# Context Engineering

> Context engineering is the practice of curating the full set of tokens a model sees at each step, including instructions, tools, retrieved data, memory, and conversation history, to maximize the chance of the desired behavior within a limited attention budget.

- Identifier: PTL-0072
- Category: Agents & Orchestration
- Canonical URL: https://protologue.com/t/context-engineering/
- Also known as: context management
- Introduced: 2025

## Description

The term gained currency in 2025 as agents ran for many steps and the main challenge shifted from wording a single prompt to deciding what information enters and leaves the context window over time, through techniques such as compaction, structured note-taking, and subagents.

## Broader terms

- [Prompt Engineering](https://protologue.com/t/prompt-engineering/)

## Related terms

- [Context Window](https://protologue.com/t/context-window/)
- [Agent Memory](https://protologue.com/t/agent-memory/)
- [Retrieval-Augmented Generation](https://protologue.com/t/retrieval-augmented-generation/)
- [AI Agent](https://protologue.com/t/ai-agent/)
- [Lost in the Middle](https://protologue.com/t/lost-in-the-middle/)

## Sources

- Anthropic (2025). Effective context engineering for AI agents. https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents

## Cite this entry

Protologue. (2026). Context Engineering. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0072). https://protologue.com/t/context-engineering/

License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)