Day 3 – The 5 Pillars of High-Quality RAG

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Continuing with the theory — it honestly feels like studying for a new degree.But understanding the fundamentals is essential to make better decisions later.

Today I found an excellent video, and the key lesson is this:

👉 The quality of any RAG system depends on 5 core factors.LLM

= the master chef. Retrieval

= the cook bringing the ingredients.If the ingredients are bad, the final dish will be bad, no matter how good the chef is.

Here are the 5 pillars, short and clear:

1️⃣ Chunk SizeChunks must be the right size — too big overloads context, too small loses meaning.

2️⃣ Query ConstructionBetter queries = better retrieval.Multi-Query RAG helps cover synonyms and variations.

3️⃣ Embedding ChoiceDense, sparse, or hybrid — your choice directly impacts search quality.

4️⃣ Retrieval QualityThe most critical point.If retrieval brings irrelevant content, the answer will be bad.Metadata & filters improve relevance dramatically.

5️⃣ Generation LayerGood prompting shapes tone, structure, and quality of the final output.

➡️ Master these 5 basics, and your RAG accuracy improves dramatically.

As always, you can find all materials in my notebook:👉 https://notebooklm.google.com/notebook/ea1c87b2-0eda-43f8-a389-ba1f57e758ce

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