Context Engineering in Practice: Building Accurate and Scalable AI Agents

Enterprises deploying AI agents are increasingly focusing on context engineering to ensure consistent and reliable outputs. This article explores how context differs from prompts, how it is managed across workflows, and how organizations use it to reduce hallucinations and improve system accuracy. It also highlights practical use cases and implementation considerations for enterprise environments.

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