen value from AI. The uncomfortable truth? These failures aren't about intelligence—they're about access, governance, and context.

Why Node.js Upgrades Are Still Hard - And How OpenJS + NodeSource Are Addressing It

In today’s ecosystem, building with Node.js is not just about writing code. It’s about running systems that are reliable, secure, and able to evolve over time. That’s where collaboration at the foundation level becomes critical. At NodeSource, working closely with the OpenJS Foundation is not just a partnership. It’s a commitment to the long-term health, security, and evolution of the Node.js ecosystem.

In case you missed it | Meet Smartbear BearQ + application integrity

Missed the live event? Here’s a quick look at what we unveiled. AI has fundamentally changed how applications are built, creating a growing gap between development velocity and your ability to validate what’s being built. That’s why SmartBear delivers application integrity for the AI era – ensuring continuous, measurable assurance that your software just works as intended, with governance to operate at AI speed and scale.

A Wharton AI Research Leader's Formula for Responsible AI

Learn why scaling AI is as much a human challenge as it is a technological one. Stefano Puntoni, Co-Director of Wharton Human-AI Research and Professor at The Wharton School, examines the limits of data-driven decision making in the age of AI and why insights so often fail to translate into action. He breaks down the psychology behind AI resistance and outlines the leadership and change management strategies needed to turn AI potential into real organizational impact.

From Fear to Adoption: Stefano Puntoni on Fixing AI in the Workplace | The Data Chief

Is AI a tool or a threat? Wharton Professor Stefano Puntoni explains why "self-preservation mode" is killing AI adoption in the workplace. Puntoni joins Cindi Howson (The Data Chief host) & breaks down why AI isn't a strategy—it's a tool that requires a "meet in the middle" approach. To succeed, leaders must provide the vision and resources, while empowering workers to co-create the roadmap.

Why we built vision AI into TestComplete: Solving the complex app testing challenge

When we talk to testing teams at enterprise organizations, we hear the same frustrations repeatedly: “Our automation breaks every time the UI changes.” “We can’t test this application because it doesn’t expose accessible properties.” “We spend more time maintaining tests than creating new ones.” These scenarios block test automation adoption for teams that need it most.

Ep 66 | Women Leaders in Technology: AI Agents Are Your New Team- Now What?

From econometrics to anthropology to leading roles at Salesforce, AWS, and Nextdoor, Tatyana shares how her background shaped a fundamentally different approach to leadership. Drawing on her unconventional journey, she explains why agentic AI is forcing leaders to rethink how they manage technology, shifting from systems to a focus on teams, culture, and governance. Together, Tatyana and Paul share their perspectives on.

Data Silos Could Be Your Biggest Cloud Liability

In an always-on industrial economy, fragmented data is a liability. Your analytics reports may look flawless, but if they’re built on data silos scattered across edge, core, and cloud, they’re built on a fault line. Data silos drive-up costs, distort the critical decisions meant to drive competition, and prevent organizations from reaching a state of data singularity — where data becomes unified, portable, and continuously usable for AI.

LiveObjects now available: shared state without the infrastructure overhead

Shared state is a hard problem. Not hard in the abstract, computer-science sense (the concepts are well understood). Hard in the someone has to actually build this sense, where every team that wants a live leaderboard, a shared config panel, or a poll that updates in real time ends up reinventing the same wheels: conflict resolution, reconnection handling, state recovery. Most teams do not want to spend their time building and maintaining that layer. They want to ship the feature that depends on it.