trigger-agents

You can orchestrate AI agent workflows by coordinating tasks, parallel workers, routing, and tool calls using Trigger.dev patterns. This approach supports multi-model prompts and deterministic execution across services.

Adding human-in-the-loop gates to an AI agent workflow is achieved using Trigger.dev waitpoints. These waitpoints allow real-time streaming and tool integration to pause execution for manual review.

Implementing an orchestrator-workers pattern involves coordinating multiple tasks and parallel workers across different models and handlers. Trigger.dev patterns provide typed task schemas and robust error handling for this dynamic automation.

Yes, Trigger.dev patterns enforce typed task schemas and observable patterns to ensure deterministic execution of complex AI orchestrations. This provides robust error handling across multi-model tasks and services.

Orchestrating AI agents with Trigger.dev supports end-to-end patterns including evaluator-optimizer and AI-tool usage. These patterns enable dynamic automation and robust agent workflows with real-time streaming.

Typed task schemas are needed when you require deterministic execution and robust error handling in AI agent orchestration. They enforce observable patterns using Trigger.dev primitives across complex multi-model workflows.