Saurabh’s Original Framework
Practical AI Stack
A real-world architecture view of how useful AI systems are built.
Developed by Saurabh Jaiswal as part of the AI for Real Work methodology, this framework explains the practical architecture layers behind useful, reliable, and maintainable AI systems.
Core idea
Real-world AI is not only a model. Useful AI systems combine models, data, tools, memory, orchestration, validation, monitoring, and human oversight.
The 5 layers
Layer 1
Model
The LLM or AI model that powers reasoning, generation, or classification.
Layer 2
Data
The documents, databases, APIs, and knowledge sources the system depends on.
Layer 3
Tools
The functions, services, automations, and external systems AI can use.
Layer 4
Orchestration
The workflow layer that coordinates models, memory, tools, and actions.
Layer 5
Oversight
The validation, monitoring, governance, and human review layer.
Why it matters
Many AI demos look impressive but fail in production because they ignore orchestration, validation, monitoring, permissions, and operational design.
Real-world use
Use this to design enterprise copilots, AI agents, RAG systems, automation platforms, internal assistants, and AI-native workflows.
Final takeaway
The model is only one layer. The system around the model creates real-world value.