Can I vibe code Kleene?

Build an open-source data pipeline and analytics dashboard stack for an e-commerce brand using Node.js, DuckDB, dbt-core, and Streamlit.

1. DATA INGESTION & MODELS:
- Create Python extraction scripts that pull incremental orders, products, and customers from the Shopify REST API and store raw JSON records in DuckDB.
- Create extraction scripts for Meta Ads API and Google Ads API to pull daily campaign spend and performance metrics.
- Establish an idempotent sync strategy using updated_at timestamps to prevent duplicate records on re-runs.

2. TRANSFORMATIONS (dbt):
- Configure dbt models to parse raw JSON payloads into clean staging tables (`stg_shopify_orders`, `stg_meta_spend`).
- Build intermediate models that join order line items with customer profiles to compute lifetime value (LTV) and 30-day repeat purchase rate.
- Build a unified daily marketing performance table (`fct_daily_marketing_roi`) joining combined ad spend against total net revenue by date.

3. ERROR HANDLING & MONITORING:
- Implement backoff retry mechanisms for 429 rate limits across API connectors.
- Add a logging pipeline that captures run statuses, record counts, and errors into a `sync_logs` table.
- Send an alert webhook to Discord/Slack if a pipeline fails or if data volume drops below expected thresholds.

4. DASHBOARD UI:
- Build a Streamlit dashboard that connects to DuckDB to display high-level KPIs: Blended CAC, MER (Marketing Efficiency Ratio), Net Revenue, and LTV cohorts.
- Include interactive date filtering and platform comparison breakdowns.

OUT OF SCOPE:
- Enterprise single sign-on (SSO).
- Complex multi-touch attribution algorithms beyond basic daily date-matching.

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