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Phase 11 · Large Language Models

Topics

Context Window & Attention

Part of the AI Engineer Roadmap.

Summary

The maximum number of tokens an LLM can 'see' at once — a hard constraint on how much conversation history, document content, or retrieved context you can feed a model.

How to Learn This

  • 1Compare context window sizes across popular models (GPT, Claude, Gemini).
  • 2Learn why larger context windows cost more compute (attention scales quadratically with sequence length).
  • 3Understand strategies (summarization, retrieval) for working within a limited context window.

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Pretraining vs Fine-tuning

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Popular LLMs (GPT, Claude, Gemini, Llama)

More topics in Large Language Models

LLM Architecture OverviewTokenization (BPE, SentencePiece)Pretraining vs Fine-tuningPopular LLMs (GPT, Claude, Gemini, Llama)Open-Source vs Closed-Source ModelsModel Scaling Laws (Overview)Emergent Abilities (Overview)Multimodal Models (Overview)
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