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Designing what information goes into the context window and in what order.
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Based on SOC occupation classification
Proactively identifying failure modes, misuse, and unintended consequences.
Managing shared context, memory, and state across multiple agents.
Coordinating text, image, voice, and tool-use modalities in a single interaction.
Helping users form warranted trust in the AI — neither overtrust nor undertrust — through deliberate confidence and source signalling.
Reading user emotional state from text signals — caps, punctuation density, repetition, latency — and adapting before the user disengages.
Designing review workflows to surface and mitigate bias in AI outputs.
| name | context-engineering |
| description | Designing what information goes into the context window and in what order. |
The context window is finite. What goes into it — and in what order — determines the quality of every output. Context engineering is the practice of deliberately designing the information architecture of the context window.
Every context window has a token budget. Allocate it deliberately:
Order matters. The model pays different amounts of attention to different positions:
Not everything should go into the context. Design selection criteria:
How to tell if your context engineering is working:
