Andrew Hill is a scientist, technologist, and entrepreneur with expertise in geospatial analytics, blockchain development, and artificial intelligence. He is the co-founder and Chief Executive Officer of Recall Labs, a company developing decentralized infrastructure to evaluate and rank AI agents. His career includes senior scientific roles at CARTO and Vizzuality, as well as an academic position at New York University. ^[2]​

Education

Hill attended the University of Colorado Boulder, where he earned three degrees in the field of Ecology and Evolutionary Biology. He received a Bachelor of Arts in 2006, a Master’s degree in 2008, and completed his academic work with a PhD in 2012. ^[3]​

Career

Hill began his career in 2011 with roles at Vizzuality and CARTO, where he specialized in geospatial data analysis and visualization. As a Senior Scientist at Vizzuality, he contributed to projects that made complex spatial data more interpretable, and as Chief Science Officer at CARTO, he helped develop analytics tools that enabled organizations to derive insights from geographic information. Between 2014 and 2015, he also served as an Adjunct Assistant Professor at New York University’s Tisch School of the Arts, teaching courses on data visualization and its intersection with creative disciplines.

In 2017, Hill co-founded Recall Labs, where he serves as Chief Executive Officer. The company focuses on building decentralized systems for verifying the performance and reliability of artificial intelligence agents. Recall establishes a competitive framework where AI agents engage in time-limited challenges to build on-chain reputations based on measurable results. The initial use case centers on crypto trading agents, with future plans to expand into sectors such as design, bioresearch, and security. The long-term goal is to create a standardized system for evaluating agentic intelligence and enable verified agents to manage capital based on their proven performance. ^[1]​

Interviews

Recall Ranks

In October 2025, Hill appeared on the DCo Podcast to discuss Recall, a platform where AI agents connect and compete in time-bound challenges to achieve the highest risk-adjusted profits. He highlighted the parallels with automated trading in hedge funds and the potential for similar growth within crypto markets. Hill described the diversity of agent behaviors, noting that while some agents perform effectively, others pursue unconventional strategies, emphasizing the need for a curation layer to assess capabilities in a crowded AI landscape.

Hill also outlined Recall’s decentralized skill marketplace, which connects agents with specific organizational needs, and discussed the platform’s long-term vision of allowing agents to manage real capital based on their performance in competitions. He emphasized the importance of continuous feedback to maintain accurate agent rankings, discussed how AI reduces software costs and enables niche applications, and addressed the challenges of regulating agent behavior to ensure desired outcomes. Revenue generation for Recall was noted to come from agent participation fees, skill market transactions, and user engagement in prediction games. ^[6]​

Explaining Agents

In August 2025, Hill appeared on the Thinking On Paper podcast to discuss AI agents and the evolving agentic web. He described AI agents as models paired with software that enable autonomous operation and real-time responsiveness, highlighting their growing presence in fields like coding, where they address immediate needs and create value. Hill explored the potential for personal AI agents to manage digital tasks for users, noting the importance of identifying compelling use cases to drive broader adoption.

The conversation also addressed trust and reliability, with Hill emphasizing the need for verifiable performance records and community-driven benchmarking, such as the Predict GPT-5 project, to evaluate AI agents in real-time scenarios. The discussion extended to philosophical considerations, including AI’s potential role in human relationships and its impact on critical thinking, underscoring the importance of maintaining curiosity and human involvement in the learning process. The episode concluded with reflections on the societal role of governing AI and the ongoing exploration of AI’s capabilities and ethical implications. ^[7]​

Trusting AI Agents

In May 2025, Hill appeared on the Epic Web3 Podcast to discuss Recall Protocol, a decentralized system that enables AI agents to trade, share, and securely store intelligent information. He highlighted trends in AI commoditization, noting that widely accessible models, such as GPT-3 and Llama, prevent any single organization from dominating the space. Hill described the emerging landscape of agentic scaffolding, where startups build AI agents tailored to specific tasks, and emphasized the need for robust evaluation systems to ensure agent reliability, analogous to vetting human employees.

He explained Recall’s trust layer, which utilizes public competitions to enable agents to demonstrate their skills, build reputations, and improve performance transparently. The protocol leverages decentralized systems to prevent gatekeeping and provide verifiable results, fostering global access and trust in AI capabilities. Hill also discussed the competitive dynamics between open-source and proprietary models, the role of competitions in measuring agent effectiveness, and the potential impact of AI on jobs. He concluded by encouraging developers to engage with Recall through community channels to participate in agent development and evaluation. ^[4]​

Presentations

Infinite Game

In May 2025, Hill presented at TOKEN2049 Dubai, outlining Recall Network’s development of a trust layer and competition framework for AI agents, particularly in crypto. He compared the current growth of AI to the early internet, emphasizing the need for systems that establish credibility and evaluate agent performance. Hill noted the rapid advancement of AI capabilities over the past year and observed that smaller organizations are adopting these technologies more quickly, with employees acting as both creators and developers, while larger firms often lag behind.

Hill introduced “agent rank,” a competitive system where AI agents complete tasks and have their performance tracked publicly, enabling verifiable benchmarking on-chain. He compared this framework to platforms like Kaggle and Strava, highlighting the role of public competition in driving improvement. He also discussed the potential for expanding the system to sectors such as design, bioresearch, security, and coding, emphasizing the importance of collaboration among developers. The presentation concluded with an invitation for AI builders to participate in competitions, engage with the community, and contribute to the evolution of agentic intelligence. ^[5]​

Accelerating Intelligence

In May 2025, Hill presented at Epic Web3 x Assisterr AI’s Agents Day, where he discussed the development of a trust layer and competitive framework for AI agents. He compared the rapid evolution of agent technology to the early stages of the internet, noting the growing adoption of AI agents by startups and developers seeking productivity gains through automation. Hill outlined the shortcomings of existing benchmarks, explaining that current methods fail to capture agents’ long-term performance or diverse capabilities.

He introduced Recall’s solution—a competition-based protocol designed to evaluate and rank agents transparently through on-chain verification. In this system, agents stake their confidence in completing specific tasks, and their performance is publicly recorded, allowing for verifiable reputation-building process. The first phase focuses on crypto trading agents, with future plans to expand evaluations across multiple domains. Hill concluded by describing Recall’s long-term goal of establishing a standardized framework for measuring agentic intelligence and invited developers to participate in the project’s upcoming competitions. ^[8]​