Google recently published a guide outlining eight essential design patterns for multi-agent systems, ranging from sequential pipelines to human-in-the-loop architecture. The guide provides concrete ...

What if the very systems designed to transform problem-solving are quietly failing behind the scenes? Multi-agent AI, often hailed as the future of artificial intelligence, promises to tackle complex ...

Today, multi-agent systems (MAS) have emerged as transformative technologies, driving innovation and efficiency across various industries. Comprising multiple autonomous agents working collaboratively ...

The governance challenge is intensifying as digital systems increasingly optimize for machine consumption rather than human ...

The biggest challenge to AI initiatives is the data they rely on. More powerful computing and higher-capacity storage at lower cost has created a flood of information, and not all of it is clean. It ...

How event-driven design can overcome the challenges of coordinating multiple AI agents to create scalable and efficient reasoning systems. While large language models are useful for chatbots, Q&A ...

For too long, enterprises have failed to go beyond the view of AI as a product; an assistant that sits to the side, helping users complete tasks and delivering incremental productivity gains. This ...

Model Context Protocol (MCP), a new open standard that defines how AI systems connect to data and tools, helps solve the ...

The key in agentic AI is establishing clear "expertise directories" and communication protocols using transactive memory ...