prose

You can orchestrate multi-agent workflows by defining agents and control flow constructs using the declarative OpenProse programming language. This enables structured execution of parallel tasks, loops, and error handling for robust AI applications.

Managing state persistence across AI agent sessions is handled automatically by configuring state backends. You can use the file system, SQLite, or PostgreSQL to persist context, memory, and agent lifecycles for scalable applications.

Building a multi-agent system for research and synthesis involves defining sequential or conditional execution flows. You configure one agent to research, another to critique, and a third to synthesize, all managed by a central orchestrator.

Yes, you can use SQLite or PostgreSQL as state backends for scalable AI agent state management. These database options allow you to persist context and memory across sessions effectively for observable applications.

Declarative AI orchestration fully supports conditional execution flows. By defining workflows in the OpenProse language, you can create sequential, parallel, or conditional execution paths to handle complex automation logic.

Defining agent lifecycles with a declarative programming language moves beyond simple prompts to create robust AI applications. It provides structured control over execution flow, state persistence, and error handling for complex workflows.