What is Cache-Augmented Generation (CAG) and why is it becoming essential in modern AI systems?
In this video, we break down:
What CAG is (in simple terms)
How CAG works step-by-step
CAG vs RAG comparison
Why CAG reduces AI inference cost
How semantic caching improves performance
Where CAG is used (AI copilots, enterprise bots, APIs, agents)
If you're building AI systems, working with LLMs, or designing agent architectures, understanding CAG can help you reduce latency, cut token costs, and scale smarter.
This is especially useful for:
AI Engineers
MLOps Engineers
Backend Developers
System Architects
Anyone building production LLM applications
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