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<title>Operating Console 反 Tokenmaxxing 指標治理台</title> |
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<span class="pill info">PLS production delivery pack</span><span class="pill ok">Solution: governance / eval / dashboard</span> |
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<h1>Operating Console 反 Tokenmaxxing 指標治理台</h1> |
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<p class="sub">把「反 Tokenmaxxing」從文件章節升級成可驗收的指標治理系統：明確禁止 Token 消耗數量、工具啟動次數、AI 使用人數排行等誘發灌水的活動指標，改用任務完成率、實際節省時間、客戶滿意度、產出品質評分與反作弊稽核。</p> |
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<div class="card"><div class="metric bad">3</div><div class="label">禁止指標：Token、啟動次數、使用排行</div></div> |
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<div class="card"><div class="metric ok">4</div><div class="label">替代指標：完成率、節省時間、CSAT、品質</div></div> |
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<div class="card"><div class="metric">D7</div><div class="label">完成第一版 metric registry 與 gate</div></div> |
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<div class="card"><div class="metric">D30</div><div class="label">接進 Operating Console 考核治理</div></div> |
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<h2>本輪問題</h2> |
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<p>Operating Console 若用 Token 消耗、工具啟動次數、AI 使用人數排行當成績效，會把人推向「看起來很 AI」而不是「真的完成任務」。這是典型 Goodhart's law：一旦指標成為目標，它就會失去衡量價值。</p> |
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<span class="pill">Owner: Operating Console owner</span><span class="pill">Due: D7 metric registry</span><span class="pill">Acceptance: bad metrics blocked</span> |
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<h2>解法選型</h2> |
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<p><strong>governance / eval / dashboard</strong>。這不是單篇規格補充，而是考核制度風險。需要 metric registry、禁止清單、替代指標、review workflow、稽核和例外批准。</p> |
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<h2>D1 / D7 / D14 / D30 路徑</h2> |
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<div class="card day"><h3>D1</h3><p>建立禁止指標與替代指標 registry，定義每個指標的 owner、公式、資料源、反作弊檢查。</p></div> |
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<div class="card day"><h3>D7</h3><p>在 Operating Console 指標設定加入 governance gate，bad metric 不得上線，例外需 decision record。</p></div> |
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<div class="card day"><h3>D14</h3><p>接 3 個實際 AI 工作流，用 outcome metrics 驗證儀表板是否能反映真價值。</p></div> |
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<div class="card day"><h3>D30</h3><p>形成 AI performance governance：指標、品質、客戶滿意、節省時間、稽核異常同表決策。</p></div> |
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<h2>Purpose-to-Purpose E2E</h2> |
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<div class="step"><strong>原始目的</strong>Operating Console 要衡量 AI 對業務的真實價值。</div> |
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<div class="step"><strong>風險</strong>Tokenmaxxing 把人推向增加消耗與表演式使用。</div> |
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<div class="step"><strong>治理</strong>metric registry 阻擋壞指標，替代成 outcome/quality/time/customer metrics。</div> |
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<div class="step"><strong>採用</strong>主管用可驗證結果考核；員工專注完成任務與提升品質。</div> |
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<div class="step"><strong>結果</strong>降低浪費、提升任務完成率、改善客戶滿意、避免制度誘發錯誤行為。</div> |
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<h2>Metric Registry Gate</h2> |
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<table> |
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<thead><tr><th>Metric</th><th>Status</th><th>Reason / Replacement</th></tr></thead> |
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<tbody> |
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<tr><td>Token consumed</td><td class="badcell">Blocked</td><td>誘發灌水與低效率；替代為 task completed per verified outcome。</td></tr> |
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<tr><td>Tool launches</td><td class="badcell">Blocked</td><td>啟動不等於採用；替代為 workflow completion rate。</td></tr> |
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<tr><td>AI usage leaderboard</td><td class="badcell">Blocked</td><td>誘發排名焦慮和表演；替代為 team outcome score。</td></tr> |
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<tr><td>Task completion rate</td><td class="goodcell">Allowed</td><td>需定義任務完成證據與品質門檻。</td></tr> |
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<tr><td>Actual time saved</td><td class="goodcell">Allowed</td><td>需 baseline 與抽樣驗證。</td></tr> |
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<tr><td>Customer satisfaction</td><td class="goodcell">Allowed</td><td>需與 AI-assisted workflow 連結，避免單點歸因。</td></tr> |
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<tr><td>Output quality score</td><td class="goodcell">Allowed</td><td>需 rubric、reviewer、sample size 與異議流程。</td></tr> |
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<h2>資料 / API / 權限</h2> |
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<p><strong>Tables:</strong> <code>metric_registry</code>, <code>metric_reviews</code>, <code>metric_observations</code>, <code>gaming_signals</code>, <code>governance_exceptions</code>.</p> |
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<p><strong>APIs:</strong> <code>POST /console/metrics/register</code>, <code>POST /console/metrics/:id/review</code>, <code>GET /console/metrics/governance-scorecard</code>.</p> |
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<p><strong>Permissions:</strong> team owner can propose metrics; governance owner approves; Louis can override with reason; blocked metrics require exception audit.</p> |
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<div class="card"><h2>價值 / 錢路徑</h2><p>避免把預算花在 Token 和工具啟動次數上，將投資導向節省時間、提升品質、客戶滿意和任務完成，降低制度性浪費。</p></div> |
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<div class="card"><h2>人的能力提升</h2><p>主管學會設計不易被操弄的指標；員工知道 AI 使用的目標是交付成果，而不是堆活動量。</p></div> |
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<div class="card"><h2>下一輪升級</h2><p>接實際 Operating Console 指標設定 UI，加入 bad metric blocker、metric review workflow 和 gaming alert。</p></div> |
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<section class="card source"> |
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<h2>Market Maturity Inputs</h2> |
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<p>McKinsey notes productivity data can damage organizations if simple activity metrics such as lines of code or commit counts are misused: <a href="https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/yes-you-can-measure-software-developer-productivity?cid=other-eml-mtg-mip-mck">McKinsey developer productivity measurement</a>.</p> |
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<p>The SPACE framework balances Satisfaction, Performance, Activity, Communication, and Efficiency to avoid over-optimizing one visible activity metric: <a href="https://space-framework.com/">SPACE framework</a>.</p> |
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<p>DORA metrics connect delivery performance with reliability and stability rather than raw activity volume: <a href="https://dora.dev/guides/dora-metrics/">DORA metrics guide</a>.</p> |
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