Anekha Sokhal distinguishes the flood of financial data from the tacit knowledge that gives an experienced investor an edge. Shared models and connectors are accessible to everyone, while learned relationships, blind spots and conviction remain difficult to capture when a trader leaves a firm.
Anekha Sokhal separates data gathering, cleaning and cross-checking from the final investment decision. She describes how agentic systems can support the former while making sources, claims and assumptions traceable, and warns that a weekend prototype still needs security, storage, reliability and sustainable running costs.
Anekha Sokhal also questions what happens to apprenticeship when each investor operates alone with agents. Her account treats trustworthy analysis and human accountability as the design problem, not autonomous trading performance as an established result.
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