This repository is currently in development. The multi-agent systems framework and educational content are being built from the ground up with a focus on production-grade architecture and enterprise reliability.
Watch this space, we're building something different for the agent development community.
Most "AI agent" implementations are shallow wrappers around LLM APIs. This project will provide production-ready architecture with async/await patterns, comprehensive monitoring, and enterprise-grade reliability.
| Component | Description | Status |
|---|---|---|
| BaseAgent | Enterprise-grade agent with async perception-action cycle | In Development |
| ReactiveAgent | Priority-based behavior rules with statistics tracking | In Development |
| Environment | Scalable state management and agent registration | In Development |
| Examples | Production-ready demonstrations (Smart Devices, etc.) | In Development |
| Documentation | Comprehensive guides and API documentation | In Development |
| Aspect | Tutorial Code | Agent Academy Framework (Planned) |
|---|---|---|
| Architecture | Single function calls | Full perception-action cycle |
| Concurrency | Basic threading | Async/await throughout |
| Error Handling | Try/catch | Timeout handling, retry logic |
| Monitoring | Print statements | Performance metrics, observability |
| Production Ready | No | Enterprise-grade |
- BaseAgent Architecture: Async perception-action cycle with timeout handling
- ReactiveAgent Implementation: Behavior rules with priority system
- Environment System: State management and agent registration
- Performance Monitoring: Built-in metrics and observability
- Type Safety: Complete type hints for enterprise development
- Smart Device(s) Demo: Working example with behavior rules
- Multi-Agent Scenarios: Agent coordination and communication
- Performance Benchmarks: Load testing and optimization
- Test Suite: Comprehensive coverage and validation
- Documentation: API docs and usage guides
- Distributed Communication: SPADE framework integration
- Modern Protocols: Support for cutting-edge agent communication
- Enterprise Deployment: Production deployment patterns
- Monitoring & Observability: Advanced performance tracking
- Async/Await Architecture: Full concurrency support for scalable deployment
- Performance Monitoring: Built-in metrics collection and analysis
- Error Recovery: Timeout handling, retry logic, graceful degradation
- Type Safety: Complete type hints for enterprise development
- Observability: Structured logging with performance tracking
The framework will support modern Python development practices:
# Planned installation process
curl -LsSf https://astral.sh/uv/install.sh | sh
git clone https://github.com/Cre4T3Tiv3/agent-academy-labs
cd agent-academy-labs
uv sync --all-extras- Hand-crafted agent architectures with proper lifecycle management
- Enterprise-grade async patterns for scalable deployment
- Comprehensive monitoring with performance tracking
- Type-safe implementations for maintainable code
- No shallow LLM wrappers or prompt chains
- No demo-level code that breaks in production
- No framework dependencies that hide architectural complexity
- No magic that obscures how agents actually work
- Technical rigor: Every component designed for production use
- Performance focus: Benchmarked and optimized for real workloads
- Educational value: Code that teaches proper agent architecture
- Community driven: Open source with comprehensive documentation
This project is in active development. We welcome:
- Architecture discussions in GitHub Discussions
- Feature requests through GitHub Issues
- Code contributions following our development guidelines (coming soon)
- Testing and feedback as components become available
- Star this repository to follow development progress
- Watch releases for major milestones
- Join discussions for architecture and design conversations
- Follow ByteStack Labs for broader updates
Agent Academy Labs will be licensed under the Apache 2.0 License.
@software{agent_academy_labs,
author = Jesse Moses (@Cre4T3Tiv3),
title = {Agent Academy Labs: Production-Grade Multi-Agent Systems Framework},
url = {https://github.com/Cre4T3Tiv3/agent-academy-labs},
version = {0.1.0},
year = {2025},
organization = {ByteStack Labs}
}Agent Academy Labs is being built by Jesse Moses (@Cre4T3Tiv3) at ByteStack Labs.
- AI Engineer with 10+ Years Experience
- MS AI/ML and MS CS (in progress)
- Multi-Agent Systems Engineer and Researcher
- Project Discussions: GitHub Discussions
- Professional Consulting: ByteStack Labs
- Development Updates: Follow this repository
Question for the Developer Community: What if agent frameworks started with production-grade architecture instead of tutorial-level wrappers?
Building the future of agent systems at ByteStack Labs
Production-grade architecture for developers who need real solutions