AutoFileForm CMS

Overview

AutoFileForm CMS is a specialized e-commerce platform for automotive parts suppliers. Built with Next.js 14, TypeScript, and Tailwind CSS, it features dynamic order forms that adapt based on vehicle specifications, real-time inventory tracking, complex pricing rules, and streamlined order management. The feature-based architecture makes it maintainable and scalable.

The Business Case

Automotive parts businesses face unique challenges: parts vary by vehicle year/make/model, fitment is complex, pricing depends on multiple factors (quantity, dealer tier, seasonal promotions), and inventory management is critical. Generic e-commerce platforms don't handle these needs well. This CMS was built specifically for the automotive industry.

Core Features

Dynamic Order Forms adapt based on vehicle selection. Choose a 2015 Honda Civic, and the form shows compatible parts. Switch to a 2020 Ford F-150, and options change completely. Form fields appear or hide based on selections, guided by fitment data. This prevents order errors and improves user experience.

Inventory Management provides real-time stock tracking across multiple warehouses. The system shows availability, reserved stock (orders in process), and incoming shipments. Low-stock alerts notify managers automatically. Integration with warehouse systems keeps inventory synchronized.

Pricing Engine handles complex rules: base pricing, quantity discounts, dealer tier pricing, promotional pricing, and bundle discounts. The engine evaluates rules in priority order and applies the best price automatically. Price calculations happen server-side for security and consistency.

Order Processing streamlines the workflow from cart to fulfillment. Orders route to appropriate warehouses based on inventory and shipping address. Automated emails keep customers informed. The system generates pick lists, packing slips, and shipping labels. Status tracking shows order progress.

Admin Dashboard gives staff powerful tools: bulk product imports via CSV, price rule configuration, order management, customer service tools, and analytics. The dashboard is role-based—warehouse staff see fulfillment views, managers see analytics, customer service sees order history.

Technical Architecture

Feature-Based Structure organizes code by business capability rather than technical layer. Each feature (products, orders, inventory, pricing) has its own folder containing components, hooks, actions, and types. This colocation makes features easy to understand and modify independently.

Next.js App Router provides the foundation. Server components fetch data efficiently, client components handle interactivity, and server actions process mutations. The architecture minimizes client-side JavaScript while delivering a responsive experience.

PostgreSQL Database stores relational data: products, vehicles, fitment data, orders, and customers. Proper normalization prevents data inconsistencies. Indexes optimize common queries. Row-level security protects sensitive data.

Tailwind CSS with a custom design system ensures visual consistency. Design tokens define colors, spacing, typography, and components. The system is mobile-first, accessible, and includes a dark mode that warehouse staff appreciate during night shifts.

TypeScript provides end-to-end type safety. Shared types between client and server prevent API mismatches. Zod validates external data (forms, API responses). The type system catches bugs during development rather than production.

Technical Challenges

Fitment Data Complexity was substantial. A single part might fit 100+ vehicle configurations. I normalized the data model to avoid redundancy, created efficient queries using PostgreSQL's array operations, and built a smart caching layer. Query performance improved from 800ms to 60ms.

Pricing Rule Priority required careful logic. Multiple rules can apply simultaneously—which takes precedence? I implemented a priority system with explicit ordering, rule activation dates, and exclusivity flags. Testing covered edge cases thoroughly to prevent pricing errors.

Real-Time Inventory needed eventual consistency. When orders are placed simultaneously for the last item, both shouldn't succeed. I used PostgreSQL transactions with row-level locking, implemented optimistic locking with version numbers, and added queue-based processing for high-volume scenarios.

What I Learned

Feature-Based Architecture transformed my approach to large applications. Instead of navigating between components/, hooks/, utils/ folders, everything related to a feature lives together. New developers understand the codebase faster. Changes are localized, reducing ripple effects.

Next.js App Router changed my React patterns. Server components for data fetching eliminated useEffect waterfalls. Server actions simplified mutations—no API routes needed for simple operations. The mental model takes adjustment but delivers better performance.

Domain Modeling became concrete through this project. Understanding automotive fitment, dealer relationships, and fulfillment workflows required deep domain knowledge. The database schema and code structure reflect this understanding. Good software mirrors the problem domain clearly.

Production Concerns like error handling, logging, monitoring, and graceful degradation became priorities. It's not enough for features to work in development—they must work reliably under load, with poor connections, and when dependencies fail. This project taught me defensive programming.

Business Impact

The platform reduced order errors by 60% through dynamic forms that prevent incorrect selections. Processing time dropped from 15 minutes per order to 2 minutes with automation. Customer satisfaction improved with real-time stock visibility and accurate fulfillment estimates.

The feature-based architecture paid maintenance dividends. When requirements changed—and they always do—updates were localized. New features integrated cleanly. Technical debt stayed manageable because the codebase structure encouraged good practices.

Read the blog post about feature-based architecture and domain-driven design.