subagent-driven-development

You coordinate multiple AI agents by decomposing a large software task into subtasks and dispatching them to specialized implementer and reviewer agents. This orchestration manages iterative refinement loops to ensure code quality and spec compliance.

Subagent-driven development is a workflow where complex software tasks are broken down and assigned to specialized AI subagents. One agent writes code, another writes tests, and a third reviews both, iterating until all requirements are met.

You automate iterative refinement by dispatching implementer and reviewer AI agents in feedback loops. The reviewer agent evaluates the generated code and tests against defined interfaces, feeding corrections back until quality goals are achieved.

Yes, orchestrating AI subagents requires defined interfaces, test strategies, and a robust review process. These prerequisites ensure the coordinated agentic execution maintains spec compliance and code quality throughout development.

Yes, you can use agent orchestration for multi-stage API endpoint development by assigning specialized subagents to handle coding, testing, and review. This coordinates the entire implementation process through iterative refinement cycles.

The limitation of using specialized AI subagents is the strict requirement for defined interfaces and robust review processes. Without a solid test strategy, the iterative refinement cycles cannot guarantee spec compliance or code quality.