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agent academy labs

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Multi-Agent Platforms & Frameworks
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Basic Information

Agent Academy Labs is a learning and research repository focused on agent-based software architectures, ranging from reactive agents to advanced AI-driven multi-agent systems. It is presented as a ByteStack Labs learning space that organizes progressive content into Beginner, Intermediate and Advanced tracks covering reactive patterns, BDI architecture, SPADE framework, coordination protocols and LLM-driven agents. The project aims to make multi-agent systems accessible through runnable, well-documented examples and production-minded patterns. The README states the work is under active development with an expected launch in Q4 2025 and encourages users to star the repo for updates. The repository is positioned for developers and researchers who want hands-on exposure to modern multi-agent design, implementation details and demonstrations of distributed systems with practical use cases.

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App URL
https://github.com/Cre4T3Tiv3/agent-academy-labs
Github Repository
https://github.com/Cre4T3Tiv3/agent-academy-labs/blob/main/README.md

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App Details

Features
The project emphasizes progressive complexity with structured learning tracks that start with reactive agents and advance to BDI and LLM agents. It lists SPADE and Mesa as primary frameworks alongside ByteStack Labs custom architectures. Examples are described as runnable, well-documented and production-ready, including testing and monitoring. Modern tooling is highlighted, such as the UV package manager, FastAPI and async/await patterns. The repo also promises interactive visualizations and web interfaces for exploration and demonstration. Real-world application examples mentioned include IoT systems, trading bots and distributed coordination. The documentation claims research-backed content and professional-grade code quality produced by ByteStack Labs. The README notes active development and invites users to follow progress.
Use Cases
The repository helps developers and researchers learn multi-agent system concepts through hands-on, runnable examples and escalating complexity across learning tracks. It provides concrete architecture patterns and framework guidance for SPADE and Mesa, plus custom ByteStack Labs designs that illustrate coordination protocols and BDI-style reasoning. Practical examples such as IoT integration, trading bots and distributed coordination demonstrate real-world application and help bridge theory to implementation. Modern tooling recommendations, production-ready examples with testing and monitoring and interactive visualizations facilitate experimentation, debugging and teaching. The materials are pitched to make multi-agent systems accessible worldwide and to support both education and research workflows while the project matures under active development.

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