What This Stack Does
This stack is for teams running more than one coding agent against the same repository. Conductor.build provides the worktree-per-agent workspace, Vibe Kanban gives task visibility, Claude Code performs the terminal implementation, Checkpoints gives rollback points, Cursor handles IDE-level review, and GitHub Actions enforces the merge gate after humans choose which lane wins.
The differentiator is isolation. A single shared worktree encourages agents to overwrite each other, hide context in terminal scrollback, and produce merge conflicts that look like model quality problems. A worktree command center turns parallelism into an operating model: one owner, one branch, one task card, one checkpoint, and one CI result per lane.
Worktree Isolation with Conductor
Conductor.build anchors the workflow because it exposes separate workspaces for simultaneous agent sessions. Use one worktree for a feature, one for a bugfix, and one for a refactor spike, then promote only the branch whose diff and CI results survive review. The base tool entry currently records Conductor as a free app with BYO Claude or Codex subscription/API key.
The operating rule is strict: no agent edits the main working tree, and no two agents share the same branch. That rule sounds basic, but it is what lets a lead engineer compare outputs cleanly, abandon a weak lane without cleanup drama, and keep secrets or generated artifacts from bleeding across independent experiments.
Agent Board and Rollback Discipline
Vibe Kanban is the control plane. Every agent gets a card with scope, files to avoid, acceptance criteria, and a review owner. The board matters because parallel agents fail silently when nobody can see which lane is blocked, which lane already changed a dependency, and which lane is still hallucinating around an outdated task description.
Checkpoints is the rollback layer for risky local edits. Place a checkpoint before broad migrations, dependency upgrades, generated code rewrites, and any task that touches authentication, billing, or deployment files. The goal is not to avoid risk; the goal is to make each lane discardable when it drifts from the acceptance criteria.
Implementation, IDE Review, and CI Gates
Claude Code is the primary executor in this stack because terminal agents can read, edit, test, and iterate quickly inside each worktree. Keep sessions small: one vertical change, one test command, one PR-ready summary. If an agent needs to touch a shared interface, pause the other lanes or rebase intentionally instead of letting conflicts accumulate.
Cursor is the review surface after the agent has produced a coherent diff. Use it for cross-file inspection, inline follow-up prompts, and final cleanup before the branch enters GitHub Actions. Actions then becomes the non-negotiable merge gate: required tests, lint, build, and deployment checks decide whether the candidate lane is promotable.
Cost, Secrets, and Team Controls
The budget is dominated by human and model seats. Cursor’s current base entry records Hobby, Pro at $20/mo, Pro+ at $60/mo, and Ultra at $200/mo; Claude usage depends on Pro, Max, or API consumption; GitHub Actions private-repo minute pools vary by plan, with the base entry recording 2,000 Free, 3,000 Pro/Team, and 50,000 Enterprise Cloud minutes per month.
Secrets are the enterprise pitfall. Do not clone production credentials into every secondary worktree, do not let agents copy .env files between lanes, and do not run deployment commands from exploratory branches. Give each lane the minimum local configuration needed to build and test, then reserve release credentials for the final reviewed branch.
When to Use It and When to Stay Solo
Use this stack when the repo has enough parallelizable work to justify coordination: UI polish beside backend fixes, test hardening beside dependency upgrades, or two alternative implementations of the same feature. It is also the right pattern for staff engineers who want to compare agent outputs without losing the ability to audit each branch independently.
Stay with a solo-agent workflow when the codebase is small, the task crosses one fragile subsystem, or the team cannot review multiple diffs quickly. Parallelism creates leverage only when ownership, worktrees, checkpoints, and CI are already disciplined; without that operating system, it multiplies token spend and merge cleanup instead of shipping faster.