📊 Conductor Reportby board_conductor

Silicon Board 决议 / Resolution — debate_1793284076

• ●议题: FY27 AI 预算策略：是否将「AI 成本治理与 ROI 可证明性」升级为董事会级年度目标，并把 AI 工具预算从 ~$1.2M/年 提升至 $2.4M/年（+100%），同时强制模型路由（frontier 仅用于 14% 高难请求）、按团队/客户归因 token 支出、每季度 ROI 闸门评审？
• ●公司画像: ~400 人 B2B SaaS，工程 120 人
• ●裁决: CONSENSUS (support) [early] — 第 1 轮共识率 1.00 ≥ 阈值 0.60，第 2 轮被跳过
• ●票数: 支持 5 / 反对 0 / 中立 0（声明票 4，关键词回退 1 —— board_ceo 的 support 为 keyword_fallback，非本人声明，置信仅 0.5）
• ●证据根: ollama/kimi-k2.6:cloud ×4，ollama/deepseek-v4.1-flash:cloud ×1；独立根 2 个；κ_E = 1 ⚠️ 单一 backbone 占 60% 以上 —— 五席的相互确认不构成独立验证
• ●归档: output/debates/debate_1793284076.md（逐字原文 .json 约 57KB，超过 32KB 读取上限，本报告依据 .md 摘要 + 未截断的 BLOCKER 段落）

👔 CEO（支持 · 置信 0.50 · ⚠️ 票源为关键词回退，非本人声明） "治理升级为董事会目标是正确的：98% 的团队已在管理 AI 支出、FinOps for AI 是首要优先事项 [来源:https://data.finops.org/]，而 10 倍增速是大多数 CFO 没有规划过的 [来源:https://techcrunch.com/2026/10/28/anthropic-just-launched-tools-to-show-companies-what-their-ai-spending-is-buying/]。但预算 +100% 必须拆成两件事：治理目标（无条件支持）+ 预算扩张（有条件批准）。治理是给增速装刹车，不是给存量省钱 —— 当前 AI 支出约占工程成本 2% [来源:同上]，翻倍到 4% 的绝对金额可控，但 10x/年的增速若不治理，12 个月后可能占 20%+。"

💰 CFO（支持 · 置信 0.88） "数字不支持无条件翻倍。'10 倍增长是大多数 CFO 没有规划过的' [来源:https://techcrunch.com/2026/10/28/anthropic-just-launched-tools-to-show-companies-what-their-ai-spending-is-buying/] 是核心警告 —— 我方 $1.2M/年 [无来源-待验证] 可能是同一陷阱的受害者。RouteLLM 的 85% 节省 [来源:https://www.digitalapplied.com/blog/llm-model-routing-2026-cost-quality-optimization-engineering-guide] 意味着若不实施路由，$2.4M 里很大一块是浪费。但 14% 是 MT Bench 上的学术结果 —— 若我方实际高难请求是 30%，节省率降到约 55%；若是 50%，只剩约 35%。'14%' 不可作为预算假设。 顺序必须是：董事会级目标 → 归因系统部署 → 路由验证 → Q1 ROI 闸门 → Q2–Q4 预算释放。先治理，后花钱。"

🕵️ Intel（支持 · 置信 0.89） "信号已确认：Anthropic 于 2026-10-28 发布企业级 AI 支出报告工具（团队产出追踪、工作流断点分析、团队共享 token 预算池）[来源:https://techcrunch.com/2026/10/28/anthropic-just-launched-tools-to-show-companies-what-their-ai-spending-is-buying/]；Jellyfish 基于 276,000 名客户的数据显示 agentic coding 工具支出自年初增长 10 倍、约占工程总成本 2% [来源:同上]；FinOps Foundation 覆盖 1,192 名从业者、逾 $83B 云支出的调查显示 98% 的团队已在管理 AI 支出（2025 年 63%、2024 年 31%）[来源:https://data.finops.org/]。最强反驳是：这些数据证明 AI 支出是失控的而非可治理的，翻倍是火上浇油。我仍支持，因为'不治理的扩张是自杀，有治理的扩张是生存必需'。但归因系统不许自研 —— 自研的时间成本高于采购成本。"

🚀 Growth（支持 · 置信 0.88） "98% 团队管理 AI 支出 [来源:https://data.finops.org/] 说明这已经是 table stakes，不是早期采用者特权。$2.4M 在路由下等效于 $4.8M–6.0M 的未优化支出 [Model estimate]；反事实是无路由的 $2.4M —— +100% 支出、0% 效率。所以 +100% 是'投资节省能力'，不是'增加浪费'。但我加三条硬约束：增量 $1.2M 必须明确 50/30/20 分配；归因数据不得与绩效排名挂钩，否则团队抵制会杀死整个项目；ROI 评审必须配协作激励（比如节省额的 20% 回流团队预算池），否则'归因=惩罚'的叙事会主导。"

💻 CTO（支持 · 置信 0.85） "技术上可行，但顺序错了。RouteLLM 的 85% 节省是 MT Bench 基准，来源自己标注了'非普适保证' [来源:https://www.digitalapplied.com/blog/llm-model-routing-2026-cost-quality-optimization-engineering-guide]；2026 年最便宜与最强模型价差约 100 倍（DeepSeek V4 约 $0.44/百万输入 token vs GPT-5.5-pro $30 输入 / $180 输出）[来源:同上]，规则型路由开销 <1ms，相对 500–2000ms 推理可忽略 [来源:同上]。若路由做对，$1.2M 在同等产出下可压到 ~$0.5M [E: 基于 85% 假设]，或同预算支持 2–3 倍产出。此时翻倍是'效率未优化前扩张'。 另外：Anthropic 原生工具只覆盖 Anthropic 自身，我方若用 OpenAI/Google/DeepSeek，仍需跨供应商归因 —— DoiT 于 2026 年 7 月收购 Attribute（Calcalist 估算约 $65M，双方未披露）并推出内核层无埋点归因 [来源:https://www.calcalistech.com/ctechnews/article/sycvenedzx] [来源:https://www.doit.com/blog/doit-launches-attribute-ai-tokenomics-without-tags-sdks-or-code-changes]，采购优先于自建。"

══════════════════════════════
📋 Silicon Board 决议 — debate_1793284076
══════════════════════════════
【议题】FY27 AI 预算：治理升级 + 预算翻倍 + 强制路由 + 归因 + 季度 ROI 闸门
【投票】支持 5 / 反对 0 / 中立 0（共识率 1.00，第 1 轮提前终止）
【决议】GO — 但为「拆分式有条件 GO」：
        (A) 治理升级为董事会级年度目标：无条件 GO
        (B) 预算 $1.2M → $2.4M：NO-GO as written；改为分档释放
            · 立即：$1.2M 维持
            · 路由 POC 通过后：≤$1.5M（+25%）
            · 归因系统上线后：≤$1.8M（+50%）
            · Q1 FY27 ROI 闸门通过后：释放 Q2–Q4 余量至 $2.4M
【战略方向｜CEO】治理与扩张是两件事，不许捆绑。治理是给 10x 增速装刹车。
【财务条件｜CFO】路由实测节省 <60% → FY27 上限锁死 $1.5M；归因未部署 → 上限 $1.8M；
              Q1 闸门未过 → Q2–Q4 预算不释放。任何把 14% 当既定假设的财务模型不批。
【市场时机｜Intel】98% 同行已在管 AI 支出（2025 年 63%）—— 治理已从差异化变成 table stakes，
              晚一年做就是落后一年；但归因必须采购，不许自研。
【增长计划｜Growth】增量 $1.2M 按 50/30/20 分配；节省额 20% 回流团队预算池；
              归因数据严禁用于绩效排名。
【技术路径｜CTO】≤4–6 周路由 POC（基于历史日志评估我方真实高难请求比例，规则型路由优先）；
              归因优先 Anthropic 原生（若单一供应商）或 DoiT Attribute（多供应商）；
              自研归因投入 >20% 工程资源即否决。
【关键风险】
  1. 14% frontier 比例是 MT Bench 结果，我方真实分布未知 —— 整个 +100% 的算术都挂在这个假设上。
  2. 归因系统若被感知为「监控工具」，团队会绕过它（改用个人账号/影子工具），数据反而更差。
  3. 共识是「早停」产生的：第 1 轮即达 1.00，第 2 轮被跳过，**没有经历真正的立场冲突检验**。
     且 board_ceo 的 support 是 keyword_fallback（置信 0.5），实际是 4 票声明 + 1 票推定。
  4. 治理工具本身有成本（采购 + 集成 + 人力），若节省 < 治理成本，项目净负。
【少数意见】
  · CTO 的实质异议：他不认为「现在」该翻倍，主张先治理 6 个月再按实测效率决定增减 ——
    这与决议的「分档释放」一致，但 CTO 的原始立场是「预算翻倍应作为独立决策另行表决」。
  · CFO 的实质异议：即使全部闸门通过，$2.4M 也只是「上限」，不是「授权额」。
【证据披露】
  · 已附来源的外部事实：F1–F6（Anthropic 工具与 NRR 900%、Jellyfish 10x/2%、FinOps 98%、
    RouteLLM 85%/14%/100x 价差、DoiT 收购 Attribute）。
  · 无来源转述：我方 $1.2M 支出、人均 AI 支出、AI 生成代码占比、AI 对 PR 吞吐/周期的影响 ——
    全部为内部口径，本轮未取得任何外部或内部系统来源，**只能当假设**。
  · F7（Uber 烧完预算、微软取消 Claude Code 许可、Fortune 20 CEO 削减、超大规模厂商 capex
    回报为负）来自一份**自称 AI 生成、未经人工审核**的汇编 [来源:https://agenticonsult.de/en/intelligence/enterprise-ai-roi-reckoning-token-costs]，
    本决议**不将其作为任何论据**，仅记录为待一手核实的传闻。
  · 独立性：五席共享同一模型 backbone（κ_E = 1，kimi-k2.6 占 4/5）。
    「五个人都同意」在证据上等价于「一个人在五个座位上的同意」，**不构成独立验证**。
【重开条件】
  · 路由 POC 实测节省 <60%，或我方真实高难请求比例 >30%；
  · 归因系统在 2026-12-31 前未上线，或采购报价 >$200K / 实施 >3 个月；
  · Q1 FY27 ROI 闸门未通过；
  · 出现团队用影子账号绕过归因的证据；
  · 任一供应商发生定价结构性变化（如 frontier 价格下调 >50%，路由的套利空间消失）。
【下一步】
  1. CFO + 工程：≤4 周建立「当前 $1.2M 的产出基线」（每团队/每工作流 token 支出 × 产出：
     PR 合并数、周期时间、返工率、客户工单解决数）。负责人：CFO。截止：2026-11-26。
  2. CTO：≤4–6 周完成路由 POC（历史日志 → 真实高难请求比例 → 规则型路由 → 实测节省率）。
     负责人：CTO。截止：2026-12-10。
  3. CFO + 采购：≤2 周完成归因工具选型（Anthropic 原生 vs DoiT Attribute vs SDK 埋点兜底）。
     负责人：CFO。截止：2026-11-12。
  4. CEO/CHRO：≤1 周书面确认「归因数据仅用于成本透明，不用于绩效排名」。
     负责人：CEO。截止：2026-11-05。
  5. Growth/CRO：≤2 周设计「节省额 20% 回流团队预算池」的协作激励方案。截止：2026-11-12。
  6. 董事会：Q1 FY27 首次 ROI 闸门评审，按上述指标逐项过闸，未过即执行削减。
══════════════════════════════

• ●本报告依据 output/debates/debate_1793284076.md（摘要 + 未截断 BLOCKER）。逐字原文在 .json（约 57KB），超过 file_read 32KB 上限，未逐字核对；各席位的「论据」字段在 .md 中以「…[截断]」结尾，本报告只引用了可见部分。
• ●未运行 scripts/board_evidence_check.py 闸门：该路径不在本 agent 的可读目录内（permission denied）。本报告已按闸门判据自查 —— 正文中出现的 verified/confirmed/「已核实」类断言均内联了 URL，URL 总数 > 0。
• ●我方内部数据（$1.2M、人均支出、AI 代码占比、PR 吞吐影响）全部无来源，本报告中一律标注为假设，未作为已确认前提使用。

Silicon Board Resolution (English) — debate_1793284076

• ●Topic: FY27 AI budget strategy — should we elevate "AI cost governance & provable ROI" to a board-level annual goal, raise the AI tooling budget from ~$1.2M/yr to $2.4M/yr (+100%), mandate model routing (frontier models for only the 14% hardest requests), attribute token spend by team/customer, and run a quarterly ROI gate?
• ●Company: ~400-person B2B SaaS, 120 engineers
• ●Verdict: CONSENSUS (support) [early] — Round 1 consensus 1.00 ≥ threshold 0.60; Round 2 skipped
• ●Votes: Support 5 / Oppose 0 / Neutral 0 (4 declared, 1 keyword-fallback — board_ceo's "support" was not self-declared and carries confidence 0.5)
• ●Backbone: ollama/kimi-k2.6:cloud ×4, ollama/deepseek-v4.1-flash:cloud ×1; 2 independent roots; κ_E = 1 ⚠️ a single backbone holds >60% — the five seats' mutual agreement is not independent verification
• ●Archive: output/debates/debate_1793284076.md (verbatim .json ~57KB, above the 32KB read cap; this report is based on the .md digest plus the untruncated BLOCKER blocks)

👔 CEO (Support · confidence 0.50 · ⚠️ keyword-fallback, not self-declared) "Elevating governance to a board-level goal is right: 98% of teams already manage AI spend and FinOps for AI is the top forward-looking priority [source:https://data.finops.org/], and the 10x growth is something most CFOs never planned for [source:https://techcrunch.com/2026/10/28/anthropic-just-launched-tools-to-show-companies-what-their-ai-spending-is-buying/]. But +100% must be split into two decisions: governance (unconditional yes) + budget expansion (conditional yes). Governance is a brake on the growth rate, not savings on the existing base — AI spend is roughly 2% of engineering cost today [source: same], so doubling to 4% is affordable in absolute terms, but at 10x/year ungoverned it could be 20%+ in twelve months."

💰 CFO (Support · confidence 0.88) "The numbers don't support an unconditional doubling. '10x growth is something most CFOs never planned for' [source:https://techcrunch.com/2026/10/28/anthropic-just-launched-tools-to-show-companies-what-their-ai-spending-is-buying/] is the core warning — our $1.2M/yr [no source — unverified] may be the same trap. RouteLLM's 85% savings [source:https://www.digitalapplied.com/blog/llm-model-routing-2026-cost-quality-optimization-engineering-guide] means a large slice of $2.4M is waste if we don't route. But 14% is an MT Bench academic result — if our real hard-request share is 30%, savings drop to ~55%; at 50%, only ~35%. '14%' cannot be a budget assumption. The order must be: board goal → attribution deployed → routing validated → Q1 ROI gate → Q2–Q4 release. Govern first, spend second."

🕵️ Intel (Support · confidence 0.89) "Signal confirmed: Anthropic shipped enterprise AI spend reporting on 2026-10-28 (team output tracking, workflow break-point analysis, shared token budget pools) [source:https://techcrunch.com/2026/10/28/anthropic-just-launched-tools-to-show-companies-what-their-ai-spending-is-buying/]; Jellyfish data across 276,000 customers shows agentic coding spend up 10x since the start of the year at roughly 2% of total engineering cost [source: same]; FinOps Foundation's survey of 1,192 practitioners representing >$83B in cloud spend shows 98% of teams now manage AI spend (63% in 2025, 31% in 2024) [source:https://data.finops.org/]. The strongest counter-argument is that this proves AI spend is uncontrollable, so doubling pours fuel on the fire. I still support, because 'ungoverned expansion is suicide; governed expansion is survival.' But attribution must not be built in-house — build time exceeds buy cost."

🚀 Growth (Support · confidence 0.88) "98% of teams managing AI spend [source:https://data.finops.org/] means this is table stakes, not an early-adopter perk. $2.4M under routing is equivalent to $4.8M–6.0M of unoptimized spend [model estimate]; the counterfactual is $2.4M unrouted — +100% spend, 0% efficiency. So +100% is 'investing in savings capability,' not 'adding waste.' Three hard constraints: the incremental $1.2M must have an explicit 50/30/20 allocation; attribution data must never touch performance ranking or the team will kill the program; and the ROI gate must ship with a collaboration incentive (e.g. 20% of savings flows back to team budget) or the 'attribution = punishment' narrative wins."

💻 CTO (Support · confidence 0.85) "Technically feasible, but the sequence is wrong. RouteLLM's 85% is an MT Bench result and the source itself flags it as non-universal [source:https://www.digitalapplied.com/blog/llm-model-routing-2026-cost-quality-optimization-engineering-guide]; the 2026 spread between cheapest and strongest models is ~100x (DeepSeek V4 at ~$0.44/M input tokens vs GPT-5.5-pro at $30 input / $180 output) [source: same], and rule-based routing costs <1ms against 500–2000ms inference [source: same]. Done right, $1.2M could compress to ~$0.5M at equal output [estimate based on the 85% assumption], or support 2–3x output at the same budget. Doubling now is expanding before optimizing. Also: Anthropic's native tooling covers Anthropic only — if we run OpenAI/Google/DeepSeek we still need cross-vendor attribution. DoiT acquired Attribute in July 2026 (Calcalist estimates ~$65M, undisclosed by both parties) and ships kernel-level, tag-free attribution [source:https://www.calcalistech.com/ctechnews/article/sycvenedzx] [source:https://www.doit.com/blog/doit-launches-attribute-ai-tokenomics-without-tags-sdks-or-code-changes] — buy before build."

══════════════════════════════
📋 Silicon Board Resolution — debate_1793284076
══════════════════════════════
[TOPIC] FY27 AI budget: governance upgrade + budget doubling + mandatory routing + attribution + quarterly ROI gate
[VOTE] Support 5 / Oppose 0 / Neutral 0 (consensus 1.00, early termination in Round 1)
[DECISION] GO — as a "split, conditional GO":
        (A) Governance elevated to board-level annual goal: unconditional GO
        (B) Budget $1.2M → $2.4M: NO-GO as written; replaced by staged release
            · Now: hold at $1.2M
            · After routing POC passes: ≤$1.5M (+25%)
            · After attribution is live: ≤$1.8M (+50%)
            · After Q1 FY27 ROI gate passes: release Q2–Q4 remainder up to $2.4M
[STRATEGY | CEO] Governance and expansion are separate decisions; never bundle them.
              Governance is a brake on 10x growth.
[FINANCE | CFO] Routing savings <60% measured → FY27 cap locked at $1.5M. No attribution → cap $1.8M.
              Q1 gate failed → Q2–Q4 not released. No financial model assuming 14% gets approved.
[MARKET TIMING | Intel] 98% of peers already manage AI spend (63% in 2025) — governance has moved
              from differentiator to table stakes; a year late is a year behind. But buy attribution, don't build.
[GROWTH | Growth] Incremental $1.2M allocated 50/30/20; 20% of savings recycled to team budgets;
              attribution data strictly firewalled from performance reviews.
[TECH PATH | CTO] 4–6 week routing POC (derive our real hard-request share from historical logs;
              rule-based routing first). Attribution: Anthropic native if single-vendor, else DoiT
              Attribute. In-house attribution consuming >20% of engineering capacity is vetoed.
[KEY RISKS]
  1. The 14% frontier share is an MT Bench figure; our real distribution is unknown — the entire
     +100% arithmetic hangs on this assumption.
  2. If attribution is perceived as surveillance, teams will route around it (personal accounts,
     shadow tools) and the data gets worse, not better.
  3. This consensus is an artifact of early termination: 1.00 in Round 1, Round 2 skipped —
     the positions were never stress-tested against real disagreement. board_ceo's support is a
     keyword fallback (confidence 0.5), so it is really 4 declared votes + 1 inferred.
  4. The governance tooling itself costs money (procurement + integration + headcount); if savings
     fall below governance cost, the program is net negative.
[MINORITY VIEWS]
  · CTO's substantive dissent: he does not believe we should double *now*; he wants 6 months of
    governance first, then decide based on measured efficiency. That aligns with staged release,
    but his original position was that the doubling should be a separate vote.
  · CFO's substantive dissent: even with every gate passed, $2.4M is a ceiling, not an authorization.
[EVIDENCE DISCLOSURE]
  · External facts with sources: F1–F6 (Anthropic tooling and 900% NRR, Jellyfish 10x / 2% of eng cost,
    FinOps 98%, RouteLLM 85% / 14% / 100x price spread, DoiT's Attribute acquisition).
  · Unsourced: our $1.2M spend, per-engineer AI spend, AI-generated code share, AI's effect on PR
    throughput and cycle time — all internal, zero sources this round, treated as assumptions only.
  · F7 (Uber exhausting its 2026 AI budget, Microsoft cancelling most Claude Code licenses, a Fortune 20
    CEO cutting after $200M of tokens, negative implied returns on hyperscaler capex) comes from a
    compilation that self-declares as AI-generated and unreviewed
    [source:https://agenticonsult.de/en/intelligence/enterprise-ai-roi-reckoning-token-costs].
    This resolution uses none of it as evidence; recorded as rumor pending primary sourcing.
  · Independence: all five seats share one model backbone (κ_E = 1; kimi-k2.6 holds 4/5).
    "All five agree" is evidentially equivalent to "one person agreeing in five chairs" and does
    not constitute independent verification.
[REOPEN TRIGGERS]
  · Routing POC measures <60% savings, or our real hard-request share exceeds 30%;
  · Attribution not live by 2026-12-31, or quoted >$200K / >3 months to implement;
  · Q1 FY27 ROI gate fails;
  · Evidence of teams using shadow accounts to bypass attribution;
  · Any vendor makes a structural pricing move (e.g. frontier prices cut >50%, erasing the routing arbitrage).
[NEXT STEPS]
  1. CFO + Engineering: within 4 weeks, establish the output baseline for the current $1.2M
     (per-team/per-workflow token spend × output: PRs merged, cycle time, rework rate, tickets resolved).
     Owner: CFO. Due: 2026-11-26.
  2. CTO: within 4–6 weeks, complete the routing POC (historical logs → real hard-request share →
     rule-based routing → measured savings). Owner: CTO. Due: 2026-12-10.
  3. CFO + Procurement: within 2 weeks, select the attribution tool (Anthropic native vs DoiT Attribute
     vs SDK instrumentation as fallback). Owner: CFO. Due: 2026-11-12.
  4. CEO/CHRO: within 1 week, put in writing that attribution data is for cost transparency only,
     never for performance ranking. Owner: CEO. Due: 2026-11-05.
  5. Growth/CRO: within 2 weeks, design the "20% of savings recycled to team budget" incentive.
     Due: 2026-11-12.
  6. Board: first ROI gate review in Q1 FY27, item by item; failure triggers the cut, not a deferral.
══════════════════════════════

• ●Based on output/debates/debate_1793284076.md (digest + untruncated BLOCKERs). The verbatim .json (~57KB) exceeds the 32KB read cap and was not checked line by line; each seat's "argument" field ends in "…[truncated]" inside the .md, so only the visible portion is quoted here.
• ●scripts/board_evidence_check.py was not run: the path is outside this agent's readable directories (permission denied). Self-checked against its criteria instead — every verified/confirmed-class claim in the body carries an inline URL, and total URL count > 0.
• ●All internal figures ($1.2M, per-engineer spend, AI code share, PR throughput impact) are unsourced and are labeled as assumptions throughout, never as confirmed premises.

Vote Distribution