Context Engineering Has Superseded Prompt Engineering

The field has reached consensus: if the model understands what you want but lacks information to do it well, that's a context problem, not a prompt problem. Context engineering is the discipline of designing systems that provide the right information, in the right format, at the right time — treating context as infrastructure with proper data curation, privacy controls, and logs. Stanford's "lost in the middle" research remains the key empirical grounding: models perform best when critical information appears at the very beginning or end of long contexts. Practical sweet spot for most tasks: 150–300 words of targeted context.

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Sources: Neo4j Blog · Firecrawl Blog · Substack guide