agentbuilder

To build scalable AI agent graphs, you create a central coordinator that defines subagents and subprompts, then expose the agent as a tool. This orchestrates providers, hooks, effects, threads, and endpoints into a modular, repeatable system.

A Standard Agent stack is a structured architecture covering providers, prompts, tools, agents, hooks, effects, threads, and endpoints. It provides a clear blueprint for organizing complex AI systems with defined model selection and environment configurations.

Configuring agent handoffs and dual_ai collaborations requires clear definitions in prompts and agent configurations. You orchestrate these connections by composing subagents into a full agent graph, ensuring safe composition and modularity across varied domains.

Yes, you can design a central coordinator to delegate tasks to subagents. You define the subagents and prompts, then expose the coordinator as a tool, allowing the full Standard Agent stack to orchestrate complex tasks with clear interconnections.

The best way to organize prompts and tools for modular AI systems is applying a structured blueprint that emphasizes modularity and repeatability. You compose subprompts and define tool configurations to ensure safe composition and scalable agent orchestration.

You should avoid subagent architectures when your AI system lacks clear definitions for prompts and configurations. Without the need for orchestrated handoffs, dual_ai collaborations, or multi-layer task delegation, the overhead of composing a full agent graph is unnecessary.