What is context engineering in AI?

It's building pipelines to feed models the right info—retrieval, chunking, injection—not just tweaking user prompts.

Why is prompt engineering outdated?

Prompts are <5% of input now; ignoring 95% context (files, docs, tools) wastes use in real apps like Cursor or Perplexity.

Yeah—think architecture over wording: RAG, vector DBs, pipelines. But tools like LangChain lower the bar.

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Prompts are <5% of input now; ignoring 95% context (files, docs, tools) wastes use in real apps like Cursor or Perplexity.

Yeah—think architecture over wording: RAG, vector DBs, pipelines. But tools like LangChain lower the bar.

Seven words into Cursor. Thousands of invisible tokens make the magic. Prompt engineering? That's yesterday's buzzword.

theAIcatchup Apr 10, 2026 4 min read

Prompt engineering misleads; context (95% of input) drives AI quality. 𝕏
Top products like Cursor and Perplexity win via context pipelines, not clever words. 𝕏
Shift to context engineering or stay behind—models are commodities. 𝕏

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#AI coding tools #AI development #RAG pipelines #context engineering #prompt engineering

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Originally reported by dev.to