AWS Bedrock automates intelligent document processing at scale

Perplexity has launched Personal Computer for Windows, extending its agentic AI tool to Microsoft's dominant operating system. The tool functions as a local AI agent that can access files and applications to perform tasks like document creation and spreadsheet updates, building on earlier integrations with Microsoft 365 and Teams announced in May. The Windows version follows Perplexity's April launch of the same tool for macOS.

Organizations typically evaluate AI agents as production-ready based on sandbox testing and benchmark scores, but this approach fails to account for how agent trustworthiness degrades in real-world deployment. According to Vijil CEO Vin Sharma, the core problem is that static benchmarks and models trained on outdated data cannot predict how agents will behave in dynamic environments where users, data, and attack techniques continuously evolve. The article argues that enterprises should shift focus from measuring agent capability to measuring trustworthiness through a fiduciary framework that assesses reliability, security, and safety as functional requirements.

The Model Context Protocol, an open standard connecting AI agents to enterprise software, released its largest update since launch twenty months ago. The revision transitions MCP to a fully stateless architecture, removes the need for persistent session management, and graduates interactive interfaces and long-running tasks into official protocol extensions. The changes eliminate operational barriers that previously made large-scale production deployments complex, allowing organizations to run MCP servers behind standard load balancers using existing cloud-native tooling.

Snowflake launched Cortex AI Gateway, a centralized control layer for governing how AI agents access enterprise data and tools, alongside security integrations with 1Password, Aembit, Linx Security, SailPoint, and Saviynt. The platform addresses a fundamental security gap: traditional enterprise security assumes humans are the actors, but AI agents operating at machine speed can exploit permission gaps and amplify existing risks. Snowflake positions itself as the control plane that decides what agents can do with enterprise data, rather than allowing each vendor to build closed ecosystems.