Common questions about Maestro and how it works.

What Is Maestro?

What exactly is Maestro?

Maestro is a conversational AI Engineer that delivers from deep research to validated, production-ready code. It goes beyond code generation to handle planning, implementation, testing, documentation, and delivery of complete features and systems. Think of Maestro as an engineering teammate, not a coding tool.

How is Maestro different from GitHub Copilot or Cursor?

FeatureCopilot/CursorMaestro
ScopeCode suggestions and autocompleteComplete feature implementation
ValidationYou test the codeMaestro tests its own code
PlanningYou plan the implementationMaestro plans with you
TestingYou write and run testsMaestro writes and runs tests
DeliveryCode snippetsProduction-ready features
ContextCurrent file + nearby filesEntire project, full iteration history
Summary: Copilot/Cursor are coding assistants. Maestro is an engineering partner.

Is Maestro a chatbot that writes code?

No. Maestro is a system that orchestrates multiple specialized models, execution environments, and validation tools to deliver complete solutions. Architecture:
  • Multiple LLMs, each optimized for specific tasks (research, coding, verification, optimization)
  • Secure sandboxes for testing and validation
  • Rich toolbox for file management, web research, visualization
  • Quality oversight and validation layers
You interact through conversation, but Maestro is executing complex orchestration underneath.

Can non-developers use Maestro?

Maestro is designed for technical professionals who understand:
  • Software requirements and architecture
  • Testing and validation concepts
  • Code quality and performance
Minimum technical literacy:
  • Understand what good code looks like
  • Recognize test failures
  • Evaluate performance metrics
  • Make technical trade-off decisions
If you’re not technical: Maestro may be overwhelming. It’s optimized for engineering professionals who know what they want but need help executing.

How Maestro Works

How does Maestro actually work?

Orchestration layer coordinates:
  1. Research models: Gather information, analyze approaches
  2. Planning models: Design systems, create specifications
  3. Implementation models: Write code, refactor, optimize
  4. Validation models: Review code, flag issues, ensure quality
Execution environment:
  • Isolated Ubuntu Linux sandboxes
  • Real code execution and testing
  • Performance benchmarking
  • Validation of claims
Toolbox:
  • File management and analysis
  • Terminal access and execution
  • Web research and browsing
  • Visualization and diagramming
  • External service integration
You collaborate by setting goals, reviewing proposals, validating outcomes, and maintaining quality standards.

Do I need to write any code?

No. Your role shifts from writing syntax to:
  • Defining goals and constraints
  • Making architectural decisions
  • Reviewing and validating implementations
  • Ensuring quality standards
  • Providing domain expertise
You guide, Maestro implements. However, you should understand code well enough to:
  • Review Maestro’s implementations
  • Spot logical errors
  • Validate test coverage
  • Make informed technical decisions

Does Maestro make mistakes?

Yes. Maestro is powerful but not infallible:
  • Can misunderstand requirements
  • May choose suboptimal approaches
  • Sometimes needs multiple attempts
  • Occasionally makes logical errors
Your job: Catch mistakes, provide correction, demand higher quality. Built-in safeguards:
  • Systematic testing
  • Multi-model validation
  • Quality oversight
  • Your review
Best practice: Treat Maestro’s output skeptically until proven with tests and validation.

Can Maestro learn from my feedback?

Within a session: Yes
  • Maestro incorporates feedback immediately
  • Adjusts approach based on corrections
  • Learns your preferences and patterns
  • Improves throughout the session
Across sessions: Limited
  • General knowledge doesn’t transfer between sessions
  • Each session starts fresh
  • But you can provide context via custom instructions
Your project patterns: Can be encoded as custom instructions that apply across sessions.

Use Cases and Capabilities

What kinds of projects can Maestro complete?

Software development:
  • REST APIs and web services
  • Full-stack applications
  • Database schemas and migrations
  • Authentication and authorization systems
  • Caching layers and performance optimization
  • Integration with third-party APIs
Data engineering:
  • ETL pipelines
  • Data transformation logic
  • Quality validation systems
  • Data analysis workflows
Machine learning:
  • Model training pipelines
  • Feature engineering
  • Inference services
  • ML model optimization
DevOps and infrastructure:
  • CI/CD pipeline configuration
  • Deployment automation
  • Infrastructure as Code
  • Monitoring and alerting
Analysis and research:
  • Competitive technical analysis
  • Performance benchmarking
  • Root cause investigation
  • Technology evaluation
Limitations: Maestro works best on projects that can be validated in sandboxes. Projects requiring specialized hardware, proprietary systems, or external dependencies may be challenging.

Can I use Maestro with my existing codebase?

Yes. Maestro supports:
  • GitHub integration: Clone any repository (public or private)
  • Direct upload: Zip or tar your codebase, Maestro extracts it
  • Gradual integration: Start with analysis, then implement changes
Best results with:
  • Well-tested codebases (Maestro preserves test behavior)
  • Clear documentation (helps Maestro understand)
  • Consistent patterns (easier to follow and extend)
Challenges with:
  • Poorly documented legacy code
  • No tests (hard to validate changes)
  • Highly coupled architecture
  • Unusual or proprietary frameworks
Recommendation: Even challenging codebases benefit, but expect more iteration and validation.

What if my codebase is too large for Maestro?

Current limit: Repositories up to ~10GB For larger codebases:
  • Clone subsets: Work on specific modules/services
  • Parallel sessions: Different parts in different sessions
  • Strategic cloning: Clone only what’s needed for current work
Future: Support for larger repositories is planned.

Can Maestro work with multiple repositories?

Yes. Common patterns: Microservices:
Clone all relevant service repositories
Implement changes across services
Create coordinated PRs
Link PRs for review coordination
Monorepo subsystems:
Clone monorepo once
Work on different subsystems
File management keeps work organized
Frontend + Backend:
Clone both repositories
Coordinate API changes
Implement frontend consuming new API
Create PRs for both with cross-references

Integration and Tooling

What tools and integrations are supported?

Source control:
  • GitHub (native integration)
  • GitLab (API access)
  • Bitbucket (git operations)
Cloud providers:
  • AWS (S3, EC2, Lambda, etc.)
  • Azure (Blob Storage, VMs, etc.)
  • GCP (Cloud Storage, Compute Engine, etc.)
Databases:
  • PostgreSQL, MySQL, SQLite
  • MongoDB, Redis, Memcached
  • Any database accessible via connection string
APIs and services:
  • OpenAI, Anthropic (AI APIs)
  • Stripe (payments)
  • SendGrid, Mailgun (email)
  • Custom REST/GraphQL APIs
Development tools:
  • Package managers (pip, npm, cargo, go get)
  • Test frameworks (pytest, jest, go test, etc.)
  • Build tools (webpack, vite, cargo, maven)
  • CI/CD (GitHub Actions compatible)
Browsers and web:
  • Automated browser control
  • Screenshot capture
  • Web scraping
  • Public URL access

Can I integrate Maestro with Slack/Discord/Teams?

Notifications: Yes, push notifications can integrate with messaging platforms. Chat integration: Multi-channel support is possible, but direct Slack/Discord bots require configuration beyond standard Maestro. Workaround: Use Maestro via web interface, share results in chat.

Can Maestro access private resources?

Yes, with proper credential setup:
  • Private GitHub repos: OAuth authentication
  • Private APIs: API keys via credential manager
  • Internal databases: Connection strings (ensure network access)
  • VPNs: SSH sandboxes can connect through jump hosts
Security: All credentials user-controlled, session-scoped, never logged.

Security and Privacy

Is Maestro secure?

Yes. Enterprise-grade security model: Isolation:
  • Dedicated sandbox per session
  • Process isolation between users
  • Credential isolation per session
Credentials:
  • Encrypted at rest
  • User-controlled activation
  • Never logged or shared
  • Automatic cleanup
Code execution:
  • Sandboxed Firecracker microVMs
  • No access to host system
  • Limited resource quotas
  • Network isolation options
Data handling:
  • Your code never used for training
  • Sessions completely isolated
  • Optional data persistence (you control)

Does Maestro learn from my code?

No. Maestro does not train on user data. What persists:
  • Your session state (if you choose to save it)
  • Files you create (in your session only)
  • Clone records (for your sessions only)
What doesn’t persist across sessions/users:
  • Code patterns you use
  • Architectural choices
  • Domain knowledge
  • Anything from your work
Privacy guarantee: Your data is private. Each session is isolated.

Can other users see my code?

No. Complete isolation:
  • Sessions are private to your account
  • Other users cannot access your sessions
  • Other users cannot see your files
  • Other users cannot view your history
Collaboration: Explicitly share session access if needed (enterprise features).

What happens to my data if I cancel my subscription?

Depends on data persistence settings:
  • Checkpointed sessions: Preserved per retention policy (typically 30-90 days)
  • Deleted sessions: Immediate removal on request
  • Exported files: You keep what you downloaded
Best practice: Use /download-all before cancelling to preserve your work.

Billing and Plans

How much does Maestro cost?

Pricing model: Monthly subscription with credit-based usage Plan tiers (example structure):
  • Basic: $X/month + Y credits
  • Pro: $X/month + Y credits
  • Ultimate: $X/month + Y credits
Credits cover:
  • Model API calls (passed through at cost, no markup)
  • Sandbox compute time
  • Storage (files and checkpoints)
Visit: https://igent.ai/ for current pricing

How do credits work?

Credit consumption:
  • Different models cost different amounts
  • Longer responses cost more (more tokens)
  • Sandbox execution time counted
  • Storage and bandwidth included up to limits
Credit management:
  • Track balance in UI
  • Low balance warnings
  • /topup command for quick refill
  • Optional auto-reload (configure in settings)
No surprises:
  • Real-time credit usage shown
  • Warnings before large operations
  • Control credit consumption via session management

Do I need my own OpenAI/Anthropic accounts?

No. Maestro handles all model calls:
  • We manage API accounts
  • We orchestrate model calls
  • We pass through costs to your credits
  • No markup: You pay model cost + platform fee
Advantage: No need to manage multiple API accounts, rate limits, or billing.

Can I control costs?

Yes, several ways: Session management:
  • Shorter sessions cost less
  • /compact and /forget reduce ongoing costs
  • /refresh reduces token usage per turn
Tool selection:
  • Disable expensive tools if not needed
  • Use faster tools when appropriate (Google vs Perplexity)
  • Limit sandbox usage for non-execution tasks
Model selection (if configurable):
  • Use cheaper models for simple tasks
  • Use premium models for complex reasoning
Auto-reload threshold:
  • Set maximum auto-reload amount
  • Prevent runaway costs
  • Manual approval for large expenses

Session and State

How long can sessions run?

Technically: Days to weeks
  • Sessions checkpoint automatically
  • Resumable across long periods
  • Context preserved
Practically: Most sessions complete in hours
  • Complex projects: Multiple focused sessions better than one massive session
  • Capacity management: Easier with bounded sessions
  • Checkpointing: Natural session boundaries
Record: Some users have single sessions spanning 100+ turns over multiple days.

Can I have multiple sessions?

Yes. Parallel sessions are common: Use cases:
  • Different features in parallel
  • Separate concerns (frontend vs backend)
  • Experimental vs production work
  • Personal vs work projects
Isolation: Sessions are completely independent.

What happens if my browser crashes?

Session state preserved:
  • Automatic checkpointing saves state
  • Refresh browser to reload session
  • Complete history restored
  • Work continues from where you left off
Sandbox state:
  • Running processes continue
  • Files preserved
  • Terminal state maintained
Interruption-safe: Maestro designed for this.

Can I access my session from different devices?

Yes. Multi-device support:
  • Same session on desktop, laptop, tablet, phone
  • Synchronized state across all devices
  • Answer asks from any device
  • Real-time updates
Use case: Start on desktop, check progress on phone, resume on laptop.

Performance and Scale

How fast is Maestro?

Varies by task:
  • Simple code generation: Seconds
  • Complex feature implementation: Minutes to hours
  • Research and analysis: Seconds to minutes
  • Test execution: Depends on your tests
Factors:
  • Model latency (inherent to LLMs)
  • Sandbox execution time (real code takes real time)
  • Validation thoroughness (quality over speed)
Optimization: Maestro prioritizes correctness over speed. Fast but wrong is useless.

Can Maestro handle large codebases?

Current capabilities:
  • Repositories up to ~10GB
  • Thousands of files
  • Complex architectures
Context management:
  • View files selectively
  • Use file search and analysis
  • Pattern-based operations
Best results:
  • Well-structured codebases
  • Clear module boundaries
  • Good documentation
If very large: Consider subsystem-focused sessions.

What are Maestro’s limits?

Technical limits:
  • Repository size: ~10GB
  • Session capacity: Token-based (manage via commands)
  • Sandbox resources: 2 vCPU, 7 GB RAM default
  • Public ports: Port 8080 only
  • GPU: Not yet available
Practical limits:
  • Works best on validatable projects
  • Requires testable implementations
  • Benefits from clear requirements
  • Best with existing test infrastructure
Not limits:
  • Number of sessions
  • Session duration
  • Complexity of problems
  • Number of tools used

Working with Maestro

When should I use Maestro vs writing code myself?

Use Maestro when:
  • Implementing complete features (not tiny changes)
  • Need systematic validation (comprehensive testing)
  • Working across many files
  • Tackling unfamiliar domains
  • Want evidence-driven development
  • Speed matters (weeks → days compression)
Use your IDE when:
  • Trivial changes (button color, typo fix)
  • You already know exact implementation
  • Rapid experimentation (trying something quickly)
  • Preference for hands-on coding
Hybrid approach: Many users use both—Maestro for heavy lifting, IDE for final polish.

How much should I guide vs let Maestro decide?

Depends on:
  • Your experience with Maestro
  • Complexity of problem
  • Familiarity with domain
  • Risk tolerance
General guideline:
  • Set goals clearly (what success looks like)
  • Define constraints (what must/must not happen)
  • Let Maestro propose approaches (leverage its knowledge)
  • Validate thoroughly (evidence required)
Over time: You’ll develop intuition for when to intervene vs delegate.

What if Maestro goes off track?

Immediate correction:
"Stop. This is going in the wrong direction. [Explain correct path]. Reset and start from [point]."
Maestro will:
  • Acknowledge the correction
  • Adjust approach
  • Continue with new understanding
Prevention:
  • Correct misunderstandings early
  • Provide clear constraints upfront
  • Validate at milestones, not just end

Can Maestro work without internet?

No. Maestro requires internet for:
  • Model API calls (core functionality)
  • Sandbox connectivity
  • Web research tools
  • External service integration
Offline work: Not supported currently.

Data and Privacy

Where is my code stored?

During session:
  • In your session state (cloud-hosted)
  • In sandbox (temporary, isolated)
  • Checkpoints (if persistence enabled)
After session:
  • Checkpoints preserved per retention policy
  • Or immediately deleted (your choice)
  • Downloaded files on your machine
Security:
  • Encrypted in transit and at rest
  • Access controlled
  • Isolated per user

Can I delete my data?

Yes. Data deletion:
  • Delete individual sessions
  • Clear all session data
  • Remove checkpoints
  • Request complete account data deletion
Immediate effect: Data removed from active systems. Backups: May persist in backups for limited time per retention policy.

Is my session visible to iGent AI staff?

Normal operation: No
  • Automated systems only
  • No human access to session content
Support requests: Only with your permission
  • If you request support
  • With explicit consent
  • Limited to debugging specific issue
Monitoring: Aggregate metrics only (no content)

Billing and Costs

How are credits charged?

Usage-based charges:
  • Model API calls (varies by model)
  • Sandbox compute time
  • Storage and bandwidth
Factors affecting cost:
  • Session length (more turns = more cost)
  • Model choice (some models more expensive)
  • Sandbox usage (execution time)
  • File storage size
Optimization:
  • Manage capacity to reduce token usage
  • Use appropriate models for tasks
  • Minimize unnecessary sandbox operations

What if I run out of credits mid-session?

Low balance warning: Notification before credits exhausted Options:
  1. /topup command for quick credit purchase
  2. Auto-reload (if configured) purchases credits automatically
  3. Pause session until credits added
Session preservation: Session state saved even if credits depleted

Can I get refunds for unused credits?

Policies vary: Check current terms at https://igent.ai/ Typical policies:
  • Subscription fees: Subject to cancellation policy
  • Unused credits: May or may not roll over (plan-dependent)
  • Refunds: Per terms of service
Recommendation: Review billing policies before subscribing.

Technical Questions

What programming languages does Maestro support?

Fully supported (with syntax highlighting, tools, validation):
  • Python
  • JavaScript/TypeScript
  • Go
  • Rust
  • Java/Kotlin
  • C/C++
  • Ruby
  • PHP
  • Shell scripting
Also works with:
  • Virtually any text-based language
  • Configuration formats (YAML, JSON, TOML, XML)
  • Markdown, HTML, CSS
  • SQL, query languages
Limitation: Language-specific IDE features (linting, autocomplete) are in sandbox, not UI.

Does Maestro support frameworks like React, Django, FastAPI?

Yes. Maestro has deep knowledge of major frameworks:
  • Frontend: React, Vue, Angular, Next.js, Svelte
  • Backend: Django, FastAPI, Express, Gin, Actix
  • Full-stack: Next.js, Nuxt, SvelteKit
  • Mobile: React Native, Flutter (code generation)
  • Data: Pandas, NumPy, PyTorch, TensorFlow
Framework-specific knowledge:
  • Idioms and best practices
  • Common patterns
  • Testing approaches
  • Performance optimization
  • Security considerations

Can Maestro help with mobile development?

Yes, for code generation and logic:
  • React Native (JavaScript/TypeScript)
  • Flutter (Dart)
  • SwiftUI/UIKit (Swift)
  • Jetpack Compose (Kotlin)
Limitations:
  • No mobile device emulator in sandbox
  • Cannot test iOS apps (requires macOS)
  • Android testing possible but limited
Best use cases:
  • Business logic implementation
  • API client code
  • State management
  • Unit tests
UI testing: Use external emulators or devices.

Does Maestro work with databases?

Yes. Database operations:
  • Schema design
  • Migration scripts
  • Query optimization
  • ORM integration (SQLAlchemy, Prisma, etc.)
Testing:
  • Local PostgreSQL/MySQL in sandbox
  • SQLite for testing
  • Can connect to external databases with credentials
Example:
"Design database schema for multi-tenant SaaS.

Requirements:
- PostgreSQL with row-level security
- Tenant isolation
- Migration scripts with Alembic
- Comprehensive tests

Validate by running migrations on test database in sandbox."

Comparison to Other Tools

Maestro vs Cursor

Cursor:
  • IDE extension
  • Real-time autocomplete
  • Fast inline suggestions
  • Works with your editor
Maestro:
  • Complete implementation partner
  • Autonomous execution and validation
  • Handles entire features
  • Includes testing and benchmarking
Use together: Cursor for inline editing, Maestro for feature implementation.

Maestro vs ChatGPT/Claude

ChatGPT/Claude:
  • General-purpose chatbots
  • Code generation via conversation
  • No execution environment
  • No validation
  • You copy/paste code
Maestro:
  • Specialized engineering system
  • Orchestrates multiple models
  • Executes and tests code
  • Validates all claims
  • Delivers tested, working code
Difference: Maestro proves code works, not just generates it.

Maestro vs Replit/Glitch

Replit/Glitch:
  • Browser-based IDEs
  • Good for prototyping
  • You write the code
  • Instant deployment
Maestro:
  • AI writes the code
  • Comprehensive testing
  • Production-ready output
  • Validation-first approach
Overlap: Both provide execution environments. Difference is who writes the code and to what standard.

Getting Help

I’m stuck. What should I do?

In order:
  1. Ask Maestro: “I’m stuck with [X]. How should I proceed?”
  2. Check documentation: Search for relevant topic
  3. Try different approach: “Let’s try a different way”
  4. Use commands: /reset-sandbox, /forget, /refresh
  5. Start fresh: New session with lesson learned
  6. Contact support: support@igent.ai
Usually: Maestro can help you get unstuck by reformulating the problem.

Something isn’t working as documented

First: Verify you’re following documentation correctly Then: Report the issue:
  • What documentation says
  • What actually happened
  • Steps to reproduce
  • Session ID if relevant
Where: Support email or appropriate feedback channel

I have a feature request

We want to hear it:
  • Email: support@igent.ai
  • Include use case and benefit
  • Explain why current features don’t solve it
Priorities driven by:
  • User demand
  • Strategic value
  • Technical feasibility
  • Resource availability

Is there a community?

Current channels: Check https://igent.ai/ for:
  • Community forums
  • Discord server
  • Office hours
  • User groups
Contribute:
  • Share workflows and patterns
  • Provide feedback
  • Request features
  • Help other users

Next Steps

Questions answered? Explore: