ArchoryYou and AI, side by side.
Open ArchoryUse desktop Chrome. Your materials are stored in the local folder you choose.
Archory is a personal archive and knowledge space centered on methodology. It is designed to turn materials, knowledge, and work experience into methods that can be used and improved in practice, and to make these accumulated resources the foundation for collaboration between people and AI.
Why methodology matters
Knowledge informs judgment. Methodology guides how we ask questions, choose a course of action, and evaluate results. A skill is the ability to put methods into practice through specific tools and workflows. Continually creating, testing, and improving methodologies is an important way for knowledge to advance human progress.
The industrial age organized work around skills that could be taught and applied repeatedly. As AI takes on more specific tasks, people should have more room to develop knowledge, ask questions, create methods, and continually revise them through practice.
Your own archive and methods
As AI agents emerge and evolve, the tools that support individual work will keep changing. Everyone needs an archive, a knowledge base, and methodologies of their own, so that the knowledge and experience they build over time can be preserved, used, and developed.
People derive methods from their own materials, data, and work experience. Agents use that knowledge and those methods to help people take action. Whatever agent you choose, the knowledge and experience you build should remain under your control and provide the foundation for your next collaboration.
Archory is built around a personal local library. Your materials are stored in a folder you choose on your own computer and managed by you. Privacy protection is a fundamental principle of this design.
People and AI, working side by side
People provide knowledge, methods, judgment, and direction. AI helps carry out specific work. The process and its results provide evidence for evaluating methods, while feedback drives continual revision—helping you refine your methods as you work with AI.