What if the next generation of AI systems could not only understand context but also act on it in real time? Imagine a world where large language models (LLMs) seamlessly interact with external tools, ...

The protocol offers a standardized framework that defines how AI systems securely connect with trusted, validated knowledge ...

Making inherently probabilistic and isolated large language models (LLMs) work in a context-aware, deterministic way to take real-world decisions and actions has proven to be a hard problem. As we ...

The Model Context Protocol (MCP) is redefining how artificial intelligence (AI) systems interact with external tools and services. By addressing the inherent limitations of large language models (LLMs ...

LLMs and AI tools have transformed nearly every industry, including marketing. We’ve become accustomed to AI’s ability to: But as these models evolve, their capabilities are entering a new phase with ...

This guide breaks down the agent-to-agent protocol, task objects, and agent Cards, which enable scalable, secure ...

A new protocol could give you power over how AI models collect and use your content. See what rules are being drafted and why they matter.

As organizations push AI systems into production, IT teams are asking how to make models more dependable, secure and useful in real-world workflows. One approach gaining traction is the Model Context ...

Carl is the CTO and co-founder at Avassa and obsesses over an edge orchestrator that application- and infrastructure teams alike can love. AI is no longer just a tool that reacts to prompts. With the ...