prose

You orchestrate AI agents by writing declarative programs that define agent behavior, control flow, and data passing. The system manages agent definitions, session spawning, parallel execution, loops, conditionals, and state persistence.

AI agent orchestration coordinates multiple specialized agents within a unified workflow. You need it when automating complex processes requiring sequential tasks, parallel execution, or conditional logic across different AI models.

Yes, state persistence supports both file-based and database backends. This allows orchestrated AI agents to maintain context management, session spawning, and recursive workflow states across execution cycles.

You automate multi-agent workflows by using a declarative syntax to define sequences, parallel tasks, loops, and conditional logic. This enables complex operations like automated code review, issue identification, and summary generation.

Yes, the orchestration framework supports parallel execution, error handling, and recursive workflows. It allows you to define custom agents, manage their prompts, and control their execution flow.

The best way to coordinate agents for code review is writing a declarative program where one agent identifies issues, another suggests fixes, and a third generates a summary report, all managed through structured orchestration.