07 - Managing LLM Context: Memory Allocation and Optimization

Complete guide to Managing LLM Context: Memory Allocation and Optimization: architecture, practical implementation and best practices for developers and technical teams.

What you'll learn

• Always count tokens before sending with tiktoken or equivalent
• Structure context to mitigate "Lost in the Middle": critical info at start and end
• Use semantic compression instead of brute truncation
• ConversationSummaryBufferMemory is the best choice for long conversations
• Monitor cost-per-query in production and set alerts

This article is part of the AI Engineering series on federicocalo.dev.

Read the full article

The complete article (15 min read) with code examples, diagrams, and practical exercises is available here:

➡️ 07 - Managing LLM Context: Memory Allocation and Optimization

https://federicocalo.dev/en/blog/managing-llm-context-memory-allocation-optimization

By Federico Calò — Software Developer & Technical Writer