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Parallel exploration of multiple solution variants is achieved by spawning isolated AI agents on separate git worktrees, allowing side-by-side comparison of divergent design directions before selecting the best approach.

The best way to compare refactoring strategies is using multi-agent parallel exploration, which generates distinct variant notes and outputs across isolated worktrees to evaluate different angles for the same task safely.

Worktree isolation and port management are handled automatically during multi-agent variant generation, ensuring each AI variant operates independently without conflicts until final convergence or rollback.

Yes, you can converge by merging the winning variant back into the main branch or cherry-picking components, with automatic cleanup of all temporary worktrees ensuring a safe rollback if needed.

Yes, parallel AI variant generation applies to UI, product, and engineering challenges, orchestrating multiple agents to explore divergent design directions and evaluate multi-solution outputs for complex tasks.

You should avoid spawning isolated worktrees for multi-agent code generation when a task requires a single deterministic path, as this approach is designed for divergent design iteration and multi-solution evaluation.