multi-agent-orchestration

Multi-agent orchestration coordinates specialized AI agents by assigning roles like Planner, Builder, and Reviewer to handle different development stages simultaneously. It uses Git worktree isolation to ensure parallel agents work in separate directories without overwriting each other's changes.

To run full-stack feature development without file conflicts, use Git worktree isolation to separate parallel agents into distinct directories. This allows frontend and backend builders to work simultaneously while a planner designs the architecture and a reviewer checks all code before merging.

Yes, you can use specialized AI agent roles for automated code review cycles. The orchestration workflow supports review loops where a dedicated Reviewer agent checks code generated by Builder agents, ensuring quality control before any changes merge to the main branch.

Git worktree isolation works by creating separate working directories for each parallel AI agent. This mechanism eliminates file conflicts and coordinates cross-agent task dependencies, allowing multiple agents to modify code simultaneously without overwriting each other's changes during complex development workflows.

Yes, multi-agent orchestration supports sequential pipelines for technical architecture design. The flexible workflow orchestration includes multiple execution modes such as sequential pipelines, parallel module development, review loops, and exploratory technical research to suit different project requirements.

You should not use a coordinated specialist team of AI agents for simple, single-disciplinary tasks that do not require specialized skill sets. The orchestration overhead is designed for complex, multi-faceted projects where sequential work by a single AI agent creates bottlenecks and inefficiency.