Systems | Development | Analytics | API | Testing

The Big AI Lie

May 28, 2026 By ThoughtSpot In ThoughtSpot
Shub Agarwal (Founder of the AI Trust Lab at USC) flips the script. Stop over-investing in massive data overhauls. Instead, reverse your approach: start with a brutal business problem, pull only the specific data needed to solve it, and build incrementally. Chief Data & AI Strategy Officer Cindi Howson agrees that true value comes from scaling immediate business impact, not waiting for a flawless architecture that will never arrive.
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ClearML

When AI Infrastructure Meets Enterprise Data: ClearML on the Dell AI Data Platform

May 28, 2026 By Adam Wolf In ClearML
Dell Technologies has published a validated integration of ClearML with the Dell AI Data Platform (AIDP), pairing ClearML’s AI infrastructure capabilities with Dell’s enterprise-managed storage and search engines. The result is a reference architecture that lets AI teams keep moving fast while platform teams keep the data foundation enterprise-grade. Here is what the integration does, why it matters, and where it fits.
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InsightSoftware

Why Healthcare Organizations Need Governed AI Analytics

May 28, 2026 By InsightSoftware In InsightSoftware
For healthcare organizations, AI governance is a must-have that can’t be ignored. To safeguard sensitive patient information, healthcare is subject to a variety of different regulations, for example HIPAA in the United States and GDPR in the European Union. As healthcare organizations implement AI, it brings a balance of efficiencies and risks.
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perforce

Perforce P4 vs Git for AI Coding Agents: Why Parallel Development Hits a Merge Wall

May 28, 2026 By Perforce In Perforce
A few months ago, a CTO I respect posted on LinkedIn that he was thinking about going back to Perforce P4 or SVN. He runs a modern engineering org and uses Git. The trigger was that his AI coding agents were stomping on each other’s changes faster than his developers could reconcile them. That post isn’t an outlier. It’s an emerging pain point in AI-driven workflows.
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Your AI Pilot is Lying to You: Why Enterprise Tech Needs a Trust Score

May 27, 2026 By ThoughtSpot In ThoughtSpot
Understand how to close the gap between AI experimentation and enterprise production. Shub Agarwal, Founder of the AI Trust Lab at USC and author of Successful AI Product Creation: A Nine-Step Framework, shares his AI product management framework for taking enterprise AI strategy from demo to production, drawing on two decades of product leadership at Amazon and Fortune 50 firms. He breaks down why experimentation must tie directly to business OKRs, the four mindset shifts leaders need to scale AI responsibly, and how the AI Trust Lab is building a benchmark evaluation framework for AI model trust and governance.
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appian

Address the Long Tail of Legacy Applications with AI Modernization

May 27, 2026 By Rachel Nizinski In Appian
The pressure to scale AI is on, forcing most organizations to take a serious look at their legacy technology stacks and reinstate failed or postponed modernization projects. AI both requires and enables a modern enterprise. Traditional barriers to modernization—such as time, cost, and business disruption—are now significantly reduced with the introduction of AI modernization tools.
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