The transition to Artificial Superintelligence (ASI) requires a radical paradigm shift: instead of simply increasing the parameters of single models, the industry must move toward horizontal scaling through the coordination of multiple specialized AI agents.
What Happened
Current multi-agent systems demonstrate critically high failure rates—ranging from 41% to 87%—due to the lack of a unified architectural coordination layer. To solve this problem, the concept of an "Internet of Cognition" is proposed, which includes Shared Intent protocols, a common contextual memory (Cognition Fabric), and semantic authorization mechanisms (CASA — Continuous Agent Semantic Authorization).
Context
The traditional approach to AI development has focused on vertical scaling—increasing the number of parameters in neural networks. However, to achieve ASI levels, the current engineering base is insufficient, as the interaction of disparate agents requires new standards for context exchange and security management, analogous to TCP/IP protocols in classical networks.
Why It Matters for the Industry
AI scaling problems are shifting from model size to interaction architecture. For developers, this means growing demand for middleware solutions, agent orchestrators, and observability tools for multi-agent systems. The development of semantic authorization and context exchange protocols will become a critical node in creating reliable autonomous systems for business.
Why It Matters for Users
The future of AI lies not in a single "all-knowing" model, but in an ecosystem of specialized agents working as a team. Understanding their coordination principles and security mechanisms, such as CASA, will allow users and companies to better predict the evolution of enterprise AI tools and integrate them into complex workflows.
What Is Not Yet Known / Limitations
There is a divergence in how the problem is interpreted: ranging from a purely architectural approach by machine learning researchers to the applied aspects of usage and the infrastructure layer.
Sources
Author
Look at AI, Editorial Staff