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# The AI Stack in 2026: 11 Layers Behind Production-Ready AI Systems

**[Medium](https://daily.dev/sources/medium_js)** · 10 min read · 1 upvotes · 0 comments

## Summary

Building production-ready AI applications requires far more than selecting a language model. A complete AI stack spans 11 layers: model providers, embeddings, vector databases, RAG pipelines, memory and state management, agent frameworks, managed agent platforms, MCP tool integrations, durable workflow execution, security and guardrails, and evaluation/observability. Each layer addresses a distinct concern — from semantic retrieval and multi-step agent reasoning to prompt injection defense and continuous quality measurement. Not every use case needs all 11 layers, but autonomous customer-facing agents typically require the full stack. Architecture should start from the business problem, not the tooling.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/devsecops-ai/the-ai-stack-in-2026-11-layers-behind-production-ready-ai-systems-a52409308ced>

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