---
Title: "What Is Context Engineering in AI?"
Url: "https://computer.io/glossary/context-engineering"
Topic: "Agentic AI"
Description: "Context engineering is designing what an AI model sees, including instructions, data, memory and tools, so it performs reliably. Context vs prompt engineering."
---

# What is context engineering?

Context engineering is the practice of designing and managing everything an AI model sees when it works, including instructions, retrieved documents, conversation history, memory, tool definitions and user permissions, so it has the right information to perform a task reliably.

## Context engineering vs prompt engineering

|  | Prompt engineering | Context engineering |
| --- | --- | --- |
| Focus | Wording of instructions | All information given to the model |
| Scope | Single prompt | Whole system |
| Includes | Instructions, examples | Retrieval, memory, tools, state |

## Techniques

Retrieve only relevant data, summarize long histories, structure tool outputs, and filter by permissions.

## Why it matters for agents

Agents fail more often from missing or noisy context than from model limits.

## FAQ

### Who coined context engineering?

The term spread widely in 2025 among AI practitioners.

### Is prompt engineering dead?

No, it's one part of context engineering.

### How does a knowledge graph help context engineering?

It supplies connected, relevant facts instead of loose text.

## Related terms

- [Prompt engineering](https://computer.io/glossary/prompt-engineering)
- [Context window](https://computer.io/glossary/context-window)

## How Computer helps

- [How computer works](https://computer.io/how-computer-works)

## Further reading

- [Knowledge graph missing layer ai agents](https://devrev.ai/blog/knowledge-graph-missing-layer-ai-agents)