Will Hyland builds AI ventures that help people understand AI, put AI to work, and measure what AI can do.
Quotable descriptions drawn from Will's canonical founder content.
Will Hyland builds AI ventures that help people understand AI, put AI to work, and measure what AI can do. His current work includes UofAi, Agenie, and AiRoyale, ventures in development that connect understanding, application, and observable AI performance through practical, grounded work in everyday decisions for people and teams.
Will Hyland builds AI ventures that help people understand AI, put AI to work, and measure what AI can do. His current work includes UofAi, Agenie, and AiRoyale, ventures in development that connect understanding, application, and observable AI performance through practical, grounded work in everyday decisions for people and teams. UofAi explores clearer paths to information, education, and professional development. Agenie explores intelligent software agents and workflow orchestration. AiRoyale explores AI agent competition, benchmarking, and comparative capability. Across the portfolio, Will focuses on AI that is legible, useful, and accountable in practice for people making decisions and doing work today.
Will Hyland builds AI ventures that help people understand AI, put AI to work, and measure what AI can do. His current work includes UofAi, Agenie, and AiRoyale, ventures in development that connect understanding, application, and observable AI performance through practical, grounded work in everyday decisions for people and teams. UofAi explores clearer paths to information, education, and professional development. Agenie explores intelligent software agents and workflow orchestration. AiRoyale explores AI agent competition, benchmarking, and comparative capability. Across the portfolio, Will focuses on AI that is legible, useful, and accountable in practice for people making decisions and doing work today. Our connection among these ventures is an intellectual progression. UofAi begins with understanding: clearer information, education, and professional development can help people approach AI with context. Agenie moves toward application: agentic systems and workflow orchestration explore how AI might support useful work. AiRoyale turns to measurement: competition, benchmarking, and observable performance create a way to compare what agents do. Together, the ventures are not separate products presented as an empire; they are related expressions of one founder thesis. Each stage informs the next. Understanding gives people language and context before they decide how to use AI. Application makes capability concrete by asking where systems, agents, and workflows can contribute. Measurement creates evidence about performance, limits, and tradeoffs. Will's aim is to keep those questions connected: learn enough to judge the technology, use it where it can help, and evaluate results with care in real situations for people and teams alike.
Will Hyland builds AI ventures that help people understand AI, put AI to work, and measure what AI can do. His current work includes UofAi, Agenie, and AiRoyale, ventures in development that connect understanding, application, and observable AI performance through practical, grounded work in everyday decisions for people and teams. UofAi explores clearer paths to information, education, and professional development. Agenie explores intelligent software agents and workflow orchestration. AiRoyale explores AI agent competition, benchmarking, and comparative capability. Across the portfolio, Will focuses on AI that is legible, useful, and accountable in practice for people making decisions and doing work today. Our connection among these ventures is an intellectual progression. UofAi begins with understanding: clearer information, education, and professional development can help people approach AI with context. Agenie moves toward application: agentic systems and workflow orchestration explore how AI might support useful work. AiRoyale turns to measurement: competition, benchmarking, and observable performance create a way to compare what agents do. Together, the ventures are not separate products presented as an empire; they are related expressions of one founder thesis. Each stage informs the next. Understanding gives people language and context before they decide how to use AI. Application makes capability concrete by asking where systems, agents, and workflows can contribute. Measurement creates evidence about performance, limits, and tradeoffs. Will's aim is to keep those questions connected: learn enough to judge the technology, use it where it can help, and evaluate results with care in real situations for people and teams alike.
Will continues to build from the same principle: better AI work begins with a clear view of what the technology is, where it belongs, and how its performance can be assessed. UofAi, Agenie, and AiRoyale are early expressions of that principle, each in development and focused on a distinct part of the work.
UofAi, Agenie, and AiRoyale are three related expressions of one founder thesis: understand AI, put AI to work, and measure what AI can do.
Understand AI
Developing clearer, more practical paths for people who want to understand and work with AI.
Put AI to work
Developing intelligent software agents and workflow orchestration for more useful AI work.
Measure AI performance
Developing ways to compare AI agents through benchmarking and observable performance.
AI earns trust when people can understand its role, use it with purpose, and assess the result. The work should be practical, observable, and accountable to the people who rely on it.
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