DictionaryContext Engineering

Context Engineering

Dictionary
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What is Context Engineering?

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Context engineering is the discipline of shaping everything that surrounds the model call: system prompts, retrieval, tool schemas, and guardrails. It’s how you turn LLMs into dependable business systems.

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How does Context Engineering work?

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Select the right context sources (RAG), design chunking and metadata, craft prompts and schemas, and evaluate outputs for faithfulness. Add tools and rules so the model can act safely.

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When should you use it? (Typical use cases)

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  • RAG assistants with high factual accuracy.
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  • Agents that make safe, auditable changes in systems.
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  • Analytics narratives grounded in governed datasets.
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  • Multilingual support based on curated knowledge.
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Benefits and risks

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Benefits

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  • Higher answer quality.
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  • Lower hallucination risk.
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  • Repeatable behavior across tasks.
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Common pitfalls/risks

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  • Overly complex pipelines.
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  • Context bloat inflating costs.
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Antire and Context Engineering

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Antire delivers context-first designs: retrieval quality, prompt patterns, tool governance, and evaluation, so AI apps are useful, safe, and economical.

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Services

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  • Data platforms and applied AI
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  • Tailored AI & ML
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  • Cloud-native business applications
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  • Fast Track AI Value Sprint
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