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mediumAI Engineering

How do you manage conversations that outgrow the context window?

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01

Understand the problem

Sliding windows, summarization, and externalized memory for long-running chats and agents.

memorysummarizationcontext-windowchat
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

Common strategies: keep a sliding window of recent turns; compress older turns into a running summary that is prepended; extract durable facts into an external store (profile/memory) and retrieve them when relevant; and for agents, checkpoint task state so work can resume in a fresh context. The trade-off is fidelity v

Solution ready — 2 min read

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04

Read the code

Summary + pins + recent turns
async function prepareHistory(turns: Turn[], pins: string[]) {
  const recent = turns.slice(-8);
  const evicted = turns.slice(0, -8);
  const summary = evicted.length
    ? await summarize(prevSummary, evicted)     // incremental, ~300 tokens
    : null;
  return [
    summary && { role: "user", content: "[Conversation so far]\n" + summary },
    pins.length && { role: "user", content: "[Pinned facts]\n- " + pins.join("\n- ") },
    ...recent,
  ].filter(Boolean);
}
05

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