7个Claude驱动的部门,1个公司大脑,16个咨询案例以及NPV、IRR和龙卷风计算器。由Ayman Khayat设计并构建。
AI 翻译
7 Claude-powered departments, 1 Company Brain, 16 consulting cases and an NPV, IRR and tornado calculator. Designed and built by Ayman Khayat.
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一分钟完成验证通过由七个 Claude 驱动的部门组成的模拟投资委员会,进行资本决策,使用 NPV、IRR、龙卷风敏感度模型,并演练咨询案例面试。
AI 翻译
Run a capital decision through a simulated investment committee of seven Claude-powered departments, model it with NPV/IRR/tornado sensitivity, and drill consulting case interviews.
取自仓库 README
正在加载完整 README。 以下为已保存的摘录。
Engineering economics & case practice. Put a capital decision in front of a simulated investment committee of seven Claude-powered departments, model it with NPV / IRR / tornado sensitivity, and drill consulting case interviews, all grounded in sourced GCC and industry figures.
Live demo · Case study · Designed & built by Ayman Khayat查看完整 README ↗Engineering economics & case practice. Put a capital decision in front of a simulated investment committee of seven Claude-powered departments, model it with NPV / IRR / tornado sensitivity, and drill consulting case interviews, all grounded in sourced GCC and industry figures.
Live demo · Case study · Designed & built by Ayman Khayat
The live demo runs in demo mode on GitHub Pages: sample committees replay, and the calculator and case practice work fully. Live AI runs need the serverless API on Vercel with an
ANTHROPIC_API_KEY(see Deploy). The hero and boardroom images are concept images made with Higgsfield from the project's real renders, and are labelled as such on the site. Prompts are logged indocs/higgsfield_prompts.md.
The page opens on a rounded hero panel, followed by a Live Committee section holding the real app: a 3D committee map (three.js) of metallic department hubs orbiting the Company Brain, with a live particle core, drifting dust and beads of light flowing along each department's link. Hovering a department flies the camera in and sets off a burst of its colour. Clicking zooms further and reveals that department's four specialist agents; once a verdict is in, the panel shows what each agent contributed. Without WebGL, or with reduced motion requested, it falls back to the flat SVG map. The render loop pauses while the scene is off-screen.
A decision runs through seven department agents, in parallel, each a separate Claude call with its own persona:
| Department | Argues from | Characteristic bias (kept on purpose) |
|---|---|---|
| Finance | NPV/IRR vs hurdle, payback, covenant headroom | Underweights option value and long horizons |
| Strategy & Corp Dev | Right to win, timing, build/borrow/buy | Optimistic about upside; treats execution as detail |
| Legal & Risk | Exposure, conditions precedent, RAPID "Agree" veto | Defensibility over expected value |
| Operations & Engineering | FEL stage, AACE estimate class, HSE, critical path | Wants one more stage of definition |
| Marketing & Sales | Bottom-up SOM, win rates, LTV:CAC | Optimistic demand, light on cost-to-serve |
| Sustainability & ESG | GHG scopes, SBTi / SGI / UAE Net Zero, IFRS S2 | Underweights near-term cash |
| HR & Talent | Capability gaps, Nitaqat / Emiratisation, ADKAR | "The organisation isn't ready" |
Each returns a schema-validated verdict (stance, confidence, 2–3 reasons, one risk flag, conditions, key metric). Only after all seven settle does the Company Brain rule. It acts as the RAPID "D", honours Legal and safety vetoes, corrects for each function's known bias, names the single hinge trade-off, and sets owned conditions and kill criteria.
An assumptions sheet (blue = input, financial-model convention), a live WACC slider with GCC reference bands, and NPV, IRR, MIRR, simple and discounted payback, PI and LCOE. Four exhibits in consulting style, each with a "so what" action title, footnotes and a source line:
Presets: 10 MWp factory solar (KSA), 5 MWe waste-heat-to-power (cement), SWRO energy-recovery retrofit (UAE), and a deliberately negative battery-arbitrage case. Send to the committee attaches the results as a committee pack, so Finance argues from your numbers.
16 original cases: 8 strategy (market sizing, profitability, breakeven, pricing, market entry, M&A) and 8 technical (energy go/no-go, LCOE/LCOW, debottlenecking, district cooling, plant efficiency). 12 are set in the Gulf.
flowchart LR
B[Browser] -- 7 parallel POST /api/department --> F1[Serverless fn × 7]
F1 -- Claude API --> C[(claude-opus-5 / claude-sonnet-5)]
B -- after all settle: POST /api/brain --> F2[Serverless fn]
F2 -- Claude API --> C
B -. static .-> S[index.html + ES modules]
/api hold ANTHROPIC_API_KEY and proxy every call. An optional APP_PASSCODE protects your budget on a public URL, and a best-effort per-IP limiter caps abuse.output_config.format with JSON Schema) guarantee parseable verdicts; adaptive thinking; server-side refusal fallback on Opus 5; the persona system prompts are prompt-cached.@anthropic-ai/sdk).| Tier | Departments | Brain | Typical full run |
|---|---|---|---|
| Standard | Opus 5 ($5 / $25 per M tokens) | Opus 5 | ≈ $0.40 |
| Economy | Sonnet 5 ($2 / $10) | Opus 5 | ≈ $0.20 |
Roughly 1.3K input and 1.5K output tokens per department (including adaptive thinking) and about 5K / 2.5K for the Brain. The header shows the actual spend from each response's usage.
npm install
echo "ANTHROPIC_API_KEY=sk-ant-..." > .env.local
npm run dev # http://localhost:5173
npm test # finance engine checks against the research sanity figures
Import the repo in Vercel, add ANTHROPIC_API_KEY (and optionally APP_PASSCODE) under Environment Variables, and deploy. No build settings are needed.
Every default is sourced in docs/research:
npm run build:cases)GCC tariffs and regulations change often; figures marked as estimates are triangulated, not published. Not investment advice.
api/ serverless functions: department, brain, coach, health
api/_lib/ Claude client, personas + JSON schemas
js/ app shell, simulation, constellation map, calculator, practice, finance engine
docs/research/ sourced research behind every default
scripts/ case-bank generator
tests/ finance engine tests
MIT licensed. Built with the Claude API.