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Claude Architect · 강의

오래된 컨텍스트와 새로 시작하기

재개한 도구 결과가 오래되었다면 새로 요약합니다

오래된 컨텍스트와 새로 시작하기은(는) CoddyKit의 무료 Claude Architect 강의입니다. 이것은 4개 중 4번째 강의입니다. 아래에서 전체 강의를 무료로 읽을 수 있으며, 내장 코드 에디터와 24/7 AI 튜터와 함께 브라우저에서 직접 실습할 수 있습니다. 이 강의는 Claude Architect 학습 경로의 일부이며, 진행 상황이 웹과 CoddyKit 앱에 동기화됩니다. Claude Architect 강의에는 총 4개의 강의가 포함되어 있습니다.

이 강의의 일부는 아직 번역되지 않았으며 영어로 표시됩니다.

Resuming a Session

Claude Code lets you continue work across days. --resume <name> reopens a named session with its full message history intact: the prompts, the model's reasoning, and crucially the tool results that were captured the first time.

That replay is powerful. But it hides a sharp edge: those tool results are a snapshot of the past, not a live view of your system. This lesson is about recognizing when that snapshot has gone stale and what to do instead.

claude --resume refactor-auth

Why the History Is Frozen

Remember how the API works: the model keeps no state of its own. Every turn you send the full messages history — including prior tool_result blocks. The model reasons over whatever those blocks say.

A resumed session simply reloads that saved history. If a Read captured a file's contents last Tuesday, the model still believes Tuesday's version today — even if the file changed ten times since.

messages = [
    {"role": "user", "content": "Refactor the auth module"},
    {"role": "assistant", "content": [tool_use_read_authpy]},
    # tool_result below is a FROZEN snapshot from the prior session
    {"role": "user", "content": [tool_result_authpy_old]},
]
client.messages.create(model="claude-opus-4-1", max_tokens=2048, messages=messages, tools=tools)

What 'Stale Context' Looks Like

Stale context is when the resumed tool results no longer match reality. Common triggers:

  • A teammate edited the same files between sessions.
  • A migration changed the database schema the model had cached.
  • A dependency bump altered an API the model read earlier.
  • A build artifact or test output captured earlier is now obsolete.

The danger: the model proceeds confidently on outdated facts, producing edits that conflict with the current codebase.

Resume vs. Fresh Session

You have two recovery levers when a session ages:

  • --resume <name> continues the named session, replaying its full saved history.
  • fork_session branches from a shared point — useful for exploring an alternative without disturbing the original.

Both inherit the old tool results. When the codebase has drifted substantially, neither is ideal. Sometimes a fresh session seeded with a structured summary beats resuming, because it forces every fact to be re-fetched against current reality.

claude --resume refactor-auth     # replays old tool results
claude                            # fresh session, no stale snapshots

The Core Decision

Ask one question: has the ground truth changed since the session was captured?

  • Little or no drift (you paused for an hour, no one else touched the repo) → --resume is fine and cheap.
  • Significant drift (days passed, merges landed, schema migrated) → start fresh and re-summarize the goal, then let the model re-fetch live tool results.

This is a context-management reliability call — domain D5 on the exam.

Summarize Anew, Don't Replay

"Summarize anew" means: carry forward the intent and decisions, but drop the frozen tool outputs so they get re-acquired. You write a compact, structured summary of where the task stands, then open a clean session with that summary as the opening prompt.

The model then runs Read, Grep, and Bash against the current codebase — no stale snapshot to mislead it.

summary = """
GOAL: Finish refactoring auth to use the new TokenService.
DONE: Extracted TokenService; updated login() and logout().
TODO: Migrate refresh() and the 3 middleware call sites.
NOTE: schema migrated since last session — re-read current files before editing.
"""
messages = [{"role": "user", "content": summary + "\nRe-read the current files, then continue."}]

Keep Hard Facts Verbatim

Progressive summarization is lossy: it makes numbers, percentages, and dates vague. When your summary must preserve exact values — a version pin, a row count, a deadline, an order ID — don't fold them into prose.

Pull them into a separate "case facts" block kept verbatim, outside the narrative summary. The summary can compress the story; the facts block stays exact.

case_facts = {
    "target_version": "TokenService 2.4.0",
    "affected_call_sites": 3,
    "migration_applied": "2026-06-09",
}
prompt = SUMMARY_PROSE + "\n\nCASE FACTS (verbatim, do not paraphrase):\n" + str(case_facts)

Re-Fetch Before You Edit

In a fresh session the discipline is simple: investigate before mutating. Use the incremental pattern — Grep entry points, Read the files, Grep usages, Read consumers — so every edit is grounded in current contents.

This is also why Edit uses a unique-match contract: if the file drifted and your expected text no longer matches uniquely, the edit fails loudly rather than corrupting the file. Re-Read and retry.

# Fresh-session re-grounding before any change
# 1) Grep for the symbol
# 2) Read the current file
# 3) Edit with a unique match (fails loudly if the file drifted)

Don't Confuse This with /compact

/compact compresses the current conversation to free context space. It is useful, but it carries the same lossiness risk: numbers and dates can become vague. It does not solve staleness — the compacted facts are still from the original captures.

Starting fresh is different: you discard the old tool results entirely and re-derive them live. Use /compact for a long but still-accurate session; start fresh when the underlying system has moved on.

Subagents Never Inherit History

This staleness lesson rhymes with multi-agent design. Subagents do not inherit the coordinator's conversation history — all context must be passed explicitly in each subagent prompt.

The same hygiene helps you: when you hand a fresh session (or a subagent) a structured summary plus a verbatim facts block, you are doing deliberately what resume does accidentally — except you control exactly which facts survive and you force live re-fetching of the rest.

# Coordinator passes explicit, current context to each subagent
subagent_prompt = (
    "You are refactoring auth. Context summary:\n" + summary +
    "\nCASE FACTS:\n" + str(case_facts) +
    "\nRe-read the current files yourself; do not assume prior state."
)

A Practical Checklist

Before resuming a stale session, run this gate:

  • Drift? Did the repo/schema/deps change since capture? If yes → lean fresh.
  • Summarize goal, decisions made, and remaining TODOs.
  • Preserve exact numbers/dates/IDs in a verbatim facts block.
  • Re-fetch live: Grep → Read before any Edit.
  • Verify against current state, not the remembered one.

Cheap to resume when nothing moved; cheap insurance to start fresh when it did.

Quick Check

Test your judgment on the resume-vs-fresh decision.

Recap

Key takeaways:

  • Resumed sessions replay frozen tool results because the model holds no state and reasons over the full saved history.
  • When the system has drifted (merges, migrations, dependency bumps), those results are stale and can drive confident-but-wrong edits.
  • When drift is significant, start fresh and summarize anew rather than --resume or fork_session, which both inherit the old snapshots.
  • Keep exact numbers, dates, and IDs in a verbatim case-facts block; summarization makes those vague.
  • Re-fetch live (Grep → Read) before any Edit; /compact saves space but does not cure staleness.

자주 묻는 질문

“오래된 컨텍스트와 새로 시작하기” 강의는 무료인가요?

네 — “오래된 컨텍스트와 새로 시작하기” 전체 내용을 이 웹사이트에서 무료로 읽을 수 있습니다. 인터랙티브하게 실습하려면(내장 코드 에디터와 24/7 AI 튜터), CoddyKit PRO로 업그레이드하면 Claude Architect 강의 전체를 잠금 해제할 수 있습니다. Claude Architect 강의에는 총 4개의 강의가 포함되어 있습니다.

“오래된 컨텍스트와 새로 시작하기”에서 뭘 배우나요?

재개한 도구 결과가 오래되었다면 새로 요약합니다 브라우저에서 직접 실행하는 실습 코드로 Claude Architect을(를) 배우며, 24/7 AI 튜터가 강의를 진행하면서 질문에 답변해줍니다.

Claude Architect을(를) 시작하는 데 경험이 필요한가요?

사전 경험은 필요하지 않습니다. CoddyKit의 Claude Architect은(는) 초급자부터 고급 학습자까지를 위해 구성되어 있으므로, 여기서 시작하거나 처음부터 시작할 수 있으며 자신의 속도대로 진행할 수 있습니다. 이것은 4개 중 4번째 강의입니다.

“오래된 컨텍스트와 새로 시작하기” 강의는 얼마나 걸리나요?

대부분의 CoddyKit 강의는 약 5~10분이 소요됩니다. 각 강의는 간결하고 인터랙티브하여 꾸준한 진행이 가능하며, 웹과 앱에서 중단한 부분부터 바로 시작할 수 있습니다.

이 Claude Architect 강의에서 코드를 작성하고 실행할 수 있나요?

네. 모든 Claude Architect 강의에는 내장 코드 에디터가 포함되어 있으므로, 브라우저에서 바로 실제 코드를 작성하고 실행한 후 즉시 AI 피드백을 받을 수 있습니다 — 로컬 설정이 필요 없습니다.

이 강의의 모든 강의

  1. 고정 파이프라인과 적응형 분해
  2. 다중 패스 분해
  3. 세션 관리
  4. 오래된 컨텍스트와 새로 시작하기
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