selfwarev1.0.0

Teams can collaboratively edit Markdown files with version control and rollback, ensuring data remains the canonical source. Each file is self-contained with its own logic and views, enabling offline-first editing without vendor lock-in.

AI agents autonomously fetch, sync, and merge remote data sources (e.g., APIs or Git repos) into local canonical storage, with user confirmation required for any writes. This allows automated data aggregation while maintaining audit trails and rollback capabilities.

Interactive learning materials where each file bundles content (Markdown), interactive quizzes (logic), and embedded viewing tools. Students can save progress locally, and instructors can update modules without breaking existing user data.

A single .self file acts as a personal wiki with linked notes, tasks, and scripts. Users can carry their entire knowledge base across devices, with AI agents assisting in content organization and search.

Industrial operators can create dashboards that read sensor data from local files, apply transformation logic, and display views—all within a single file. Changes to sensor mappings or views are versioned and reversible.

Offer a platform where users publish .self packages (apps as files). Basic hosting is free; premium features include remote canonical data sync, collaboration, and AI agent integration.

License the Selfware runtime and protocol stack to enterprises needing secure, decentralized data management. Provide customization, support, and training.

Create a marketplace where developers sell AI agents (packaged as .self files) that automate tasks like data analysis, content generation, or workflow orchestration.