According to God of Prompt (@godofprompt), modern AI routers are designed to automatically learn the affinity between specific user inputs and specialized expert modules during training. This means that when a user asks for a quantum physics explanation, the router activates Science and Technical experts, while creative prompts trigger Creative and Emotional experts. This process eliminates the need for manual assignment, enabling AI systems to dynamically route requests to the most suitable expertise, thereby improving performance and scalability in real-world AI applications (Source: @godofprompt, Jan 3, 2026).

According to @godofprompt, Mixture of Experts (MoE) architectures in AI go beyond compute savings by enabling transformative training strategies. MoE allows researchers to dynamically add new expert models during training to introduce novel capabilities, replace underperforming experts without retraining the entire model, and fine-tune individual experts with specialized datasets. This modular approach to AI design, referred to as compositional intelligence, presents significant business opportunities for scalable, adaptable AI systems across industries. Companies can leverage MoE for efficient resource allocation, rapid iteration, and targeted model improvements, supporting demands for flexible, domain-specific AI solutions (source: @godofprompt, Jan 3, 2026).

According to God of Prompt on Twitter, the current trend in AI development emphasizes building modular AI skills rather than full-scale autonomous agents, citing advantages in scalability, maintainability, and integration with existing enterprise workflows (source: @godofprompt, Dec 30, 2025). This approach allows businesses to deploy targeted AI functionalities—such as advanced data extraction or personalized recommendations—directly into their platforms without the complexity of managing end-to-end agents. The modular AI skills model drives faster time-to-market, reduces operational risk, and opens new opportunities for SaaS providers and enterprise AI integration, aligning with market demand for flexible, composable AI solutions.