TL;DR AI risk doesn’t live in the model. It lives in the APIs behind it. Every AI interaction triggers a chain of API calls across your environment. Many of those APIs aren’t documented or tracked.

Legacy IAM can't govern autonomous AI agents that spin up, execute and terminate in seconds. New identity patterns are now emerging. The post 5 Capabilities of Workload Access Managers – And Why WAM ...

Onboarding has become a key control point for law firms, claims management companies (CMCs) and other regulated professional ...

Microsoft's Data API Builder is designed to help developers expose database objects through REST and GraphQL without building a full data access layer from scratch. In this Q&A, Steve Jones previews ...

With fewer than 1,700 votes counted here — early votes from Wells County — Indiana state Sen. Travis Holdman, with 741 votes, ...

Discover why ChatGPT 5.5 Codex is the ultimate AI coding tool for developers, featuring integrated design tools, high usage ...

ISN, the global leader in contractor and supplier information management services, announced Spartan Companies, a leading ...

The issue isn't artificial intelligence, but rather an industry adding AI agent integrations into production environments ...

The role of product managers in AI is rapidly evolving, requiring new skills and approaches. Quick iteration and weekly ...

Microsoft Product Manager Mike Kistler previews his Visual Studio Live! session on how MCP servers give .NET developers a universal standard for connecting AI models to external data and tools -- and ...

As enterprises move AI from experimentation to production, they face a growing connectivity and governance challenge.