According to @godofprompt, leading organizations like Goldman Sachs are leveraging a sub-agent decomposition strategy to enhance AI-driven business automation. Instead of relying on a single, monolithic AI agent, professionals design specialized micro-agents for distinct tasks—such as search, extraction, and synthesis. This modular approach increases efficiency and accuracy, as each micro-agent returns targeted, compressed summaries rather than unstructured data dumps. In the context of automating complex processes like S1 drafting, this architecture enables faster, more reliable document generation, presenting significant opportunities for financial institutions and enterprise AI adoption (source: @godofprompt, Jan 12, 2026).