Python · LangGraph · Agentic AI · Architecture
AI Agentic System
A seven-layer architectural blueprint for building reliable, observable, and scalable agentic AI systems in production.
A reference architecture and implementation blueprint for production agentic AI systems. Defines 7 architectural layers from task decomposition to evaluation with working code examples for each layer.
Problem
Teams building agentic AI systems from scratch repeatedly encounter the same failure modes: no observability, no error recovery, no evaluation. There was no opinionated reference architecture to build from.
Solution
A 7-layer framework covering: (1) Task decomposition, (2) Tool design, (3) Memory management, (4) Error recovery, (5) Observability, (6) Human-in-the-loop gates, and (7) Evaluation pipelines with a LangGraph implementation for each.
Key Features
- Complete working implementation of all 7 layers
- LangGraph-based orchestration with typed state schemas
- Three-tier memory: working, episodic, semantic
- Human-in-the-loop checkpoints at high-stakes nodes
- Golden dataset evaluation pipeline built in
- Starred by the community on GitHub