Design Retrieval architecture for a coding copilot for a large engineering org
Junior architecture interview question on Retrieval within RAG.
Read full explanationFrom prompt engineering to context engineering — budgets, retrieval, compression, and company-wide repository context.
The industry discussion has shifted from prompt engineering toward context engineering: selecting, structuring, and budgeting everything an agent sees each step — policy, AGENTS.md, retrieved code, tool results, and memory.
An important nuance from current research: concise, focused context (including AGENTS.md) helps, but overly long or overly prescriptive context files can increase inference cost and reduce task success. That makes 'best practices' content more valuable than generic tutorials — and it is exactly what interviews probe.
This guide defines context engineering, contrasts it with prompt engineering, and walks through repository context systems at company scale. Pair with the AGENTS.md guide for implementation detail.
Deep explanations with architecture diagrams for every question below.
Junior architecture interview question on Retrieval within RAG.
Read full explanationJunior trade-off interview question on Chain-of-Thought within Prompt Engineering.
Read full explanationJunior debugging interview question on Few-Shot within Prompt Engineering.
Read full explanationSenior debugging interview question on Jailbreaking within Prompt Engineering.
Read full explanationMid-Level debugging interview question on Prompt Templates within Prompt Engineering.
Read full explanationJunior debugging interview question on Structured Outputs within Prompt Engineering.
Read full explanationSenior debugging interview question on XML Prompting within Prompt Engineering.
Read full explanationJunior architecture interview question on Few-Shot within Prompt Engineering.
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