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<div class="eyebrow">PLS production artifact · codex-session-stability · 2026-05-24</div> |
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<h1>Codex Worker 自修復採用作戰台</h1> |
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<p>把「worker 穩定與自修復」從上層要求，升級成一線 worker 可自下而上回報、修復、驗收與累積學習記憶的 production loop。</p> |
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</header> |
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<main class="wrap"> |
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<section class="grid"> |
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<div class="panel span-12"><div class="kpis"> |
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<div class="kpi"><strong>2</strong><span>最新共同訊號都指向生產關係調整</span></div> |
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<div class="kpi"><strong>3</strong><span>關聯專案需合併成 reliability/adoption lane</span></div> |
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<div class="kpi"><strong>D7</strong><span>完成 worker 回報與自修復 acceptance</span></div> |
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<div class="kpi"><strong>D30</strong><span>進 PLS ops console 與 worker learning memory</span></div> |
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</div></div> |
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<div class="panel span-8"> |
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<h2>自修復 Adoption Gates</h2> |
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<table> |
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<thead><tr><th>Gate</th><th>Trigger</th><th>Worker Action</th><th>Human Policy</th><th>Pass Evidence</th></tr></thead> |
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<tbody> |
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<tr><td><span class="status red">stuck_claim</span></td><td>claim 無 job 或 context fetch failed</td><td>重試一次、touch、記錄 blocker phase</td><td>不得硬 complete</td><td>progress / verification 記錄 command output</td></tr> |
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<tr><td><span class="status amber">repair_suggested</span></td><td>同類錯誤重複 2 次</td><td>產生 backlog/capability repair proposal</td><td>Louis 或 PLS owner 決定是否納入 worker policy</td><td>decision-record 有採納/不採納欄</td></tr> |
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<tr><td><span class="status blue">artifact_guard</span></td><td>complete 前</td><td>驗證 primary URL HTTP 200、upload-files 成功</td><td>無可開啟主成果不得完成</td><td>curl/gh/upload-files output</td></tr> |
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<tr><td><span class="status green">worker_learning</span></td><td>每次修復後</td><td>更新 learning_memory 與 next_round_priority</td><td>一線 worker 可回報 policy friction</td><td>D7 產出 3 筆採用/阻塞訊號</td></tr> |
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</tbody> |
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</table> |
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<h2>LINE Ask</h2> |
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<div class="script">這輪 Codex worker 穩定性不是只補 watchdog，而是把一線 worker 的自修復回報納入作業。 |
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請確認三件事： |
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1. context/complete fetch failed 時，是否允許 worker 自動 touch + retry 一次？ |
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2. 同類錯誤連續 2 次時，是否要自動產 repair proposal？ |
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3. 哪些 self-heal 動作需要 Louis/PLS owner 批准？ |
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未回覆前，worker 只做 diagnosis / retry once / proposal，不做 release/reclaim。</div> |
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</div> |
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<div class="panel span-12"> |
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<h2>D1 / D7 / D14 / D30</h2> |
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<div class="timeline"> |
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<div class="stage"><h3>D1 · Console + Policy</h3><ul><li>發布自修復採用作戰台。</li><li>定義 retry once、artifact guard、repair proposal policy。</li><li>上傳 production pack。</li></ul></div> |
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<div class="stage"><h3>D7 · Worker Adoption</h3><ul><li>收 3 筆一線 worker friction/repair 訊號。</li><li>驗證 stuck_claim 與 artifact_guard。</li><li>輸出 first reliability scorecard。</li></ul></div> |
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<div class="stage"><h3>D14 · Workflow App</h3><ul><li>接 PLS job/lease/progress/artifact tables。</li><li>自動產 repair proposal。</li><li>建立 policy approval matrix。</li></ul></div> |
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<div class="stage"><h3>D30 · Operating Model</h3><ul><li>worker self-repair 進 PLS ops console。</li><li>每週 review learning memory。</li><li>用 adoption evidence 改 worker prompts/tools。</li></ul></div> |
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</div> |
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</div> |
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<div class="panel span-12"> |
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<h2>Purpose-to-Purpose E2E</h2> |
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<div class="flow"> |
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<div class="step"><b>原始目的</b><span class="small">Codex Session / worker 要穩定推進專案與強化 huber 分身。</span></div> |
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<div class="step"><b>主成果</b><span class="small">自修復 adoption console、資料模型、acceptance tests、policy LINE ask。</span></div> |
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<div class="step"><b>人採用</b><span class="small">PLS owner 決定 self-heal policy；worker 回報 friction。</span></div> |
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<div class="step"><b>系統改善</b><span class="small">fetch failed、schema error、artifact missing 變成可驗收事件。</span></div> |
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<div class="step"><b>價值路徑</b><span class="small">降低人工盯盤、減少錯誤完成、讓 AI 推進產能累積成制度。</span></div> |
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</div> |
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</div> |
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<div class="panel span-6"> |
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<h2>市場成熟做法</h2> |
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<p>Google SRE monitoring 強調用 actionable symptom 管理 production reliability；McKinsey gen AI transformation 則指出價值來自 operating model、workflow redesign、talent/adoption reinforcement。這輪把兩者合併：不只監控 worker，也讓一線 worker 能提出修復訊號，形成生產關係調整。</p> |
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<ul> |
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<li>https://sre.google/resources/book-update/monitoring-distributed-systems/</li> |
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<li>https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/gen-ais-next-inflection-point-from-employee-experimentation-to-organizational-transformation</li> |
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</ul> |
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<div class="panel span-6"> |
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<h2>Data / API / Permission</h2> |
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<div class="code">tables: |
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worker_repair_events |
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worker_policy_decisions |
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artifact_gate_checks |
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learning_memory_updates |
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apis: |
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POST /worker-repair-events |
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POST /artifact-gate-checks |
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PATCH /worker-policy/:id |
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roles: |
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worker: diagnose/propose |
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PLS owner: approve policy |
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Louis: approve risky self-heal</div> |
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</div> |
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<div class="panel span-4"> |
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<h2>Production Acceptance</h2> |
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<p><b>Owner:</b> PLS platform / Louis。</p> |
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<p><b>Due:</b> D7 worker adoption proof。</p> |
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<p><b>Pass:</b> 3 筆 repair/friction event、1 次 artifact guard pass、1 份 policy decision。</p> |
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</div> |
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<div class="panel span-4"> |
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<h2>Solution Selection</h2> |
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<p>選 `watchdog + governance + project`：比單純 watchdog 更能回應本輪「生產關係調整」訊號；不直接 full agent，因 self-heal 權限仍需政策批准。</p> |
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</div> |
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<div class="panel span-4"> |
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<h2>Next Upgrade</h2> |
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<p>D7 後把真實 worker repair events 接到 PLS ops console，D14 建 policy approval matrix，D30 用 learning memory 自動改善 worker prompt/tooling。</p> |
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