Can I vibe code Lifetimely?

Build a full-stack E-commerce Profit & LTV Analytics application in Next.js (App Router), TypeScript, Tailwind CSS, and DuckDB / Postgres.

CORE DATA MODEL & ENTITIES:
1. Store: id, name, currency, timezone, platform ('shopify').
2. Order: id, store_id, order_number, created_at, total_price, subtotal_price, total_tax, total_shipping, total_discounts, total_cogs, gateway_fee, refund_amount, status.
3. OrderItem: id, order_id, product_id, variant_id, sku, quantity, price, cost_per_item.
4. AdSpend: id, store_id, date, platform ('meta', 'google', 'tiktok'), campaign_id, spend, impressions, clicks.
5. CohortData: month_cohort, initial_customers, m1_revenue, m2_revenue, m3_revenue, m6_revenue, m12_revenue.

KEY FEATURES TO IMPLEMENT:
1. Data Ingestion Engine:
   - Provide REST API webhook routes (`/api/webhooks/shopify/orders`) to ingest order creation, update, and refund payloads.
   - Parse order line items and look up item cost (`cost_per_item`) to compute total COGS per order automatically.
   - Support manual CSV upload for historical Ad Spend (date, platform, spend) and COGS map (sku, cost).

2. Daily P&L Engine (Financial Dashboard):
   - Calculate Net Profit = Gross Revenue - Refunds - COGS - Transaction Fees - Shipping Costs - Ad Spend.
   - Display a responsive financial table showing Gross Sales, Net Sales, COGS, Gross Profit, Total Ad Spend, Contribution Margin ($ and %), and Net Profit over a selected date range.
   - Include daily metric time-series charts using Recharts.

3. LTV & Cohort Analytics Engine:
   - Build a Cohort Matrix component: Group customers by acquisition month. Compute retained revenue and repeat purchase rate at Month 0, 1, 3, 6, and 12.
   - Implement a simple Predictive LTV calculation using logarithmic regression based on historical cohort performance.

4. Integration Logic:
   - Create mock OAuth and sync handlers for Meta Ads and Google Ads that pull daily spend into the AdSpend table.

FAILURE MODES & OUT OF SCOPE:
- OUT OF SCOPE: Real-time LLM natural language querying ('Profit Agent'), Amazon SP-API integrations, live multi-currency live rate conversions, complex inventory forecasting.
- FAILURE MODES TO HANDLE:
  - Missing COGS data: Default unmapped SKU costs to $0 and flag the order in an 'Unmapped COGS' notification tray.
  - Partial refunds: Accurately subtract refund amounts from gross revenue without doubling COGS deductions.
  - Ad Spend disparity: Handle days with missing ad spend gracefully by displaying an inline warning on the daily P&L.

TECH STACK: Next.js 14, TailwindCSS, Lucide React, Recharts, Prisma/Drizzle with Postgres or DuckDB-wasm for local-first analytics processing. Ensure all math functions for margin, ROAS, and CAC are fully covered with unit test suites.

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