prose

Multi-agent AI workflows are orchestrated by defining sequences, parallel tasks, loops, and error handling using the OpenProse declarative programming language. A virtual machine model executes these programs while managing agent lifecycles and context passing.

Specialized AI agents can be defined, configured, and managed with custom prompts, models, and skills. This agent management capability allows assigning specific roles to different agents within a structured workflow automation program.

OpenProse is a declarative programming language used to define multi-agent workflows. It handles state persistence through a virtual machine model, ensuring context passing and agent lifecycles are maintained during complex parallel execution.

Multi-agent workflow orchestration supports dynamic program composition via imports. It allows reusable blocks to be defined, enabling modular construction of complex sequences and parallel tasks for AI agent execution.

Automating a code review process involves orchestrating multiple AI agents where one researches the issue, another critiques the code, and a third synthesizes feedback. This is achieved by defining these steps in a structured OpenProse program.

Using a declarative programming language for LLMOps automation requires understanding OpenProse syntax to manage agent lifecycles and parallel execution. Complex error handling and state persistence logic must be explicitly programmed within the virtual machine model.