What problem does it solve? Coordinating multiple AI agents for complex tasks usually requires external orchestration frameworks, custom code, and infrastructure. OpenProse treats the AI session itself as a virtual machine, letting you write structured .prose programs that spawn subagents, manage state, and handle control flow without any external dependencies. ## Core Features & Use Cases - Program Execution: Run .prose files locally, from URLs, or from the p.prose.md registry using prose run, with the AI embodying the OpenProse VM. - Multi-Agent Orchestration: Define agents with models, prompts, skills, and permissions; coordinate them with parallel blocks, loops, pipelines, and persistent memory via resume:. - Compilation & Validation: Validate .prose syntax with prose compile before execution, and migrate legacy workspaces with prose update. - Flexible State Management: Choose between filesystem (default), in-context, SQLite, or PostgreSQL state backends for run persistence. - Use Case: Write a program that fans out five research sessions in parallel, synthesizes the results, and loops until a quality condition is met—then run it with a single prose run command. ## Quick Start Run the hello world example by asking the assistant to execute prose run examples/01-hello-world.prose.