Multi-Agent
Parallel execution.
Professional scale.
One agent on one task is fine for small work. Real projects require parallel execution — five agents running simultaneously on frontend, backend, tests, docs, and bug fixes. Parallel means faster. Vera Studio makes parallel easy.
This is professional orchestration built by people who’ve managed distributed systems at scale. Not a toy that lets you run two things at once. Real infrastructure for coordinating dozens of agents across complex, multi-day projects.
How it works
Professional coordination.
Simple interface.
Orchestrating parallel agents sounds complicated. It’s not — when the infrastructure is designed right. Each session is independent. Each has its own model, its own sandbox, its own context. You give it a focused task, set Auto mode, and move on.
This is applying distributed systems principles to AI agents: isolation, independent state, clear boundaries, controlled merge points. The same patterns professional engineers use to coordinate human teams, applied to AI workflows.
Create sessions
Open a new session for each task. Name it something useful.
Give focused tasks
One task per agent. Specific, scoped, and clear.
Set Auto mode
Agents execute freely without asking for permission on every step.
Monitor from Grid
The Grid view shows all running agents with live status at a glance.
Review & merge
Each agent's work is isolated. Review diffs, approve, merge when ready.
Sub-Agents
Agents that delegate.
Like real teams.
A parent agent can decompose a large task, spawn child agents to handle subtasks, and coordinate the results. The parent monitors progress. The children execute in parallel. When they’re done, the parent merges the work.
This is how professional teams work: senior engineer breaks down the project, delegates to specialists, coordinates integration. The difference is that Vera Studio makes it work for AI agents without requiring you to understand distributed systems architecture.
- Parent agent decomposes complex tasks automatically
- Children run in parallel, each in its own sandbox
- Parent monitors progress and coordinates merging
- Full agent tree visible in the dashboard with live status
- Nested delegation — children can spawn their own children
Model routing
The right model for each agent.
Not every task needs Opus. Not every agent should run on the same model. Vera Studio lets you pick the model per agent — so architecture work uses Opus, implementation uses Sonnet, and grunt work uses Haiku.
This is professional judgment about tools and cost. Use the expensive model where it delivers 10x value. Use the cheap model where it’s 90% as good. Don’t overpay for tasks that don’t need genius. Don’t underpay for tasks where quality compounds.
Opus
Architecture & planning
System design, complex refactors, multi-file coordination. The tasks where getting it right the first time matters more than speed.
Sonnet
Implementation & features
Building features, writing components, implementing APIs. The daily driver. Fast, capable, and cost-effective for the bulk of the work.
Haiku
Grunt work & cleanup
Renaming files, fixing imports, updating configs, writing boilerplate. The tasks that don’t need a genius — just speed and accuracy.
Capabilities
Every agent has professional tools.
Every agent gets the complete toolkit: file operations, shell commands, code search, Git, web browsing, MCP tool integrations, image analysis, and multi-file coordination. No tiered access. No “upgrade to unlock features.” Professional capabilities available to every agent, every time.
This is what a professional studio provides: the right tools for the job, always available, never gated. The limitation is the task scope you define, not the capabilities the tool withholds.
File Operations
Read, write, edit, and search files across the entire project.
Shell Commands
Run any terminal command. Install packages, run tests, start servers.
Code Search
Grep across the codebase. Find references, patterns, and dependencies.
Git Operations
Commit, branch, diff, and manage version control automatically.
Web Browsing
Fetch documentation, check APIs, research solutions on the web.
MCP Tools
Connect to Figma, Stripe, Slack, databases — any MCP-compatible service.
Image Analysis
Read screenshots, mockups, and design files to inform implementation.
Multi-File Edits
Coordinate changes across dozens of files in a single session.
Isolation
Every agent gets its own sandbox.
Each agent works in an isolated Git worktree — a complete copy of the project that doesn’t interfere with any other agent. No merge conflicts mid-session. No stepping on each other’s toes. When an agent finishes, you review its diff and merge on your terms.
This is professional version control infrastructure. Not Docker containers with shared state. Not file locks that break when something crashes. Real Git isolation that professional developers trust, made accessible to AI agents.
- Each agent gets a full, isolated copy of the codebase
- Changes are isolated until you choose to merge them
- No merge conflicts between parallel agents
- Clean diffs make code review straightforward
- Works with any Git repo — no special setup required
Modes
Control how much freedom
each agent gets.
Different tasks require different levels of autonomy. Architecture work needs review. Grunt work needs speed. Sensitive operations need oversight. Set the mode per agent, per session, based on what the work requires.
Professional teams don’t give the same autonomy to every task. Junior engineers get more oversight. Routine work gets less. Vera Studio applies the same principle to AI agents: match autonomy to risk and complexity.
Plan
Agent proposes a plan before making any changes. You review and approve before it writes a single line.
Interact
Agent asks permission before each action. Good for sensitive operations where you want oversight on every step.
Auto
Full autonomy. Agent executes freely until the task is done. The mode you want for parallel workflows — set it and walk away.
Professional orchestration.
At scale.
Run five agents at once. Each isolated. Each focused. Each using the right model for the job. Professional coordination infrastructure built for real work, not toy demos.