Free PDF · 12 pages · October 2026
AI Engineering Cheat Sheet
What our labs measured about tokens, prompting, RAG, evals, agents, serving, cost and fine-tuning, and the rule each result teaches.
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This sheet is the one-page summary. The full AI Engineering course teaches each idea step by step, with diagrams and code you run. It is one payment with lifetime access, and the first lessons are free.
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Each result comes from a lab in the AI Engineering course, with the model it ran on. Every lesson is linked, so you can read how it was measured.
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What is inside
- 01Tokens and embeddings, and prompting that holds up
- 02RAG: chunk size and overlap measured, embeddings, HNSW, hybrid search and reranking
- 03Evals: error analysis first, and the ways an LLM judge misleads you
- 04Agents in production, serving and inference, and where the cost goes
- 05Fine-tuning: when it pays, and why production breaks
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