RAG vs CAG vs KAG: What I'd Choose for Production AI
RAG retrieves documents, CAG reuses cached context, and KAG follows connected facts. I compare their production trade-offs and the checks I'd run before choosing.
Tech blog · India
Deep dives into React.js, AI and ML integration, MERN stack patterns, and lessons from building production applications at scale in India — written by Deepak Kumar.
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Showing 3 articles tagged generative-ai. Clear filter
Artificial general intelligence remains hypothetical; I explain what separates it from today's AI and how I'd evaluate capabilities before expanding autonomy.
Read the articleRAG retrieves documents, CAG reuses cached context, and KAG follows connected facts. I compare their production trade-offs and the checks I'd run before choosing.
Gemini 4 Carbon targets vulnerability discovery and patching; I'd evaluate its evidence, permissions and total review cost before trusting it with production code.
About the author
Deepak Kumar
Sr Software Engineer at India Today Group | Aaj Tak
Building scalable web applications and Generative AI systems. Writing about React, Node.js, AI and the engineering lessons from 9+ years of production work.
More about meOpen to senior full-stack and AI engineering roles, and to focused contract work. Delhi NCR or fully remote. I reply within 24 hours.
What I take on
Full-stack product build
React, Next.js, Node, NestJS, MongoDB and MySQL — from idea to production.
AI features that ship
OpenAI and LangChain, RAG, semantic search, content and voice automation.
Architecture and scale
Microservices, real-time pipelines and caching — proven at national news scale.
Founding engineer work
Idea to MVP to scale, with SEO and analytics built in from the start.