Parallel AI agent coding means running multiple AI coding agents on different tasks at the same time, usually inside the same project. Instead of one agent finishing task A before task B starts, several workers can move separate parts of the project forward concurrently.
The benefit is speed, but the risk is conflict. Parallel agents only help when their work is scoped, isolated, and reviewable. If every agent edits the same working tree, the result can be merge conflicts, duplicated changes, or unclear ownership.
Verdent's parallel workflow is built around planning and workspace isolation. A goal can be broken into subtasks, dispatched to workers, and tracked while each workspace stays separate through git worktrees. That lets teams use parallelism for frontend and backend work, test expansion, refactors, and experiments without merging everything blindly.
