promptdojo_promptdojo_promptdojo_promptdojo_promptdojo_promptdojo_promptdojo_promptdojo_promptdojo_promptdojo_promptdojo_
chapter 44

cnns, transformers, and useful llm internals

architecture literacy for builders: convolution, attention, tokens, decoding, kv cache, quantization, and what those choices do to cost and behavior.

5 live lessons · 35 live steps · 130 XP

cnns, transformers, and useful llm internals

Architecture literacy helps builders predict cost and behavior. This chapter keeps CNNs, token budgets, attention, decoding, KV cache, and quantization grounded in the tradeoffs a product builder actually reviews.

The exercises use small Python dictionaries and lists so every check can run in the browser. Real-world tools may be larger, but the review shape stays the same: input, decision, evidence, blocker, and next step.

By the end of the chapter, learners should be able to turn this topic into a concrete handoff instead of a vague model claim.

lessons in this chapter

  1. 01cnns and local patterns7 steps01cnns and local patterns7 steps01cnns and local patterns7 steps01cnns and local patterns7 steps01cnns and local patterns7 steps01cnns and local patterns7 steps01cnns and local patterns7 steps01cnns and local patterns7 steps01cnns and local patterns7 steps01cnns and local patterns7 steps01cnns and local patterns7 steps
  2. 02tokenizers and context budget7 steps02tokenizers and context budget7 steps02tokenizers and context budget7 steps02tokenizers and context budget7 steps02tokenizers and context budget7 steps02tokenizers and context budget7 steps02tokenizers and context budget7 steps02tokenizers and context budget7 steps02tokenizers and context budget7 steps02tokenizers and context budget7 steps02tokenizers and context budget7 steps
  3. 03attention and transformer blocks7 steps03attention and transformer blocks7 steps03attention and transformer blocks7 steps03attention and transformer blocks7 steps03attention and transformer blocks7 steps03attention and transformer blocks7 steps03attention and transformer blocks7 steps03attention and transformer blocks7 steps03attention and transformer blocks7 steps03attention and transformer blocks7 steps03attention and transformer blocks7 steps
  4. 04decoding, kv cache, and quantization7 steps04decoding, kv cache, and quantization7 steps04decoding, kv cache, and quantization7 steps04decoding, kv cache, and quantization7 steps04decoding, kv cache, and quantization7 steps04decoding, kv cache, and quantization7 steps04decoding, kv cache, and quantization7 steps04decoding, kv cache, and quantization7 steps04decoding, kv cache, and quantization7 steps04decoding, kv cache, and quantization7 steps04decoding, kv cache, and quantization7 steps
  5. 05mission: architecture tradeoff note7 steps05mission: architecture tradeoff note7 steps05mission: architecture tradeoff note7 steps05mission: architecture tradeoff note7 steps05mission: architecture tradeoff note7 steps05mission: architecture tradeoff note7 steps05mission: architecture tradeoff note7 steps05mission: architecture tradeoff note7 steps05mission: architecture tradeoff note7 steps05mission: architecture tradeoff note7 steps05mission: architecture tradeoff note7 steps