Agent Apprenticeship is an open ecosystem for teaching AI agents through real-world work loops, reusable experience, and collective training signals. The project combines a GitHub repository, seed dataset, and community site aimed at agent builders who want workflows that improve through repeated tasks rather than isolated prompts. It is notable because it frames agent improvement around apprenticeship-style practice: agents observe work, collect loop data, and reuse learned experience across future tasks. GitHub discovery found the project as a recently created, high-star AI-agent repository, and the official site describes “real-world agent work experience, looped into collective learning.” For Smartoolbox visitors, it fits as a developer-oriented AI agent training and workflow-loop resource rather than a consumer chatbot.
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