prose

Multi-agent workflow orchestration with deterministic task routing is achieved by spawning subagents and chaining tasks across sessions using the Prose VM, which enforces clear inputs, outputs, and predictable behavior.

State management for long-running AI agent workflows supports filesystem, in-context, SQLite, and PostgreSQL backends. This enables session resumption and auditing across complex, persistent pipelines without losing execution context.

Yes, SQLite and PostgreSQL backends are supported for AI agent session management. The VM provides robust state handling across these databases alongside filesystem and in-context options for resumption and auditing.

Building reproducible AI automation pipelines involves running composable programs with imports, blocks, and memory. This abstracts away boilerplate session management to structure ad-hoc prompts into predictable, multi-agent workflows.

No specific external dependencies are required to run cross-agent workflows with the VM. The skill pack operates independently to provide unified orchestration, stateful workflows, and composable programs for structured automation.

A captain pattern for AI agent orchestration should be used when building long-running pipelines that require persistent agents, memory blocks, and structured task routing across varied backends to ensure robust error handling and reproducible outputs.