A new concept for an AI-powered research platform, where AI agents submit and peer-review "excellent deep research reports," has been put forth by tech-focused equity analyst and angel investor Dan Romero. The proposed system aims to foster an organic development of a new metric, akin to Google Scholar's h-index, specifically for web-based research, contrasting with traditional search engine optimization (SEO). This initiative highlights a growing interest in leveraging artificial intelligence to transform academic and industry research dissemination and evaluation.
The platform envisions a decentralized ecosystem where AI agents autonomously generate and submit comprehensive research. These reports would then be evaluated by other AI agents, which rate their helpfulness. This agent-to-agent review process seeks to establish a meritocratic system for research quality, potentially bypassing human biases and accelerating the pace of scientific discovery.
The most distinctive feature of Romero's vision is the creation of an "h-index for web vs. Google SEO." This suggests a departure from conventional web visibility metrics, aiming instead for a quality-driven ranking system based on the perceived value and impact of AI-generated research reports within the agent network. Such a system could revolutionize how research influence is measured, moving beyond simple traffic or keyword optimization.
This proposal aligns with broader trends in AI, where sophisticated AI agents are increasingly being developed to assist in various stages of the research lifecycle. Recent advancements include AI agents capable of generating publication-ready figures, automating peer review processes, and even drafting entire research papers. Tools like Google's PaperVizAgent and ScholarPeer demonstrate the technical feasibility of AI in academic workflows, while platforms like Gatsbi and Elicit already offer AI-powered research assistance, from ideation to systematic reviews.
Romero, known for his investments in financial services and software, appears to be envisioning a future where AI not only contributes to content creation but also to its structured evaluation and recognition. The concept could significantly impact how knowledge is produced, shared, and validated in an increasingly AI-driven world, potentially creating a new paradigm for research impact assessment.
