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Representation Design for LLM Systems

7 chapters · 33 lessons

1. 1. How LLMs Process Information

   4 lessons

   Understand tokenization, embeddings, and attention mechanisms to predict how representation choices affect model behavior.

2. 2. Structured vs Unstructured Representations

   5 lessons

   Compare representation formats and learn when to use lists, tables, JSON, typed blocks, and narrative text.

3. 3. Context Selection and Retrieval Design

   5 lessons

   Build systems that identify and surface relevant information from large document collections and databases.

4. 4. Transforming Domain Data for LLM Input

   4 lessons

   Convert databases, APIs, logs, and structured sources into formats that preserve signal and reduce noise.

5. 5. Prompt Patterns for Common Tasks

   5 lessons

   Apply proven representation strategies for classification, extraction, summarization, and reasoning workflows.

6. 6. Evaluation and Iteration

   5 lessons

   Build test suites and metrics to measure representation quality and identify systematic failures.

7. 7. Production System Design

   5 lessons

   Architect scalable pipelines that combine retrieval, transformation, generation, and monitoring.