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Spec-driven development workflow orchestration coordinates tasks across distinct planning, implementation, verification, and learning phases. It delegates specialized tasks to assigned AI agents using MCP tools while enforcing project governance and managing state transitions.

A spec-driven workflow for software development streamlines complex feature creation by defining strict specifications first. It enforces project governance early in planning, delegates implementation to specialized agents, verifies results, and extracts learnings to improve future development cycles.

Task delegation to specialized AI agents is managed by intelligently assigning implementation tasks, such as backend engineering or UX design, through MCP tools. The workflow ensures agents operate within governance constraints during the implementation phase.

Project governance checks are enforced during the planning phase of agent orchestration. The workflow requires strict adherence to a predefined execution protocol, integrating governance validation early before any implementation tasks are delegated to specialized agents.

Spec-driven agent orchestration supports code review verification through a dedicated workflow phase. After implementation agents complete their tasks, a reviewer agent verifies the output against the initial specification before the workflow transitions to the learning phase.

Predefined execution protocols for development workflows require strict adherence across all phases, limiting flexibility for ad-hoc changes. The orchestration depends on distinct phase transitions and MCP tool availability, making it less suitable for unstructured or highly dynamic development processes.