prose

You can coordinate multiple AI agents in a parallel workflow by using a VM orchestrator that spawns subagents and manages their interactions through configurable state backends like SQLite, PostgreSQL, or in-context memory.

The captain-pattern for multi-agent orchestration is an automation workflow where a formal VM coordinates sessions, spawns subagents for parallel execution, and manages persistent memory across long-running projects.

You manage persistent state across multiple AI agent runs by configuring a formal VM execution model with filesystem, SQLite, or PostgreSQL backends to track context bindings and session memory.

Yes, you can execute parallel research branches with deterministic state tracking by applying a VM orchestrator that enforces explicit imports, blocks, and context bindings for robust multi-step automation.

Multi-agent workflow orchestration works with PostgreSQL backends, alongside filesystem, SQLite, and in-context memory options, to support persistent state tracking and cross-agent coordination across sessions.

A formal VM provides deterministic execution, explicit session management, and robust state tracking for complex multi-step orchestrations, overcoming the context and memory limitations of basic agent chaining.