While multi-agent AI systems sound great in theory and even practice, without trust mechanisms, these systems can fall apart fast.

Agent memory remains a problem that enterprises want to fix, as agents forget some instructions or conversations the longer they run. Anthropic believes it has solved this issue for its Claude Agent ...

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 ...

When I first started working with multi-agent collaboration (MAC) systems, they felt like something out of science fiction. It’s a group of autonomous digital entities that negotiate, share context, ...

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 ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I identify and showcase a new prompting ...

Salesforce tells us that a “critical orchestration and governance gap” is emerging as enterprises race to deploy AI agents everywhere. While adoption is high, the infrastructure supporting it needs to ...

As AI-assisted coding becomes more common, a new pattern is emerging: multi-agent workflows. A multi-agent workflow refers to using various AI agents in parallel for specific software development life ...

In mission-critical environments—think disaster response, financial systems, or supply chain logistics—success hinges on the seamless collaboration of multiple agents, whether they’re humans, machines ...