Search Was Built for Humans. Parallel's Parag Agrawal Is Rebuilding It for Agents

Web search is undergoing a fundamental transformation as the industry shifts from human-centric keyword queries to agentic search, where AI agents perform thousands of times more searches than humans. Parag Agrawal, founder of Parallel Web Systems, addresses this transition by building specialized infrastructure that prioritizes agent feedback over traditional human click data. This shift necessitates a new economic model for the internet, as current advertising-based systems fail to account for the value generated by autonomous agents. By applying Shapley values to quantify the contribution of specific content to AI outputs, creators can be fairly compensated, ensuring the continued availability of high-quality data. Ultimately, the future of the internet lies in a "push" model where agents proactively monitor the web, creating a more efficient, high-value ecosystem that moves beyond the limitations of human attention and traditional search engine optimization.