Can I vibecode Bigin?

Build a comprehensive, production-ready personal replacement for Bigin CRM in an empty repository.
Use Next.js 15, TypeScript, PostgreSQL, Drizzle ORM, TailwindCSS, and Docker Compose; do not offer alternative stacks.

The core objective is to build a pipeline-centric CRM specifically designed for small businesses to manage customer-facing operations, mirroring Bigin's "DIY-ready" philosophy.

Core Sales & Pipeline Management:
- Visual Pipeline Management: Create a drag-and-drop Kanban interface that allows tracking deals from lead generation to closure, providing a 360-degree view of the sales process. Allow users to define custom pipeline stages.
- Contact & Record Management: Implement centralized storage for leads, contacts, and company information. Include fast global search, duplicate detection, merging, CSV import, and CSV export.
- Activities Tracking: Build a system to manage tasks, calls, and follow-ups. Provide a chronological interaction timeline with manual email and meeting logging, ensuring no leads fall through the cracks.

Automation & Productivity:
- Workflow Automation: Design a simple workflow engine that allows automating routine tasks (e.g., automatically creating a follow-up task when a deal moves to a certain stage).
- Multi-Channel Communication Logs: While avoiding complex real-time telephony, provide rich interfaces for logging and tracking emails, phone calls, and WhatsApp messages within the platform.
- AI-Powered Features: Integrate basic AI wrappers (using OpenAI/Anthropic APIs) for features like "Smart Summaries" of contact interactions, "Email Assistance" for drafting replies, and "Churn Analyzer" to flag at-risk deals.

Customization & Analytics:
- Customization ("Toppings"): Build an extensible schema that allows users to add custom fields to contacts, companies, and deals without writing new code.
- Advanced Analytics: Create standard dashboards and charts (using Recharts or similar) for real-time visibility into business performance, sales forecasting, and activity metrics. Include saved views and filters.

Technical Requirements:
- Make the first run work locally with one documented command (e.g., `docker-compose up`).
- Store all user data locally by default and make export straightforward.
- Put secrets in .env, ship .env.example, and never commit credentials.
- Add role-based access, an immutable activity log, backups, and a recovery command.
- Seed a realistic demo workspace and document field mapping for imports.
- Include clear empty, loading, success, and recoverable error states.
- Add input validation (Zod), safe filenames, and graceful handling of unavailable APIs.
- Write focused tests for the core transformation and one end-to-end happy path.
- Create a detailed README with setup, architecture, permissions, data location, and backup steps.
- Deliberately leave out automatic mailbox ingestion, commercial enrichment databases, and complex enterprise compliance.
- Finish by running the tests and listing the exact commands used.