Overview
The Batch Builder enables large-scale autonomous code generation across entire projects. Define a BatchSpec describing your target application, and VibeCody orchestrates up to 10 specialized agent roles through an architecture plan, module plan, and code generation pipeline. Runs can target 3M+ lines of output over 8-12 hours, with full pause/resume/cancel support and checkpoint intervals.
Prerequisites
- VibeCLI installed and on your PATH
- At least one AI provider configured (e.g.,
ANTHROPIC_API_KEYorOPENAI_API_KEY) - For VibeUI: the desktop app running with the Batch Builder panel visible
Step-by-Step Walkthrough
1. Create a BatchSpec
Define the scope of your batch run. A BatchSpec includes target modules, estimated line counts, and which agent roles to activate.
CLI:
vibecli --batch create --name "ecommerce-platform" \
--target-lines 500000 \
--roles architect,frontend,backend,database,api,auth,testing,devops,docs,qa \
--checkpoint-interval 30m
VibeUI:
Open the Batch Builder panel and select the New Run tab. Fill in the project name, target line count, and toggle the agent roles you want to include. Click Create BatchSpec.
2. Review the Architecture Plan
Once the BatchSpec is created, the Architect agent produces an architecture plan that maps out the high-level structure: services, data models, APIs, and dependencies.
CLI:
vibecli --batch status ecommerce-platform --show-plan
VibeUI:
In the Monitor tab, expand the Architecture Plan section to review the generated service graph and module breakdown.
3. Start the Batch Run
Launch the autonomous run. All 10 agent roles work in parallel according to the architecture and module plans.
CLI:
vibecli --batch start ecommerce-platform
VibeUI:
Click Start Run in the Monitor tab. The progress bar and per-agent status indicators will update in real time.
4. Monitor Progress
Track each agent’s output, token usage, and completion percentage during the 8-12 hour run.
CLI:
vibecli --batch status ecommerce-platform
Example output:
Batch: ecommerce-platform
Status: Running (4h 12m elapsed)
Progress: 47% (235,000 / 500,000 lines)
Checkpoint: #8 (saved 2m ago)
Agent Roles:
Architect ████████████████████ 100%
Frontend ████████████░░░░░░░░ 62%
Backend ██████████░░░░░░░░░░ 51%
Database ████████████████████ 100%
API ████████████░░░░░░░░ 58%
Auth ██████████████░░░░░░ 72%
Testing ████████░░░░░░░░░░░░ 38%
DevOps ██████████████████░░ 90%
Docs ██████░░░░░░░░░░░░░░ 30%
QA ████░░░░░░░░░░░░░░░░ 22%
VibeUI:
The Monitor tab shows a live dashboard with per-agent progress bars, a timeline view of checkpoints, and token consumption graphs.
5. Pause and Resume
Interrupt a run without losing progress. The system saves a checkpoint before pausing.
CLI:
vibecli --batch pause ecommerce-platform
# Later...
vibecli --batch resume ecommerce-platform
VibeUI:
Click Pause in the Monitor tab toolbar. The run saves a checkpoint and halts. Click Resume when ready to continue.
6. QA Review
After the run completes (or at any checkpoint), review the generated code through the integrated QA pipeline.
CLI:
vibecli --batch status ecommerce-platform --qa-summary
VibeUI:
Switch to the QA Review tab to see severity-weighted scores, auto-fix suggestions, and cross-validation confidence ratings for each module.
7. Cancel a Run
If a run is no longer needed, cancel it cleanly.
CLI:
vibecli --batch cancel ecommerce-platform
8. View History
Browse past batch runs, their specs, and outcomes.
CLI:
vibecli --batch status --history
VibeUI:
The History tab lists all previous runs with their specs, durations, line counts, and QA scores.
The 10 Agent Roles
| Role | Responsibility |
|---|---|
| Architect | High-level design, service boundaries, data models |
| Frontend | UI components, pages, styling, client state |
| Backend | Business logic, service layer, middleware |
| Database | Schema design, migrations, queries, indexes |
| API | REST/GraphQL endpoints, request validation |
| Auth | Authentication, authorization, RBAC, session mgmt |
| Testing | Unit tests, integration tests, E2E tests |
| DevOps | CI/CD pipelines, Docker, K8s manifests, IaC |
| Docs | API docs, README files, architecture decision records |
| QA | Code review, quality scoring, auto-fix suggestions |
Pipeline Flow
BatchSpec → Architect → ArchitecturePlan → ModulePlan → [10 Agents in parallel] → Code Output
↓
Checkpoint saved every N minutes
↓
QA Review & Scoring
Demo Recording JSON
{
"demo_id": "31-batch-builder",
"title": "Batch Builder",
"version": "1.0.0",
"steps": [
{
"action": "cli_command",
"command": "vibecli --batch create --name demo-app --target-lines 100000 --roles architect,frontend,backend,testing --checkpoint-interval 15m",
"description": "Create a BatchSpec with 4 agent roles"
},
{
"action": "cli_command",
"command": "vibecli --batch start demo-app",
"description": "Start the autonomous batch run"
},
{
"action": "cli_command",
"command": "vibecli --batch status demo-app",
"description": "Monitor progress and per-agent status"
},
{
"action": "cli_command",
"command": "vibecli --batch pause demo-app",
"description": "Pause the run with a checkpoint"
},
{
"action": "cli_command",
"command": "vibecli --batch resume demo-app",
"description": "Resume from the last checkpoint"
},
{
"action": "cli_command",
"command": "vibecli --batch status demo-app --qa-summary",
"description": "Review QA scores after completion"
},
{
"action": "vibeui_interaction",
"panel": "BatchBuilder",
"tab": "New Run",
"description": "Create a BatchSpec using the GUI form"
},
{
"action": "vibeui_interaction",
"panel": "BatchBuilder",
"tab": "Monitor",
"description": "Watch live progress dashboard with per-agent bars"
},
{
"action": "vibeui_interaction",
"panel": "BatchBuilder",
"tab": "QA Review",
"description": "Review auto-fix suggestions and quality scores"
},
{
"action": "vibeui_interaction",
"panel": "BatchBuilder",
"tab": "History",
"description": "Browse past batch runs and outcomes"
}
]
}
What’s Next
- Demo 32: Legacy Migration – Migrate legacy codebases with the batch pipeline
- Demo 33: App Builder – Scaffold full applications from natural language descriptions
- Demo 34: Usage Metering – Track token usage and budgets across batch runs