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Cheatsheet AI
The RAG Developer's Stack 2026
From LLMs to vector DBs to evals the complete ecosystem map for building production retrieval-augmented generation systems.
Layer 2
Frameworks
Orchestration libraries that wire LLMs, retrieval, and tools together.
Library
Layer 4
Data Extraction
Parse PDFs, scrape sites, and extract structured data from messy sources.
Web
Documents
Layer 5
Open LLM Access
Hosted gateways to open-weight models often cheaper and faster than self-hosting.
Hosting
Layer 6
Embeddings
Models that turn text (and images) into vectors. Quality here caps RAG quality.
Open
Closed
Layer 7
Evaluation
How you measure if your RAG actually answers correctly.
Eval & Tracing
RAG isn’t a technique anymore it’s an ecosystem. Most production stacks pull from at least 5 of the layers above. Read more in our RAG glossary entry or browse the full AI tools directory.
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