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mediumAI Engineering

What is context engineering and how does it differ from prompt engineering?

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01

Understand the problem

The discipline of deciding what the model sees: retrieval, memory, tools and budget allocation.

context-engineeringpromptingragmemory
02

Attempt it yourself

Sketch your approach before reading the solution — that's what interviews test.

Nudge consolestandby

Stuck? Beam a request up — the console returns a conceptual nudge that guides your logic without spoiling the implementation.

03

Study the solution

Prompt engineering crafts the instruction; context engineering designs everything the model sees at inference time — system rules, retrieved documents, conversation memory, tool results and few-shot examples — under a token budget. It treats the context window as a scarce resource: rank and admit only what raises answe

Solution ready — 2 min read

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04

Read the code

A context assembler with explicit budgets
function assembleContext(q: Query, budget: number) {
  const parts = [
    { text: SYSTEM_RULES,                     priority: 0 },   // stable prefix
    { text: relevantMemories(q, 3),           priority: 1 },
    { text: rerank(retrieve(q, 40)).slice(0, 6), priority: 2 },
    { text: summarizeOldTurns(q.history),     priority: 3 },
    { text: lastTurnsVerbatim(q.history, 4),  priority: 1 },
  ];
  return admitByPriorityUntil(parts, budget); // evict low-priority overflow
}
05

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