The AI industry is moving from using Large Language Models (LLMs) as isolated tools toward creating full-fledged agentic systems and the concept of an Agentic OS, where AI agents act proactively based on user intent.

image

What Happened

A fundamental technological shift is occurring: the focus is moving from reactive models to multi-layered agentic architectures that include reasoning, memory, action, and learning layers. A key trend is the implementation of agent interaction protocols, such as Agent2Agent from Google Cloud and Salesforce, to create cross-platform ecosystems.

Context

The traditional SaaS model requires manual management through interfaces and dashboards. Modern development is aimed at creating systems that do not wait for commands but instead understand context and independently execute complex chains of tasks, replacing management interfaces with intent-based interfaces.

Why It Matters for the Industry

For the industry, this means a radical transformation of business models: capitalization is shifting from process optimization tools (AI-native SaaS) to the creation of new markets through autonomous systems. The development of standardized interaction protocols (A2A) will allow for the construction of large-scale ecosystems where interaction between different AI agents becomes the standard for software operation.

Why It Matters for Users

Users need to distinguish between ordinary tools (SaaS) and full-fledged intelligence (Agentic OS). In the near future, software will become proactive, eliminating the need for manual management of complex processes and moving toward a workflow based on end goals and intentions.

What Is Not Yet Known / Limitations

There is a difference in how the focus is assessed: while technical and product roles emphasize architectural complexity, legal specialists (IP/Privacy Counsel, Startup Counsel) point to growing liability risks and regulatory uncertainty when transitioning to autonomous AI actions.

Sources

Author

Look at AI, Editorial Team